From dbb3e2b81086f97819ebd21457148c7160a4d703 Mon Sep 17 00:00:00 2001 From: Chavithra PARANA Date: Mon, 28 Mar 2022 23:31:39 +0200 Subject: [PATCH] Pyinstaller : remove property_cached, user_agent and vaderSentiment --- build/pyinstaller/property_cached/__init__.py | 159 - .../pyinstaller/property_cached/_version.txt | 1 - build/pyinstaller/user_agent/__init__.py | 4 - build/pyinstaller/user_agent/base.py | 627 -- build/pyinstaller/user_agent/cli.py | 21 - .../user_agent/data/smartphone_dev_ext.json | 2820 ------- .../user_agent/data/smartphone_dev_id.json | 180 - .../user_agent/data/tablet_dev_ext.json | 757 -- .../user_agent/data/tablet_dev_id.json | 52 - build/pyinstaller/user_agent/device.py | 15 - build/pyinstaller/user_agent/error.py | 15 - build/pyinstaller/user_agent/warning.py | 13 - build/pyinstaller/vaderSentiment/__init__.py | 1 - .../vaderSentiment/emoji_utf8_lexicon.txt | 3570 -------- .../vaderSentiment/vaderSentiment.py | 687 -- .../vaderSentiment/vader_lexicon.txt | 7520 ----------------- 16 files changed, 16442 deletions(-) delete mode 100644 build/pyinstaller/property_cached/__init__.py delete mode 100644 build/pyinstaller/property_cached/_version.txt delete mode 100644 build/pyinstaller/user_agent/__init__.py delete mode 100644 build/pyinstaller/user_agent/base.py delete mode 100644 build/pyinstaller/user_agent/cli.py delete mode 100644 build/pyinstaller/user_agent/data/smartphone_dev_ext.json delete mode 100644 build/pyinstaller/user_agent/data/smartphone_dev_id.json delete mode 100644 build/pyinstaller/user_agent/data/tablet_dev_ext.json delete mode 100644 build/pyinstaller/user_agent/data/tablet_dev_id.json delete mode 100644 build/pyinstaller/user_agent/device.py delete mode 100644 build/pyinstaller/user_agent/error.py delete mode 100644 build/pyinstaller/user_agent/warning.py delete mode 100644 build/pyinstaller/vaderSentiment/__init__.py delete mode 100644 build/pyinstaller/vaderSentiment/emoji_utf8_lexicon.txt delete mode 100644 build/pyinstaller/vaderSentiment/vaderSentiment.py delete mode 100644 build/pyinstaller/vaderSentiment/vader_lexicon.txt diff --git a/build/pyinstaller/property_cached/__init__.py b/build/pyinstaller/property_cached/__init__.py deleted file mode 100644 index 3353048943d..00000000000 --- a/build/pyinstaller/property_cached/__init__.py +++ /dev/null @@ -1,159 +0,0 @@ -import asyncio -import functools -import pkg_resources -import threading -import weakref -from time import time - - -__author__ = "Martin Larralde" -__email__ = "martin.larralde@ens-paris-saclay.fr" -__license__ = "BSD" -__version__ = pkg_resources.resource_string(__name__, "_version.txt").decode('utf-8').strip() - - -class cached_property(property): - """ - A property that is only computed once per instance and then replaces itself - with an ordinary attribute. Deleting the attribute resets the property. - Source: https://github.com/bottlepy/bottle/commit/fa7733e075da0d790d809aa3d2f53071897e6f76 - """ # noqa - - _sentinel = object() - _update_wrapper = functools.update_wrapper - - def __init__(self, func): - self.cache = weakref.WeakKeyDictionary() - self.func = func - self._update_wrapper(func) - - def __get__(self, obj, cls): - if obj is None: - return self - - if asyncio and asyncio.iscoroutinefunction(self.func): - return self._wrap_in_coroutine(obj) - - value = self.cache.get(obj, self._sentinel) - if value is self._sentinel: - value = self.cache[obj] = self.func(obj) - - return value - - def __set_name__(self, owner, name): - self.__name__ = name - - def __set__(self, obj, value): - self.cache[obj] = value - - def __delete__(self, obj): - del self.cache[obj] - - def _wrap_in_coroutine(self, obj): - - @functools.wraps(obj) - @asyncio.coroutine - def wrapper(): - value = self.cache.get(obj, self._sentinel) - if value is self._sentinel: - self.cache[obj] = value = asyncio.ensure_future(self.func(obj)) - return value - - return wrapper() - - -class threaded_cached_property(cached_property): - """ - A cached_property version for use in environments where multiple threads - might concurrently try to access the property. - """ - - def __init__(self, func): - super(threaded_cached_property, self).__init__(func) - self.lock = threading.RLock() - - def __get__(self, obj, cls): - if obj is None: - return self - with self.lock: - return super(threaded_cached_property, self).__get__(obj, cls) - - def __set__(self, obj, value): - with self.lock: - super(threaded_cached_property, self).__set__(obj, value) - - def __delete__(self, obj): - with self.lock: - super(threaded_cached_property, self).__delete__(obj) - - -class cached_property_with_ttl(cached_property): - """ - A property that is only computed once per instance and then replaces itself - with an ordinary attribute. Setting the ttl to a number expresses how long - the property will last before being timed out. - """ - - def __init__(self, ttl=None): - if callable(ttl): - func = ttl - ttl = None - else: - func = None - self.ttl = ttl - super(cached_property_with_ttl, self).__init__(func) - - def __call__(self, func): - super(cached_property_with_ttl, self).__init__(func) - return self - - def __get__(self, obj, cls): - if obj is None: - return self - - now = time() - if obj in self.cache: - value, last_updated = self.cache[obj] - if not self.ttl or self.ttl > now - last_updated: - return value - - value, _ = self.cache[obj] = (self.func(obj), now) - return value - - def __set__(self, obj, value): - super(cached_property_with_ttl, self).__set__(obj, (value, time())) - - -# Aliases to make cached_property_with_ttl easier to use -cached_property_ttl = cached_property_with_ttl -timed_cached_property = cached_property_with_ttl - - -class threaded_cached_property_with_ttl( - cached_property_with_ttl, threaded_cached_property -): - """ - A cached_property version for use in environments where multiple threads - might concurrently try to access the property. - """ - - def __init__(self, ttl=None): - super(threaded_cached_property_with_ttl, self).__init__(ttl) - self.lock = threading.RLock() - - def __get__(self, obj, cls): - with self.lock: - return super(threaded_cached_property_with_ttl, self).__get__(obj, cls) - - def __set__(self, obj, value): - with self.lock: - return super(threaded_cached_property_with_ttl, self).__set__(obj, value) - - def __delete__(self, obj): - with self.lock: - return super(threaded_cached_property_with_ttl, self).__delete__(obj) - - -# Alias to make threaded_cached_property_with_ttl easier to use -threaded_cached_property_ttl = threaded_cached_property_with_ttl -timed_threaded_cached_property = threaded_cached_property_with_ttl diff --git a/build/pyinstaller/property_cached/_version.txt b/build/pyinstaller/property_cached/_version.txt deleted file mode 100644 index 9edc58bb1dd..00000000000 --- a/build/pyinstaller/property_cached/_version.txt +++ /dev/null @@ -1 +0,0 @@ -1.6.4 diff --git a/build/pyinstaller/user_agent/__init__.py b/build/pyinstaller/user_agent/__init__.py deleted file mode 100644 index d2656ae9e38..00000000000 --- a/build/pyinstaller/user_agent/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from user_agent.base import * # noqa: F403 pylint: disable=wildcard-import -from user_agent.error import * # noqa: F403 pylint: disable=wildcard-import - -__version__ = '0.1.10' diff --git a/build/pyinstaller/user_agent/base.py b/build/pyinstaller/user_agent/base.py deleted file mode 100644 index a6dc292b9f7..00000000000 --- a/build/pyinstaller/user_agent/base.py +++ /dev/null @@ -1,627 +0,0 @@ -# -*- coding: utf-8 -*- -# pylint: disable=line-too-long -""" -This module is for generating random, valid web navigator's - configs & User-Agent HTTP headers. - -Functions: -* generate_user_agent: generates User-Agent HTTP header -* generate_navigator: generates web navigator's config -* generate_navigator_js: generates web navigator's config with keys - identical keys used in navigator object - -FIXME: -* add Edge, Safari and Opera support -* add random config i.e. windows is more common than linux - -Specs: -* https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/User-Agent/Firefox -* http://msdn.microsoft.com/en-us/library/ms537503(VS.85).aspx -* https://developer.chrome.com/multidevice/user-agent -* http://www.javascriptkit.com/javatutors/navigator.shtml - -Release history: -* https://en.wikipedia.org/wiki/Firefox_release_history -* https://en.wikipedia.org/wiki/Google_Chrome_release_history -* https://en.wikipedia.org/wiki/Internet_Explorer_version_history -* https://en.wikipedia.org/wiki/Android_version_history - -Lists of user agents: -* http://www.useragentstring.com/ -* http://www.user-agents.org/ -* http://www.webapps-online.com/online-tools/user-agent-strings - -""" -# pylint: enable=line-too-long - -from random import SystemRandom -from datetime import datetime, timedelta -from itertools import product - -import six - -from .warning import warn -# pylint: disable=unused-import -from .device import SMARTPHONE_DEV_IDS, TABLET_DEV_IDS -# pylint: enable=unused-import -from .error import InvalidOption - -__all__ = ['generate_user_agent', 'generate_navigator', - 'generate_navigator_js'] - -randomizer = SystemRandom() -DEVICE_TYPE_OS = { - 'desktop': ('win', 'mac', 'linux'), - 'smartphone': ('android',), - 'tablet': ('android',), -} -OS_DEVICE_TYPE = { - 'win': ('desktop',), - 'linux': ('desktop',), - 'mac': ('desktop',), - 'android': ('smartphone', 'tablet'), -} -DEVICE_TYPE_NAVIGATOR = { - 'desktop': ('chrome', 'firefox', 'ie'), - 'smartphone': ('firefox', 'chrome'), - 'tablet': ('firefox', 'chrome'), -} -NAVIGATOR_DEVICE_TYPE = { - 'ie': ('desktop',), - 'chrome': ('desktop', 'smartphone', 'tablet'), - 'firefox': ('desktop', 'smartphone', 'tablet'), -} -OS_PLATFORM = { - 'win': ( - 'Windows NT 5.1', # Windows XP - 'Windows NT 6.1', # Windows 7 - 'Windows NT 6.2', # Windows 8 - 'Windows NT 6.3', # Windows 8.1 - 'Windows NT 10.0', # Windows 10 - ), - 'mac': ( - 'Macintosh; Intel Mac OS X 10.8', - 'Macintosh; Intel Mac OS X 10.9', - 'Macintosh; Intel Mac OS X 10.10', - 'Macintosh; Intel Mac OS X 10.11', - 'Macintosh; Intel Mac OS X 10.12', - ), - 'linux': ( - 'X11; Linux', - 'X11; Ubuntu; Linux', - ), - 'android': ( - 'Android 4.4', # 2013-10-31 - 'Android 4.4.1', # 2013-12-05 - 'Android 4.4.2', # 2013-12-09 - 'Android 4.4.3', # 2014-06-02 - 'Android 4.4.4', # 2014-06-19 - 'Android 5.0', # 2014-11-12 - 'Android 5.0.1', # 2014-12-02 - 'Android 5.0.2', # 2014-12-19 - 'Android 5.1', # 2015-03-09 - 'Android 5.1.1', # 2015-04-21 - 'Android 6.0', # 2015-10-05 - 'Android 6.0.1', # 2015-12-07 - #'Android 7.0', # 2016-08-22 - #'Android 7.1', # 2016-10-04 - #'Android 7.1.1', # 2016-12-05 - ), -} -OS_CPU = { - 'win': ( - '', # 32bit - 'Win64; x64', # 64bit - 'WOW64', # 32bit process on 64bit system - ), - 'linux': ( - 'i686', # 32bit - 'x86_64', # 64bit - 'i686 on x86_64', # 32bit process on 64bit system - ), - 'mac': ( - '', - ), - 'android': ( - 'armv7l', # 32bit - 'armv8l', # 64bit - ), -} -OS_NAVIGATOR = { - 'win': ('chrome', 'firefox', 'ie'), - 'mac': ('firefox', 'chrome'), - 'linux': ('chrome', 'firefox'), - 'android': ('firefox', 'chrome'), -} -NAVIGATOR_OS = { - 'chrome': ('win', 'linux', 'mac', 'android'), - 'firefox': ('win', 'linux', 'mac', 'android'), - 'ie': ('win',), -} -FIREFOX_VERSION = ( - ('45.0', datetime(2016, 3, 8)), - ('46.0', datetime(2016, 4, 26)), - ('47.0', datetime(2016, 6, 7)), - ('48.0', datetime(2016, 8, 2)), - ('49.0', datetime(2016, 9, 20)), - ('50.0', datetime(2016, 11, 15)), - ('51.0', datetime(2017, 1, 24)), -) - -# Top chrome builds from website access log -# for september, october 2020 -CHROME_BUILD = ''' -80.0.3987.132 -80.0.3987.149 -80.0.3987.99 -81.0.4044.117 -81.0.4044.138 -83.0.4103.101 -83.0.4103.106 -83.0.4103.96 -84.0.4147.105 -84.0.4147.111 -84.0.4147.125 -84.0.4147.135 -84.0.4147.89 -85.0.4183.101 -85.0.4183.102 -85.0.4183.120 -85.0.4183.121 -85.0.4183.127 -85.0.4183.81 -85.0.4183.83 -86.0.4240.110 -86.0.4240.111 -86.0.4240.114 -86.0.4240.183 -86.0.4240.185 -86.0.4240.75 -86.0.4240.78 -86.0.4240.80 -86.0.4240.96 -86.0.4240.99 -'''.strip().splitlines() - -IE_VERSION = ( - # (numeric ver, string ver, trident ver) # release year - (8, 'MSIE 8.0', '4.0'), # 2009 - (9, 'MSIE 9.0', '5.0'), # 2011 - (10, 'MSIE 10.0', '6.0'), # 2012 - (11, 'MSIE 11.0', '7.0'), # 2013 -) -USER_AGENT_TEMPLATE = { - 'firefox': ( - 'Mozilla/5.0' - ' ({system[ua_platform]}; rv:{app[build_version]})' - ' Gecko/{app[geckotrail]}' - ' Firefox/{app[build_version]}' - ), - 'chrome': ( - 'Mozilla/5.0' - ' ({system[ua_platform]}) AppleWebKit/537.36' - ' (KHTML, like Gecko)' - ' Chrome/{app[build_version]} Safari/537.36' - ), - 'chrome_smartphone': ( - 'Mozilla/5.0' - ' ({system[ua_platform]}) AppleWebKit/537.36' - ' (KHTML, like Gecko)' - ' Chrome/{app[build_version]} Mobile Safari/537.36' - ), - 'chrome_tablet': ( - 'Mozilla/5.0' - ' ({system[ua_platform]}) AppleWebKit/537.36' - ' (KHTML, like Gecko)' - ' Chrome/{app[build_version]} Safari/537.36' - ), - 'ie_less_11': ( - 'Mozilla/5.0' - ' (compatible; {app[build_version]}; {system[ua_platform]};' - ' Trident/{app[trident_version]})' - ), - 'ie_11': ( - 'Mozilla/5.0' - ' ({system[ua_platform]}; Trident/{app[trident_version]};' - ' rv:11.0) like Gecko' - ), -} - - -def get_firefox_build(): - build_ver, date_from = randomizer.choice(FIREFOX_VERSION) - try: - idx = FIREFOX_VERSION.index((build_ver, date_from)) - _, date_to = FIREFOX_VERSION[idx + 1] - except IndexError: - date_to = date_from + timedelta(days=1) - sec_range = (date_to - date_from).total_seconds() - 1 - build_rnd_time = ( - date_from + timedelta(seconds=randomizer.randint(0, int(sec_range))) - ) - return build_ver, build_rnd_time.strftime('%Y%m%d%H%M%S') - - -def get_chrome_build(): - return randomizer.choice(CHROME_BUILD) - - -def get_ie_build(): - """ - Return random IE version as tuple - (numeric_version, us-string component) - - Example: (8, 'MSIE 8.0') - """ - - return randomizer.choice(IE_VERSION) - - -MACOSX_CHROME_BUILD_RANGE = { - # https://en.wikipedia.org/wiki/MacOS#Release_history - '10.8': (0, 8), - '10.9': (0, 5), - '10.10': (0, 5), - '10.11': (0, 6), - '10.12': (0, 2) -} - - -def fix_chrome_mac_platform(platform): - """ - Chrome on Mac OS adds minor version number and uses underscores instead - of dots. E.g. platform for Firefox will be: 'Intel Mac OS X 10.11' - but for Chrome it will be 'Intel Mac OS X 10_11_6'. - - :param platform: - string like "Macintosh; Intel Mac OS X 10.8" - :return: platform with version number including minor number and formatted - with underscores, e.g. "Macintosh; Intel Mac OS X 10_8_2" - """ - ver = platform.split('OS X ')[1] - build_range = range(*MACOSX_CHROME_BUILD_RANGE[ver]) - build = randomizer.choice(build_range) - mac_ver = ver.replace('.', '_') + '_' + str(build) - return 'Macintosh; Intel Mac OS X %s' % mac_ver - - -def build_system_components(device_type, os_id, navigator_id): - """ - For given os_id build random platform and oscpu - components - - Returns dict {platform_version, platform, ua_platform, oscpu} - - platform_version is OS name used in different places - ua_platform goes to navigator.platform - platform is used in building navigator.userAgent - oscpu goes to navigator.oscpu - """ - - if os_id == 'win': - platform_version = randomizer.choice(OS_PLATFORM['win']) - cpu = randomizer.choice(OS_CPU['win']) - if cpu: - platform = '%s; %s' % (platform_version, cpu) - else: - platform = platform_version - res = { - 'platform_version': platform_version, - 'platform': platform, - 'ua_platform': platform, - 'oscpu': platform, - } - elif os_id == 'linux': - cpu = randomizer.choice(OS_CPU['linux']) - platform_version = randomizer.choice(OS_PLATFORM['linux']) - platform = '%s %s' % (platform_version, cpu) - res = { - 'platform_version': platform_version, - 'platform': platform, - 'ua_platform': platform, - 'oscpu': 'Linux %s' % cpu, - } - elif os_id == 'mac': - cpu = randomizer.choice(OS_CPU['mac']) - platform_version = randomizer.choice(OS_PLATFORM['mac']) - platform = platform_version - if navigator_id == 'chrome': - platform = fix_chrome_mac_platform(platform) - res = { - 'platform_version': platform_version, - 'platform': 'MacIntel', - 'ua_platform': platform, - 'oscpu': 'Intel Mac OS X %s' % platform.split(' ')[-1], - } - elif os_id == 'android': - assert navigator_id in ('firefox', 'chrome') - assert device_type in ('smartphone', 'tablet') - platform_version = randomizer.choice(OS_PLATFORM['android']) - if navigator_id == 'firefox': - if device_type == 'smartphone': - ua_platform = '%s; Mobile' % platform_version - elif device_type == 'tablet': - ua_platform = '%s; Tablet' % platform_version - elif navigator_id == 'chrome': - device_id = randomizer.choice(SMARTPHONE_DEV_IDS) - ua_platform = 'Linux; %s; %s' % (platform_version, device_id) - oscpu = 'Linux %s' % randomizer.choice(OS_CPU['android']) - res = { - 'platform_version': platform_version, - 'ua_platform': ua_platform, - 'platform': oscpu, - 'oscpu': oscpu, - } - return res - - -def build_app_components(os_id, navigator_id): - """ - For given navigator_id build app features - - Returns dict {name, product_sub, vendor, build_version, build_id} - """ - - if navigator_id == 'firefox': - build_version, build_id = get_firefox_build() - if os_id in ('win', 'linux', 'mac'): - geckotrail = '20100101' - else: - geckotrail = build_version - res = { - 'name': 'Netscape', - 'product_sub': '20100101', - 'vendor': '', - 'build_version': build_version, - 'build_id': build_id, - 'geckotrail': geckotrail, - } - elif navigator_id == 'chrome': - res = { - 'name': 'Netscape', - 'product_sub': '20030107', - 'vendor': 'Google Inc.', - 'build_version': get_chrome_build(), - 'build_id': None, - } - elif navigator_id == 'ie': - num_ver, build_version, trident_version = get_ie_build() - if num_ver >= 11: - app_name = 'Netscape' - else: - app_name = 'Microsoft Internet Explorer' - res = { - 'name': app_name, - 'product_sub': None, - 'vendor': '', - 'build_version': build_version, - 'build_id': None, - 'trident_version': trident_version, - } - return res - - -def get_option_choices(opt_name, opt_value, default_value, all_choices): - """ - Generate possible choices for the option `opt_name` - limited to `opt_value` value with default value - as `default_value` - """ - - choices = [] - if isinstance(opt_value, six.string_types): - choices = [opt_value] - elif isinstance(opt_value, (list, tuple)): - choices = list(opt_value) - elif opt_value is None: - choices = default_value - else: - raise InvalidOption('Option %s has invalid' - ' value: %s' % (opt_name, opt_value)) - if 'all' in choices: - choices = all_choices - for item in choices: - if item not in all_choices: - raise InvalidOption('Choices of option %s contains invalid' - ' item: %s' % (opt_name, item)) - return choices - - -def pick_config_ids(device_type, os, navigator): - """ - Select one random pair (device_type, os_id, navigator_id) from - all possible combinations matching the given os and - navigator filters. - - :param os: allowed os(es) - :type os: string or list/tuple or None - :param navigator: allowed browser engine(s) - :type navigator: string or list/tuple or None - :param device_type: limit possible oses by device type - :type device_type: list/tuple or None, possible values: - "desktop", "smartphone", "tablet", "all" - """ - - if os is None: - default_dev_types = ['desktop'] - else: - default_dev_types = list(DEVICE_TYPE_OS.keys()) - dev_type_choices = get_option_choices( - 'device_type', device_type, default_dev_types, - list(DEVICE_TYPE_OS.keys()) - ) - os_choices = get_option_choices('os', os, list(OS_NAVIGATOR.keys()), - list(OS_NAVIGATOR.keys())) - nav_choices = get_option_choices('navigator', navigator, - list(NAVIGATOR_OS.keys()), - list(NAVIGATOR_OS.keys())) - - variants = [] - for dev, os, nav in product(dev_type_choices, os_choices, - nav_choices): - - if (os in DEVICE_TYPE_OS[dev] - and nav in DEVICE_TYPE_NAVIGATOR[dev] - and nav in OS_NAVIGATOR[os]): - variants.append((dev, os, nav)) - if not variants: - raise InvalidOption('Options device_type, os and navigator' - ' conflicts with each other') - device_type, os_id, navigator_id = randomizer.choice(variants) - - assert os_id in OS_PLATFORM - assert navigator_id in NAVIGATOR_OS - assert device_type in DEVICE_TYPE_OS - - return device_type, os_id, navigator_id - - -def choose_ua_template(device_type, navigator_id, app): - tpl_name = navigator_id - if navigator_id == 'ie': - tpl_name = ('ie_11' if app['build_version'] == 'MSIE 11.0' - else 'ie_less_11') - if navigator_id == 'chrome': - if device_type == 'smartphone': - tpl_name = 'chrome_smartphone' - if device_type == 'tablet': - tpl_name = 'chrome_tablet' - return USER_AGENT_TEMPLATE[tpl_name] - - -def build_navigator_app_version(os_id, navigator_id, - platform_version, user_agent): - if navigator_id in ('chrome', 'ie'): - assert user_agent.startswith('Mozilla/') - app_version = user_agent.split('Mozilla/', 1)[1] - elif navigator_id == 'firefox': - if os_id == 'android': - app_version = '5.0 (%s)' % platform_version - else: - os_token = { - 'win': 'Windows', - 'mac': 'Macintosh', - 'linux': 'X11', - }[os_id] - app_version = '5.0 (%s)' % os_token - return app_version - - -def generate_navigator(os=None, navigator=None, platform=None, - device_type=None): - """ - Generates web navigator's config - - :param os: limit list of oses for generation - :type os: string or list/tuple or None - :param navigator: limit list of browser engines for generation - :type navigator: string or list/tuple or None - :param device_type: limit possible oses by device type - :type device_type: list/tuple or None, possible values: - "desktop", "smartphone", "tablet", "all" - - :return: User-Agent config - :rtype: dict with keys (os, name, platform, oscpu, build_version, - build_id, app_version, app_name, app_code_name, - product, product_sub, vendor, vendor_sub, - user_agent) - :raises InvalidOption: if could not generate user-agent for - any combination of allowed platforms and navigators - :raise InvalidOption: if any of passed options is invalid - """ - - if platform is not None: - os = platform - warn('The `platform` option is deprecated.' - ' Use `os` option instead.', stacklevel=3) - device_type, os_id, navigator_id = ( - pick_config_ids(device_type, os, navigator) - ) - system = build_system_components( - device_type, os_id, navigator_id) - app = build_app_components(os_id, navigator_id) - ua_template = choose_ua_template( - device_type, navigator_id, app) - user_agent = ua_template.format(system=system, app=app) - app_version = build_navigator_app_version( - os_id, navigator_id, system['platform_version'], user_agent) - return { - # ids - 'os_id': os_id, - 'navigator_id': navigator_id, - # system components - 'platform': system['platform'], - 'oscpu': system['oscpu'], - # app components - 'build_version': app['build_version'], - 'build_id': app['build_id'], - 'app_version': app_version, - 'app_name': app['name'], - 'app_code_name': 'Mozilla', - 'product': 'Gecko', - 'product_sub': app['product_sub'], - 'vendor': app['vendor'], - 'vendor_sub': '', - # compiled user agent - 'user_agent': user_agent, - } - - -def generate_user_agent(os=None, navigator=None, platform=None, - device_type=None): - """ - Generates HTTP User-Agent header - - :param os: limit list of os for generation - :type os: string or list/tuple or None - :param navigator: limit list of browser engines for generation - :type navigator: string or list/tuple or None - :param device_type: limit possible oses by device type - :type device_type: list/tuple or None, possible values: - "desktop", "smartphone", "tablet", "all" - :return: User-Agent string - :rtype: string - :raises InvalidOption: if could not generate user-agent for - any combination of allowed oses and navigators - :raise InvalidOption: if any of passed options is invalid - """ - return generate_navigator(os=os, navigator=navigator, - platform=platform, - device_type=device_type)['user_agent'] - - -def generate_navigator_js(os=None, navigator=None, platform=None, - device_type=None): - """ - Generates web navigator's config with keys corresponding - to keys of `windows.navigator` JavaScript object. - - :param os: limit list of oses for generation - :type os: string or list/tuple or None - :param navigator: limit list of browser engines for generation - :type navigator: string or list/tuple or None - :param device_type: limit possible oses by device type - :type device_type: list/tuple or None, possible values: - "desktop", "smartphone", "tablet", "all" - :return: User-Agent config - :rtype: dict with keys (TODO) - :raises InvalidOption: if could not generate user-agent for - any combination of allowed oses and navigators - :raise InvalidOption: if any of passed options is invalid - """ - - config = generate_navigator(os=os, navigator=navigator, - platform=platform, - device_type=device_type) - return { - 'appCodeName': config['app_code_name'], - 'appName': config['app_name'], - 'appVersion': config['app_version'], - 'platform': config['platform'], - 'userAgent': config['user_agent'], - 'oscpu': config['oscpu'], - 'product': config['product'], - 'productSub': config['product_sub'], - 'vendor': config['vendor'], - 'vendorSub': config['vendor_sub'], - 'buildID': config['build_id'], - } diff --git a/build/pyinstaller/user_agent/cli.py b/build/pyinstaller/user_agent/cli.py deleted file mode 100644 index c9083ba0d93..00000000000 --- a/build/pyinstaller/user_agent/cli.py +++ /dev/null @@ -1,21 +0,0 @@ -from argparse import ArgumentParser -import json - -from user_agent import generate_navigator_js - - -def script_ua(): - parser = ArgumentParser() - parser.add_argument('-e', '--extended', action='store_true', - default=False) - parser.add_argument('-o', '--os') - parser.add_argument('-n', '--navigator') - parser.add_argument('-d', '--device-type') - opts = parser.parse_args() - nav = generate_navigator_js(os=opts.os, - navigator=opts.navigator, - device_type=opts.device_type) - if opts.extended: - print(json.dumps(nav, indent=2)) - else: - print(nav['userAgent']) diff --git a/build/pyinstaller/user_agent/data/smartphone_dev_ext.json b/build/pyinstaller/user_agent/data/smartphone_dev_ext.json deleted file mode 100644 index cb7da6534e5..00000000000 --- a/build/pyinstaller/user_agent/data/smartphone_dev_ext.json +++ /dev/null @@ -1,2820 +0,0 @@ -[ - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Quad-core 1.2 or 1.4 GHz Cortex-A7", - "dev_ids": [ - "GT-I9300 Build/JRO03C" - ], - "name": "Samsung I9300I Galaxy S3 Neo", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.2.2", - "v4.2.2" - ], - "cpu": "Octa-core 1.4 GHz Cortex-A7", - "dev_ids": [ - "HTC Desire 616 dual sim Build/JDQ39" - ], - "name": "HTC Desire 616 dual sim", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.2.2", - "v4.2.2" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Lenovo A526 Build/JDQ39" - ], - "name": "Lenovo A526", - "released": 2014, - "resolution": [ - 480, - 854 - ] - }, - { - "android_versionss": [ - "v4.3", - "v4.3" - ], - "cpu": "Quad-core 1.2 GHz", - "dev_ids": [ - "7050Y Build/JLS36C" - ], - "name": "alcatel Pop S9", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.2.2", - "v4.2.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "HTC Desire 516 dual sim Build/JWR66Y" - ], - "name": "HTC Desire 516 dual sim", - "released": 2014, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v4.3", - "v4.3" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "Lenovo S580 Build/JLS36C" - ], - "name": "Lenovo S580", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.2.1", - "v4.4.4" - ], - "cpu": "Octa-core 2.0 GHz Cortex-A7", - "dev_ids": [ - "6043D Build/KOT49H" - ], - "name": "alcatel Idol X+", - "released": 2014, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "D2212 Build/18.4.B.1.20" - ], - "name": "Sony Xperia E3 Dual", - "released": 2014, - "resolution": [ - 480, - 854 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "GSmart Mika M3 Build/GSmart" - ], - "name": "Gigabyte GSmart Mika M3", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.3", - "v4.3" - ], - "cpu": "Dual-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "NokiaX2DS Build/JLS36C" - ], - "name": "Nokia X2 Dual SIM", - "released": 2014, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Octa-core 1.7 GHz - 526G+ modelQuad-core 1.3 GHz - 526G model", - "dev_ids": [ - "HTC Desire 526G dual sim Build/KOT49H" - ], - "name": "HTC Desire 526G+ dual sim", - "released": 2015, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.2 GHz", - "dev_ids": [ - "HTC Desire 326G dual sim Build/KOT49H" - ], - "name": "HTC Desire 326G dual sim", - "released": 2015, - "resolution": [ - 480, - 854 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "HTC Desire 610 Build/KOT49H" - ], - "name": "HTC Desire 610", - "released": 2014, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Octa-core 1.7 GHz Cortex-A7", - "dev_ids": [ - "HTC Desire 620G dual sim Build/KOT49H" - ], - "name": "HTC Desire 620G dual sim", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Lenovo A328 Build/KOT49H" - ], - "name": "Lenovo A328", - "released": 2014, - "resolution": [ - 480, - 854 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Lenovo A606 Build/KOT49H" - ], - "name": "Lenovo A606", - "released": 2014, - "resolution": [ - 480, - 854 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Lenovo A536 Build/KOT49H" - ], - "name": "Lenovo A536", - "released": 2014, - "resolution": [ - 480, - 854 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v6.0" - ], - "cpu": "Quad-core 2.5 GHz Krait 400", - "dev_ids": [ - "LGLS990 Build/KVT49L.LS990ZV4" - ], - "name": "LG G3 (CDMA)", - "released": 2014, - "resolution": [ - 1440, - 2560 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Dual-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Micromax D303 Build/KOT49H" - ], - "name": "Micromax Bolt D303", - "released": 2015, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Dual-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "Micromax D320 Build/KOT49H" - ], - "name": "Micromax Bolt D320", - "released": 2015, - "resolution": [ - 480, - 854 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Hexa-core (4x1.3 GHz Cortex A7 & 2x1.7 GHz Cortex A15)", - "dev_ids": [ - "SM-C111 Build/KOT49H" - ], - "name": "Samsung Galaxy K zoom", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Octa-core 1.7 GHz", - "dev_ids": [ - "Philips I908 Build/KOT49H" - ], - "name": "Philips I908", - "released": 2015, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Octa-core (4x1.7 GHz Cortex-A15 & 4x1.3 GHz Cortex-A7)", - "dev_ids": [ - "H60-L04 Build/HDH60-L04" - ], - "name": "Huawei Honor 6", - "released": 2014, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.6 GHz Cortex-A7", - "dev_ids": [ - "ZTE Star 1 Build/KVT49L" - ], - "name": "ZTE Star 1", - "released": 2014, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Quad-core 1.5 GHz Cortex-A53", - "dev_ids": [ - "E2033 Build/25.0.B.2.31" - ], - "name": "Sony Xperia E4g Dual", - "released": 2015, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v6.0", - "v6.0" - ], - "cpu": "Quad-core 1.4 GHz Cortex-A53", - "dev_ids": [ - "ZTE Blade A5 Build/KOT49H" - ], - "name": "ZTE Blade A512", - "released": 2016, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Octa-core 1.7 GHz Cortex-A7", - "dev_ids": [ - "Lenovo A806 Build/KOT49H" - ], - "name": "Lenovo Golden Warrior A8", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53", - "dev_ids": [ - "Lenovo K30-T Build/KTU84Q" - ], - "name": "Lenovo K3", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Dual-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "SM-J100FN Build/KTU84P" - ], - "name": "Samsung Galaxy J1", - "released": 2015, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Dual-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "SM-J100H Build/KTU84P" - ], - "name": "Samsung Galaxy J1", - "released": 2015, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "E2115 Build/24.0.B.5.14" - ], - "name": "Sony Xperia E4 Dual", - "released": 2015, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v5.1.1" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53", - "dev_ids": [ - "SM-G360H Build/KTU84P" - ], - "name": "Samsung Galaxy Core Prime", - "released": 2014, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Octa-core 1.7 GHz Cortex-A53", - "dev_ids": [ - "m1 note Build/KTU84P" - ], - "name": "Meizu M1 Note", - "released": 2015, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v5.1.1" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53", - "dev_ids": [ - "SM-G360F Build/KTU84P" - ], - "name": "Samsung Galaxy Core Prime", - "released": 2014, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Dual-core 1.2 GHz", - "dev_ids": [ - "SM-G318H Build/KTU84P" - ], - "name": "Samsung Galaxy V Plus", - "released": 2015, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.2", - "v4.2" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Lenovo S850 Build/KOT49H" - ], - "name": "Lenovo S850", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v6.0.1" - ], - "cpu": "Quad-core 2.5 GHz Krait 450", - "dev_ids": [ - "SAMSUNG SM-G906S Build/LRX22C" - ], - "name": "Samsung Galaxy S5 LTE-A G906S", - "released": 2014, - "resolution": [ - 1440, - 2560 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v5.0.2" - ], - "cpu": "Quad-core 2.5 GHz Krait 400", - "dev_ids": [ - "Lenovo K920 Build/LRX22G" - ], - "name": "Lenovo Vibe Z2 Pro", - "released": 2014, - "resolution": [ - 1440, - 2560 - ] - }, - { - "android_versionss": [ - "v5.0", - "v5.0" - ], - "cpu": "Octa-core (4x1.5 GHz Cortex-A53 & 4x1.0 GHz Cortex-A53)", - "dev_ids": [ - "Lenovo PB1-770M Build/S100" - ], - "name": "Lenovo Phab Plus", - "released": 2015, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v5.0.2", - "v5.0.2" - ], - "cpu": "Octa-core (4x1.7 GHz Cortex-A53 & 4x1.0 GHz Cortex-A53)", - "dev_ids": [ - "Mi 4i Build/LRX22G" - ], - "name": "Xiaomi Mi 4i", - "released": 2015, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v5.0", - "v5.0" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Micromax Q380 Build/LRX22G" - ], - "name": "Micromax Canvas Spark Q380", - "released": 2015, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Octa-core (4x1.5 GHz Cortex-A53 & 4x1.0 GHz Cortex-A53)", - "dev_ids": [ - "SM-A700H Build/LRX22G" - ], - "name": "Samsung Galaxy A7 Duos", - "released": 2015, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v5.0.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53Quad-core 1.3 GHz Cortex-A7 (Value Edition)", - "dev_ids": [ - "SM-G530FZ Build/LRX22G" - ], - "name": "Samsung Galaxy Grand Prime", - "released": 2014, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v5.0", - "v5.0" - ], - "cpu": "Octa-core 2.0 GHz Cortex-A53 - Redmi Note 2Octa-core 2.2 GHz Cortex-A53 - Redmi Note 2 Prime", - "dev_ids": [ - "Redmi Note 2 Build/LRX22G" - ], - "name": "Xiaomi Redmi Note 2", - "released": 2015, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53", - "dev_ids": [ - "SM-A500FU Build/LRX22G" - ], - "name": "Samsung Galaxy A5", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53", - "dev_ids": [ - "RIDGE 4G Build/LRX22G" - ], - "name": "Wiko Ridge 4G", - "released": 2015, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v5.0.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53Quad-core 1.3 GHz Cortex-A7 (Value Edition)", - "dev_ids": [ - "SM-G530H Build/LRX22G" - ], - "name": "Samsung Galaxy Grand Prime", - "released": 2014, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v5.0.2" - ], - "cpu": "Octa-core (4x1.8 GHz Cortex-A15 & 4x1.3 GHz Cortex-A7)", - "dev_ids": [ - "SM-G850F Build/LRX22G" - ], - "name": "Samsung Galaxy Alpha", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v6.0" - ], - "cpu": "Quad-core 2.5 GHz Krait 400", - "dev_ids": [ - "SM-G900I Build/LRX21T" - ], - "name": "Samsung Galaxy S5", - "released": 2014, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v5.0.2", - "v6.0" - ], - "cpu": "Octa-core 1.7 GHz Cortex-A53", - "dev_ids": [ - "Lenovo K50-t5 Build/LRX21M" - ], - "name": "Lenovo K3 Note", - "released": 2015, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v6.0.1" - ], - "cpu": "Octa-core (4x1.9 GHz Cortex-A15 & 4x1.3 GHz Cortex-A7)", - "dev_ids": [ - "SM-G900H Build/LRX21T" - ], - "name": "Samsung Galaxy S5 (octa-core)", - "released": 2014, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v4.3", - "v5.1" - ], - "cpu": "Quad-core 2.2 GHz Krait 400", - "dev_ids": [ - "D5503 Build/14.6.A.1.236" - ], - "name": "Sony Xperia Z1 Compact", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v5.1", - "v5.1" - ], - "cpu": "Octa-core (4x1.6 GHz Cortex-A53 & 4x1.2 GHz Cortex-A53)", - "dev_ids": [ - "Lenovo P1a42 Build/LMY47V" - ], - "name": "Lenovo Vibe P1 Turbo", - "released": 2016, - "resolution": [ - 1080, - 1920 - ] - }, - { - "android_versionss": [ - "v5.0.1", - "v5.0.1" - ], - "cpu": "Octa-core (4x1.5 GHz Cortex-A53 & 4x2.0 GHz Cortex-A57)", - "dev_ids": [ - "MI NOTE Pro Build/LMY47V" - ], - "name": "Xiaomi Mi Note Pro", - "released": 2015, - "resolution": [ - 1440, - 2560 - ] - }, - { - "android_versionss": [ - "v5.0", - "v5.0" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "Micromax AQ5001 Build/LRX21M" - ], - "name": "Micromax Canvas Juice 2 AQ5001", - "released": 2015, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.4 GHz Cortex-A7", - "dev_ids": [ - "SM-G800F Build/LMY47X" - ], - "name": "Samsung Galaxy S5 mini", - "released": 2014, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v5.1.1", - "v5.1.1" - ], - "cpu": "Quad-core 1.3 GHz Cortex-A7", - "dev_ids": [ - "SM-J120F Build/LMY47X" - ], - "name": "Samsung Galaxy J1 (2016)", - "released": 2016, - "resolution": [ - 480, - 800 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v4.4.4" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53", - "dev_ids": [ - "SM-E500F Build/LMY47X" - ], - "name": "Samsung Galaxy E5", - "released": 2015, - "resolution": [ - 720, - 1280 - ] - }, - { - "android_versionss": [ - "v4.4.4", - "v5.0.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A53Quad-core 1.3 GHz Cortex-A7 (Value Edition)", - "dev_ids": [ - "SM-G531F Build/LMY48B" - ], - "name": "Samsung Galaxy Grand Prime", - "released": 2014, - "resolution": [ - 540, - 960 - ] - }, - { - "android_versionss": [ - "v5.1.1", - "v6.0.1" - ], - "cpu": "Octa-core (4x1.2 GHz Cortex-A53 & 4x1.5 GHz Cortex-A53)Octa-core 1.6 GHz Cortex-A53", - "dev_ids": [ - "SM-A510F Build/LMY47X" - ], - "name": 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"v4.4.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.2 GHz Cortex-A7", - "dev_ids": [ - "SM-T365 Build/LMY47X" - ], - "name": "Samsung Galaxy Tab Active LTE", - "released": 2014, - "resolution": [ - 800, - 1280 - ] - }, - { - "android_versionss": [ - "v5.0", - "v5.0" - ], - "cpu": "Octa-core (4x1.5 GHz Cortex-A53 & 4x2.0 GHz Cortex-A57)", - "dev_ids": [ - "SGP771 Build/28.0.A.8.260" - ], - "name": "Sony Xperia Z4 Tablet LTE", - "released": 2015, - "resolution": [ - 2560, - 1600 - ] - }, - { - "android_versionss": [ - "v5.0.2", - "v6.0.1" - ], - "cpu": "Octa-core (4x1.9 GHz & 4x1.3 GHz) - T710, T715Octa-core (4x1.8 GHz Cortex-A72 & 4x1.4 GHz Cortex-A53) - T719N", - "dev_ids": [ - "SM-T715 Build/MMB29K" - ], - "name": "Samsung Galaxy Tab S2 8.0", - "released": 2015, - "resolution": [ - 1536, - 2048 - ] - }, - { - "android_versionss": [ - "v4.2.2", - "v4.4.2" - ], - "cpu": "Quad-core 1.6 GHz Cortex-A9", - "dev_ids": [ - "X1 7.0 Build/HuaweiMediaPad" - ], - "name": "Huawei MediaPad X1", - "released": 2014, - "resolution": [ - 1200, - 1920 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v6.0" - ], - "cpu": "Quad-core 2.3 GHz Krait 400 (S800)Quad-core 1.9GHz Cortex-A15 & quad-core 1.3 GHz Cortex-A7 (Exynos 5420)", - "dev_ids": [ - "SAMSUNG SM-T805 Build/LRX22G" - ], - "name": "Samsung Galaxy Tab S 10.5 LTE", - "released": 2014, - "resolution": [ - 2560, - 1600 - ] - }, - { - "android_versionss": [ - "v4.4.2", - "v6.0" - ], - "cpu": "Octa-core (4x1.9 GHz Cortex-A15 & 4x1.3 GHz Cortex-A7)", - "dev_ids": [ - "SM-T700 Build/LRX22G" - ], - "name": "Samsung Galaxy Tab S 8.4", - "released": 2014, - "resolution": [ - 1600, - 2560 - ] - } -] \ No newline at end of file diff --git a/build/pyinstaller/user_agent/data/tablet_dev_id.json b/build/pyinstaller/user_agent/data/tablet_dev_id.json deleted file mode 100644 index 5ab83ea01cb..00000000000 --- a/build/pyinstaller/user_agent/data/tablet_dev_id.json +++ /dev/null @@ -1,52 +0,0 @@ -[ - "A1-713HD Build/KOT49H", - "A3-A30 Build/LRX22G", - "Archos 80 Helium 4G Build/JLS36C", - "BTV-DL09 Build/HUAWEIBEETHOVEN-DL09", - "FDR-A01L Build/HuaweiMediaPad", - "HUAWEI M2-A01L Build/HUAWEIM2-A01L", - "Lenovo A3500-H Build/KOT49H", - "Lenovo A3500-HV Build/KOT49H", - "Lenovo A5500-F Build/KOT49H", - "Lenovo A5500-H Build/KOT49H", - "Lenovo A7600-H Build/KOT49H", - "Lenovo TAB 2 A10-70L Build/KTU84P", - "Lenovo TAB 2 A8-50LC Build/LMY47D", - "Lenovo TAB 2 A8-50LC Build/LRX22G", - "MediaPad T1 8.0 Build/HuaweiMediaPad", - "Nexus 9 Build/MOB30M", - "Nexus 9 Build/NRD91N", - "SAMSUNG SM-T805 Build/LRX22G", - "SAMSUNG SM-T815Y Build/MMB29K", - "SGP771 Build/28.0.A.8.260", - "SM-P901 Build/KOT49H", - "SM-T110 Build/JDQ39", - "SM-T113 Build/KTU84P", - "SM-T116 Build/KTU84P", - "SM-T116BU Build/KTU84P", - "SM-T230 Build/KOT49H", - "SM-T231 Build/KOT49H", - "SM-T235 Build/LMY47X", - "SM-T325 Build/KOT49H", - "SM-T331 Build/LMY47X", - "SM-T365 Build/LMY47X", - "SM-T525 Build/KOT49H", - "SM-T530 Build/KOT49H", - "SM-T530 Build/LRX22G", - "SM-T531 Build/KOT49H", - "SM-T535 Build/KOT49H", - "SM-T555 Build/LRX22G", - "SM-T560 Build/KTU84P", - "SM-T561 Build/KTU84P", - "SM-T700 Build/LRX22G", - "SM-T705 Build/LRX22G", - "SM-T710 Build/LRX22G", - "SM-T715 Build/MMB29K", - "SM-T719 Build/MMB29M", - "SM-T800 Build/MMB29K", - "SM-T805 Build/KOT49H", - "SM-T813 Build/MMB29M", - "T1-701u Build/HuaweiMediaPad", - "X1 7.0 Build/HuaweiMediaPad", - "YOGA Tablet 2 Pro-1380F Build/LRX22C" -] \ No newline at end of file diff --git a/build/pyinstaller/user_agent/device.py b/build/pyinstaller/user_agent/device.py deleted file mode 100644 index 30a99bb2021..00000000000 --- a/build/pyinstaller/user_agent/device.py +++ /dev/null @@ -1,15 +0,0 @@ -import os.path -import json - - -PACKAGE_DIR = os.path.dirname(os.path.realpath(__file__)) - - -def load_json_data(rel_path): - path = os.path.join(PACKAGE_DIR, rel_path) - with open(path, encoding='utf-8') as inp: - return json.load(inp) - - -SMARTPHONE_DEV_IDS = load_json_data('data/smartphone_dev_id.json') -TABLET_DEV_IDS = load_json_data('data/tablet_dev_id.json') diff --git a/build/pyinstaller/user_agent/error.py b/build/pyinstaller/user_agent/error.py deleted file mode 100644 index 73f2e19e18c..00000000000 --- a/build/pyinstaller/user_agent/error.py +++ /dev/null @@ -1,15 +0,0 @@ -__all__ = ('UserAgentError', 'InvalidOption') - - -class UserAgentError(Exception): - """ - Base class for all errors - raising from the user_agent library - """ - - -class InvalidOption(Exception): - """ - Raises when user call user_agent library methods - with incorrect arguments. - """ diff --git a/build/pyinstaller/user_agent/warning.py b/build/pyinstaller/user_agent/warning.py deleted file mode 100644 index 2980b8428d4..00000000000 --- a/build/pyinstaller/user_agent/warning.py +++ /dev/null @@ -1,13 +0,0 @@ -import warnings - - -class UserAgentDeprecationWarning(UserWarning): - """ - Warning category used to generate warning message - about deprecated feature of user_agent library. - """ - - -def warn(msg, stacklevel=2): - warnings.warn(msg, category=UserAgentDeprecationWarning, - stacklevel=stacklevel) diff --git a/build/pyinstaller/vaderSentiment/__init__.py b/build/pyinstaller/vaderSentiment/__init__.py deleted file mode 100644 index 693737ff390..00000000000 --- a/build/pyinstaller/vaderSentiment/__init__.py +++ /dev/null @@ -1 +0,0 @@ -#!/usr/bin/python \ No newline at end of file diff --git a/build/pyinstaller/vaderSentiment/emoji_utf8_lexicon.txt b/build/pyinstaller/vaderSentiment/emoji_utf8_lexicon.txt deleted file mode 100644 index 5e1a91b2b95..00000000000 --- a/build/pyinstaller/vaderSentiment/emoji_utf8_lexicon.txt +++ /dev/null @@ -1,3570 +0,0 @@ -😀 grinning face -😁 beaming face with smiling eyes -😂 face with tears of joy -🤣 rolling on the floor laughing -😃 grinning face with big eyes -😄 grinning face with smiling eyes -😅 grinning face with sweat -😆 grinning squinting face -😉 winking face -😊 smiling face with smiling eyes -😋 face savoring food -😎 smiling face with sunglasses -😍 smiling face with heart-eyes -😘 face blowing a kiss -🥰 smiling face with 3 hearts -😗 kissing face -😙 kissing face with smiling eyes -😚 kissing face with closed eyes -☺️ smiling face -☺ smiling face -🙂 slightly smiling face -🤗 hugging face -🤩 star-struck -🤔 thinking face -🤨 face with raised eyebrow -😐 neutral face -😑 expressionless face -😶 face without mouth -🙄 face with rolling eyes -😏 smirking face -😣 persevering face -😥 sad but relieved face -😮 face with open mouth -🤐 zipper-mouth face -😯 hushed face -😪 sleepy face -😫 tired face -😴 sleeping face -😌 relieved face -😛 face with tongue -😜 winking face with tongue -😝 squinting face with tongue -🤤 drooling face -😒 unamused face -😓 downcast face with sweat -😔 pensive face -😕 confused face -🙃 upside-down face -🤑 money-mouth face -😲 astonished face -☹️ frowning face -☹ frowning face -🙁 slightly frowning face -😖 confounded face -😞 disappointed face -😟 worried face -😤 face with steam from nose -😢 crying face -😭 loudly crying face -😦 frowning face with open mouth -😧 anguished face -😨 fearful face -😩 weary face -🤯 exploding head -😬 grimacing face -😰 anxious face with sweat -😱 face screaming in fear -🥵 hot face -🥶 cold face -😳 flushed face -🤪 zany face -😵 dizzy face -😡 pouting face -😠 angry face -🤬 face with symbols on mouth -😷 face with medical mask -🤒 face with thermometer -🤕 face with head-bandage -🤢 nauseated face -🤮 face vomiting -🤧 sneezing face -😇 smiling face with halo -🤠 cowboy hat face -🥳 partying face -🥴 woozy face -🥺 pleading face -🤥 lying face -🤫 shushing face -🤭 face with hand over mouth -🧐 face with monocle -🤓 nerd face -😈 smiling face with horns -👿 angry face with horns -🤡 clown face -👹 ogre -👺 goblin -💀 skull -☠️ skull and crossbones -☠ skull and crossbones -👻 ghost -👽 alien -👾 alien monster -🤖 robot face -💩 pile of poo -😺 grinning cat face -😸 grinning cat face with smiling eyes -😹 cat face with tears of joy -😻 smiling cat face with heart-eyes -😼 cat face with wry smile -😽 kissing cat face -🙀 weary cat face -😿 crying cat face -😾 pouting cat face -🙈 see-no-evil monkey -🙉 hear-no-evil monkey -🙊 speak-no-evil monkey -🏻 light skin tone -🏼 medium-light skin tone -🏽 medium skin tone -🏾 medium-dark skin tone -🏿 dark skin tone -👶 baby -👶🏻 baby: light skin tone -👶🏼 baby: medium-light skin tone -👶🏽 baby: medium skin tone -👶🏾 baby: medium-dark skin tone -👶🏿 baby: dark skin tone -🧒 child -🧒🏻 child: light skin tone -🧒🏼 child: medium-light skin tone -🧒🏽 child: medium skin tone -🧒🏾 child: medium-dark skin tone -🧒🏿 child: dark skin tone -👦 boy -👦🏻 boy: light skin tone -👦🏼 boy: medium-light skin tone -👦🏽 boy: medium skin tone -👦🏾 boy: medium-dark skin tone -👦🏿 boy: dark skin tone -👧 girl -👧🏻 girl: light skin tone -👧🏼 girl: medium-light skin tone -👧🏽 girl: medium skin tone -👧🏾 girl: medium-dark skin tone -👧🏿 girl: dark skin tone -🧑 adult -🧑🏻 adult: light skin tone -🧑🏼 adult: medium-light skin tone -🧑🏽 adult: medium skin tone -🧑🏾 adult: medium-dark skin tone -🧑🏿 adult: dark skin tone -👨 man -👨🏻 man: light skin tone -👨🏼 man: medium-light skin tone -👨🏽 man: medium skin tone -👨🏾 man: medium-dark skin tone -👨🏿 man: dark skin tone -👩 woman -👩🏻 woman: light skin tone -👩🏼 woman: medium-light skin tone -👩🏽 woman: medium skin tone -👩🏾 woman: medium-dark skin tone -👩🏿 woman: dark skin tone -🧓 older adult -🧓🏻 older adult: light skin tone -🧓🏼 older adult: medium-light skin tone -🧓🏽 older adult: medium skin tone -🧓🏾 older adult: medium-dark skin tone -🧓🏿 older adult: dark skin tone -👴 old man -👴🏻 old man: light skin tone -👴🏼 old man: medium-light skin tone -👴🏽 old man: medium skin tone -👴🏾 old man: medium-dark skin tone -👴🏿 old man: dark skin tone -👵 old woman -👵🏻 old woman: light skin tone -👵🏼 old woman: medium-light skin tone -👵🏽 old woman: medium skin tone -👵🏾 old woman: medium-dark skin tone -👵🏿 old woman: dark skin tone -👨‍⚕️ man health worker -👨‍⚕ man health worker -👨🏻‍⚕️ man health worker: light skin tone -👨🏻‍⚕ man health worker: light skin tone -👨🏼‍⚕️ man health worker: medium-light skin tone -👨🏼‍⚕ man health worker: medium-light skin tone -👨🏽‍⚕️ man health worker: medium skin tone -👨🏽‍⚕ man health worker: medium skin tone -👨🏾‍⚕️ man health worker: medium-dark skin tone -👨🏾‍⚕ man health worker: medium-dark skin tone -👨🏿‍⚕️ man health worker: dark skin tone -👨🏿‍⚕ man health worker: dark skin tone -👩‍⚕️ woman health worker -👩‍⚕ woman health worker -👩🏻‍⚕️ woman health worker: light skin tone -👩🏻‍⚕ woman health worker: light skin tone -👩🏼‍⚕️ woman health worker: medium-light skin tone -👩🏼‍⚕ woman health worker: medium-light skin tone -👩🏽‍⚕️ woman health worker: medium skin tone -👩🏽‍⚕ woman health worker: medium skin tone -👩🏾‍⚕️ woman health worker: medium-dark skin tone -👩🏾‍⚕ woman health worker: medium-dark skin tone -👩🏿‍⚕️ woman health worker: dark skin tone -👩🏿‍⚕ woman health worker: dark skin tone -👨‍🎓 man student -👨🏻‍🎓 man student: light skin tone -👨🏼‍🎓 man student: medium-light skin tone -👨🏽‍🎓 man student: medium skin tone -👨🏾‍🎓 man student: medium-dark skin tone -👨🏿‍🎓 man student: dark skin tone -👩‍🎓 woman student -👩🏻‍🎓 woman student: light skin tone -👩🏼‍🎓 woman student: medium-light skin tone -👩🏽‍🎓 woman student: medium skin tone -👩🏾‍🎓 woman student: medium-dark skin tone -👩🏿‍🎓 woman student: dark skin tone -👨‍🏫 man teacher -👨🏻‍🏫 man teacher: light skin tone -👨🏼‍🏫 man teacher: medium-light skin tone -👨🏽‍🏫 man teacher: medium skin tone -👨🏾‍🏫 man teacher: medium-dark skin tone -👨🏿‍🏫 man teacher: dark skin tone -👩‍🏫 woman teacher -👩🏻‍🏫 woman teacher: light skin tone -👩🏼‍🏫 woman teacher: medium-light skin tone -👩🏽‍🏫 woman teacher: medium skin tone -👩🏾‍🏫 woman teacher: medium-dark skin tone -👩🏿‍🏫 woman teacher: dark skin tone -👨‍⚖️ man judge -👨‍⚖ man judge -👨🏻‍⚖️ man judge: light skin tone -👨🏻‍⚖ man judge: light skin tone -👨🏼‍⚖️ man judge: medium-light skin tone -👨🏼‍⚖ man judge: medium-light skin tone -👨🏽‍⚖️ man judge: medium skin tone -👨🏽‍⚖ man judge: medium skin tone -👨🏾‍⚖️ man judge: medium-dark skin tone -👨🏾‍⚖ man judge: medium-dark skin tone -👨🏿‍⚖️ man judge: dark skin tone -👨🏿‍⚖ man judge: dark skin tone -👩‍⚖️ woman judge -👩‍⚖ woman judge -👩🏻‍⚖️ woman judge: light skin tone -👩🏻‍⚖ woman judge: light skin tone -👩🏼‍⚖️ woman judge: medium-light skin tone -👩🏼‍⚖ woman judge: medium-light skin tone -👩🏽‍⚖️ woman judge: medium skin tone -👩🏽‍⚖ woman judge: medium skin tone -👩🏾‍⚖️ woman judge: medium-dark skin tone -👩🏾‍⚖ woman judge: medium-dark skin tone -👩🏿‍⚖️ woman judge: dark skin tone -👩🏿‍⚖ woman judge: dark skin tone -👨‍🌾 man farmer -👨🏻‍🌾 man farmer: light skin tone -👨🏼‍🌾 man farmer: medium-light skin tone -👨🏽‍🌾 man farmer: medium skin tone -👨🏾‍🌾 man farmer: medium-dark skin tone -👨🏿‍🌾 man farmer: dark skin tone -👩‍🌾 woman farmer -👩🏻‍🌾 woman farmer: light skin tone -👩🏼‍🌾 woman farmer: medium-light skin tone -👩🏽‍🌾 woman farmer: medium skin tone -👩🏾‍🌾 woman farmer: medium-dark skin tone -👩🏿‍🌾 woman farmer: dark skin tone -👨‍🍳 man cook -👨🏻‍🍳 man cook: light skin tone -👨🏼‍🍳 man cook: medium-light skin tone -👨🏽‍🍳 man cook: medium skin tone -👨🏾‍🍳 man cook: medium-dark skin tone -👨🏿‍🍳 man cook: dark skin tone -👩‍🍳 woman cook -👩🏻‍🍳 woman cook: light skin tone -👩🏼‍🍳 woman cook: medium-light skin tone -👩🏽‍🍳 woman cook: medium skin tone -👩🏾‍🍳 woman cook: medium-dark skin tone -👩🏿‍🍳 woman cook: dark skin tone -👨‍🔧 man mechanic -👨🏻‍🔧 man mechanic: light skin tone -👨🏼‍🔧 man mechanic: medium-light skin tone -👨🏽‍🔧 man mechanic: medium skin tone -👨🏾‍🔧 man mechanic: medium-dark skin tone -👨🏿‍🔧 man mechanic: dark skin tone -👩‍🔧 woman mechanic -👩🏻‍🔧 woman mechanic: light skin tone -👩🏼‍🔧 woman mechanic: medium-light skin tone -👩🏽‍🔧 woman mechanic: medium skin tone -👩🏾‍🔧 woman mechanic: medium-dark skin tone -👩🏿‍🔧 woman mechanic: dark skin tone -👨‍🏭 man factory worker -👨🏻‍🏭 man factory worker: light skin tone -👨🏼‍🏭 man factory worker: medium-light skin tone -👨🏽‍🏭 man factory worker: medium skin tone -👨🏾‍🏭 man factory worker: medium-dark skin tone -👨🏿‍🏭 man factory worker: dark skin tone -👩‍🏭 woman factory worker -👩🏻‍🏭 woman factory worker: light skin tone -👩🏼‍🏭 woman factory worker: medium-light skin tone -👩🏽‍🏭 woman factory worker: medium skin tone -👩🏾‍🏭 woman factory worker: medium-dark skin tone -👩🏿‍🏭 woman factory worker: dark skin tone -👨‍💼 man office worker -👨🏻‍💼 man office worker: light skin tone -👨🏼‍💼 man office worker: medium-light skin tone -👨🏽‍💼 man office worker: medium skin tone -👨🏾‍💼 man office worker: medium-dark skin tone -👨🏿‍💼 man office worker: dark skin tone -👩‍💼 woman office worker -👩🏻‍💼 woman office worker: light skin tone -👩🏼‍💼 woman office worker: medium-light skin tone -👩🏽‍💼 woman office worker: medium skin tone -👩🏾‍💼 woman office worker: medium-dark skin tone -👩🏿‍💼 woman office worker: dark skin tone -👨‍🔬 man scientist -👨🏻‍🔬 man scientist: light skin tone -👨🏼‍🔬 man scientist: medium-light skin tone -👨🏽‍🔬 man scientist: medium skin tone -👨🏾‍🔬 man scientist: medium-dark skin tone -👨🏿‍🔬 man scientist: dark skin tone -👩‍🔬 woman scientist -👩🏻‍🔬 woman scientist: light skin tone -👩🏼‍🔬 woman scientist: medium-light skin tone -👩🏽‍🔬 woman scientist: medium skin tone -👩🏾‍🔬 woman scientist: medium-dark skin tone -👩🏿‍🔬 woman scientist: dark skin tone -👨‍💻 man technologist -👨🏻‍💻 man technologist: light skin tone -👨🏼‍💻 man technologist: medium-light skin tone -👨🏽‍💻 man technologist: medium skin tone -👨🏾‍💻 man technologist: medium-dark skin tone -👨🏿‍💻 man technologist: dark skin tone -👩‍💻 woman technologist -👩🏻‍💻 woman technologist: light skin tone -👩🏼‍💻 woman technologist: medium-light skin tone -👩🏽‍💻 woman technologist: medium skin tone -👩🏾‍💻 woman technologist: medium-dark skin tone -👩🏿‍💻 woman technologist: dark skin tone -👨‍🎤 man singer -👨🏻‍🎤 man singer: light skin tone -👨🏼‍🎤 man singer: medium-light skin tone -👨🏽‍🎤 man singer: medium skin tone -👨🏾‍🎤 man singer: medium-dark skin tone -👨🏿‍🎤 man singer: dark skin tone -👩‍🎤 woman singer -👩🏻‍🎤 woman singer: light skin tone -👩🏼‍🎤 woman singer: medium-light skin tone -👩🏽‍🎤 woman singer: medium skin tone -👩🏾‍🎤 woman singer: medium-dark skin tone -👩🏿‍🎤 woman singer: dark skin tone -👨‍🎨 man artist -👨🏻‍🎨 man artist: light skin tone -👨🏼‍🎨 man artist: medium-light skin tone -👨🏽‍🎨 man artist: medium skin tone -👨🏾‍🎨 man artist: medium-dark skin tone -👨🏿‍🎨 man artist: dark skin tone -👩‍🎨 woman artist -👩🏻‍🎨 woman artist: light skin tone -👩🏼‍🎨 woman artist: medium-light skin tone -👩🏽‍🎨 woman artist: medium skin tone -👩🏾‍🎨 woman artist: medium-dark skin tone -👩🏿‍🎨 woman artist: dark skin tone -👨‍✈️ man pilot -👨‍✈ man pilot -👨🏻‍✈️ man pilot: light skin tone -👨🏻‍✈ man pilot: light skin tone -👨🏼‍✈️ man pilot: medium-light skin tone -👨🏼‍✈ man pilot: medium-light skin tone -👨🏽‍✈️ man pilot: medium skin tone -👨🏽‍✈ man pilot: medium skin tone -👨🏾‍✈️ man pilot: medium-dark skin tone -👨🏾‍✈ man pilot: medium-dark skin tone -👨🏿‍✈️ man pilot: dark skin tone -👨🏿‍✈ man pilot: dark skin tone -👩‍✈️ woman pilot -👩‍✈ woman pilot -👩🏻‍✈️ woman pilot: light skin tone -👩🏻‍✈ woman pilot: light skin tone -👩🏼‍✈️ woman pilot: medium-light skin tone -👩🏼‍✈ woman pilot: medium-light skin tone -👩🏽‍✈️ woman pilot: medium skin tone -👩🏽‍✈ woman pilot: medium skin tone -👩🏾‍✈️ woman pilot: medium-dark skin tone -👩🏾‍✈ woman pilot: medium-dark skin tone -👩🏿‍✈️ woman pilot: dark skin tone -👩🏿‍✈ woman pilot: dark skin tone -👨‍🚀 man astronaut -👨🏻‍🚀 man astronaut: light skin tone -👨🏼‍🚀 man astronaut: medium-light skin tone -👨🏽‍🚀 man astronaut: medium skin tone -👨🏾‍🚀 man astronaut: medium-dark skin tone -👨🏿‍🚀 man astronaut: dark skin tone -👩‍🚀 woman astronaut -👩🏻‍🚀 woman astronaut: light skin tone -👩🏼‍🚀 woman astronaut: medium-light skin tone -👩🏽‍🚀 woman astronaut: medium skin tone -👩🏾‍🚀 woman astronaut: medium-dark skin tone -👩🏿‍🚀 woman astronaut: dark skin tone -👨‍🚒 man firefighter -👨🏻‍🚒 man firefighter: light skin tone -👨🏼‍🚒 man firefighter: medium-light skin tone -👨🏽‍🚒 man firefighter: medium skin tone -👨🏾‍🚒 man firefighter: medium-dark skin tone -👨🏿‍🚒 man firefighter: dark skin tone -👩‍🚒 woman firefighter -👩🏻‍🚒 woman firefighter: light skin tone -👩🏼‍🚒 woman firefighter: medium-light skin tone -👩🏽‍🚒 woman firefighter: medium skin tone -👩🏾‍🚒 woman firefighter: medium-dark skin tone -👩🏿‍🚒 woman firefighter: dark skin tone -👮 police officer -👮🏻 police officer: light skin tone -👮🏼 police officer: medium-light skin tone -👮🏽 police officer: medium skin tone -👮🏾 police officer: medium-dark skin tone -👮🏿 police officer: dark skin tone -👮‍♂️ man police officer -👮‍♂ man police officer -👮🏻‍♂️ man police officer: light skin tone -👮🏻‍♂ man police officer: light skin tone -👮🏼‍♂️ man police officer: medium-light skin tone -👮🏼‍♂ man police officer: medium-light skin tone -👮🏽‍♂️ man police officer: medium skin tone -👮🏽‍♂ man police officer: medium skin tone -👮🏾‍♂️ man police officer: medium-dark skin tone -👮🏾‍♂ man police officer: medium-dark skin tone -👮🏿‍♂️ man police officer: dark skin tone -👮🏿‍♂ man police officer: dark skin tone -👮‍♀️ woman police officer -👮‍♀ woman police officer -👮🏻‍♀️ woman police officer: light skin tone -👮🏻‍♀ woman police officer: light skin tone -👮🏼‍♀️ woman police officer: medium-light skin tone -👮🏼‍♀ woman police officer: medium-light skin tone -👮🏽‍♀️ woman police officer: medium skin tone -👮🏽‍♀ woman police officer: medium skin tone -👮🏾‍♀️ woman police officer: medium-dark skin tone -👮🏾‍♀ woman police officer: medium-dark skin tone -👮🏿‍♀️ woman police officer: dark skin tone -👮🏿‍♀ woman police officer: dark skin tone -🕵️ detective -🕵 detective -🕵🏻 detective: light skin tone -🕵🏼 detective: medium-light skin tone -🕵🏽 detective: medium skin tone -🕵🏾 detective: medium-dark skin tone -🕵🏿 detective: dark skin tone -🕵️‍♂️ man detective -🕵‍♂️ man detective -🕵️‍♂ man detective -🕵‍♂ man detective -🕵🏻‍♂️ man detective: light skin tone -🕵🏻‍♂ man detective: light skin tone -🕵🏼‍♂️ man detective: medium-light skin tone -🕵🏼‍♂ man detective: medium-light skin tone -🕵🏽‍♂️ man detective: medium skin tone -🕵🏽‍♂ man detective: medium skin tone -🕵🏾‍♂️ man detective: medium-dark skin tone -🕵🏾‍♂ man detective: medium-dark skin tone -🕵🏿‍♂️ man detective: dark skin tone -🕵🏿‍♂ man detective: dark skin tone -🕵️‍♀️ woman detective -🕵‍♀️ woman detective -🕵️‍♀ woman detective -🕵‍♀ woman detective -🕵🏻‍♀️ woman detective: light skin tone -🕵🏻‍♀ woman detective: light skin tone -🕵🏼‍♀️ woman detective: medium-light skin tone -🕵🏼‍♀ woman detective: medium-light skin tone -🕵🏽‍♀️ woman detective: medium skin tone -🕵🏽‍♀ woman detective: medium skin tone -🕵🏾‍♀️ woman detective: medium-dark skin tone -🕵🏾‍♀ woman detective: medium-dark skin tone -🕵🏿‍♀️ woman detective: dark skin tone -🕵🏿‍♀ woman detective: dark skin tone -💂 guard -💂🏻 guard: light skin tone -💂🏼 guard: medium-light skin tone -💂🏽 guard: medium skin tone -💂🏾 guard: medium-dark skin tone -💂🏿 guard: dark skin tone -💂‍♂️ man guard -💂‍♂ man guard -💂🏻‍♂️ man guard: light skin tone -💂🏻‍♂ man guard: light skin tone -💂🏼‍♂️ man guard: medium-light skin tone -💂🏼‍♂ man guard: medium-light skin tone -💂🏽‍♂️ man guard: medium skin tone -💂🏽‍♂ man guard: medium skin tone -💂🏾‍♂️ man guard: medium-dark skin tone -💂🏾‍♂ man guard: medium-dark skin tone -💂🏿‍♂️ man guard: dark skin tone -💂🏿‍♂ man guard: dark skin tone -💂‍♀️ woman guard -💂‍♀ woman guard -💂🏻‍♀️ woman guard: light skin tone -💂🏻‍♀ woman guard: light skin tone -💂🏼‍♀️ woman guard: medium-light skin tone -💂🏼‍♀ woman guard: medium-light skin tone -💂🏽‍♀️ woman guard: medium skin tone -💂🏽‍♀ woman guard: medium skin tone -💂🏾‍♀️ woman guard: medium-dark skin tone -💂🏾‍♀ woman guard: medium-dark skin tone -💂🏿‍♀️ woman guard: dark skin tone -💂🏿‍♀ woman guard: dark skin tone -👷 construction worker -👷🏻 construction worker: light skin tone -👷🏼 construction worker: medium-light skin tone -👷🏽 construction worker: medium skin tone -👷🏾 construction worker: medium-dark skin tone -👷🏿 construction worker: dark skin tone -👷‍♂️ man construction worker -👷‍♂ man construction worker -👷🏻‍♂️ man construction worker: light skin tone -👷🏻‍♂ man construction worker: light skin tone -👷🏼‍♂️ man construction worker: medium-light skin tone -👷🏼‍♂ man construction worker: medium-light skin tone -👷🏽‍♂️ man construction worker: medium skin tone -👷🏽‍♂ man construction worker: medium skin tone -👷🏾‍♂️ man construction worker: medium-dark skin tone -👷🏾‍♂ man construction worker: medium-dark skin tone -👷🏿‍♂️ man construction worker: dark skin tone -👷🏿‍♂ man construction worker: dark skin tone -👷‍♀️ woman construction worker -👷‍♀ woman construction worker -👷🏻‍♀️ woman construction worker: light skin tone -👷🏻‍♀ woman construction worker: light skin tone -👷🏼‍♀️ woman construction worker: medium-light skin tone -👷🏼‍♀ woman construction worker: medium-light skin tone -👷🏽‍♀️ woman construction worker: medium skin tone -👷🏽‍♀ woman construction worker: medium skin tone -👷🏾‍♀️ woman construction worker: medium-dark skin tone -👷🏾‍♀ woman construction worker: medium-dark skin tone -👷🏿‍♀️ woman construction worker: dark skin tone -👷🏿‍♀ woman construction worker: dark skin tone -🤴 prince -🤴🏻 prince: light skin tone -🤴🏼 prince: medium-light skin tone -🤴🏽 prince: medium skin tone -🤴🏾 prince: medium-dark skin tone -🤴🏿 prince: dark skin tone -👸 princess -👸🏻 princess: light skin tone -👸🏼 princess: medium-light skin tone -👸🏽 princess: medium skin tone -👸🏾 princess: medium-dark skin tone -👸🏿 princess: dark skin tone -👳 person wearing turban -👳🏻 person wearing turban: light skin tone -👳🏼 person wearing turban: medium-light skin tone -👳🏽 person wearing turban: medium skin tone -👳🏾 person wearing turban: medium-dark skin tone -👳🏿 person wearing turban: dark skin tone -👳‍♂️ man wearing turban -👳‍♂ man wearing turban -👳🏻‍♂️ man wearing turban: light skin tone -👳🏻‍♂ man wearing turban: light skin tone -👳🏼‍♂️ man wearing turban: medium-light skin tone -👳🏼‍♂ man wearing turban: medium-light skin tone -👳🏽‍♂️ man wearing turban: medium skin tone -👳🏽‍♂ man wearing turban: medium skin tone -👳🏾‍♂️ man wearing turban: medium-dark skin tone -👳🏾‍♂ man wearing turban: medium-dark skin tone -👳🏿‍♂️ man wearing turban: dark skin tone -👳🏿‍♂ man wearing turban: dark skin tone -👳‍♀️ woman wearing turban -👳‍♀ woman wearing turban -👳🏻‍♀️ woman wearing turban: light skin tone -👳🏻‍♀ woman wearing turban: light skin tone -👳🏼‍♀️ woman wearing turban: medium-light skin tone -👳🏼‍♀ woman wearing turban: medium-light skin tone -👳🏽‍♀️ woman wearing turban: medium skin tone -👳🏽‍♀ woman wearing turban: medium skin tone -👳🏾‍♀️ woman wearing turban: medium-dark skin tone -👳🏾‍♀ woman wearing turban: medium-dark skin tone -👳🏿‍♀️ woman wearing turban: dark skin tone -👳🏿‍♀ woman wearing turban: dark skin tone -👲 man with Chinese cap -👲🏻 man with Chinese cap: light skin tone -👲🏼 man with Chinese cap: medium-light skin tone -👲🏽 man with Chinese cap: medium skin tone -👲🏾 man with Chinese cap: medium-dark skin tone -👲🏿 man with Chinese cap: dark skin tone -🧕 woman with headscarf -🧕🏻 woman with headscarf: light skin tone -🧕🏼 woman with headscarf: medium-light skin tone -🧕🏽 woman with headscarf: medium skin tone -🧕🏾 woman with headscarf: medium-dark skin tone -🧕🏿 woman with headscarf: dark skin tone -🧔 bearded person -🧔🏻 bearded person: light skin tone -🧔🏼 bearded person: medium-light skin tone -🧔🏽 bearded person: medium skin tone -🧔🏾 bearded person: medium-dark skin tone -🧔🏿 bearded person: dark skin tone -👱 blond-haired person -👱🏻 blond-haired person: light skin tone -👱🏼 blond-haired person: medium-light skin tone -👱🏽 blond-haired person: medium skin tone -👱🏾 blond-haired person: medium-dark skin tone -👱🏿 blond-haired person: dark skin tone -👱‍♂️ blond-haired man -👱‍♂ blond-haired man -👱🏻‍♂️ blond-haired man: light skin tone -👱🏻‍♂ blond-haired man: light skin tone -👱🏼‍♂️ blond-haired man: medium-light skin tone -👱🏼‍♂ blond-haired man: medium-light skin tone -👱🏽‍♂️ blond-haired man: medium skin tone -👱🏽‍♂ blond-haired man: medium skin tone -👱🏾‍♂️ blond-haired man: medium-dark skin tone -👱🏾‍♂ blond-haired man: medium-dark skin tone -👱🏿‍♂️ blond-haired man: dark skin tone -👱🏿‍♂ blond-haired man: dark skin tone -👱‍♀️ blond-haired woman -👱‍♀ blond-haired woman -👱🏻‍♀️ blond-haired woman: light skin tone -👱🏻‍♀ blond-haired woman: light skin tone -👱🏼‍♀️ blond-haired woman: medium-light skin tone -👱🏼‍♀ blond-haired woman: medium-light skin tone -👱🏽‍♀️ blond-haired woman: medium skin tone -👱🏽‍♀ blond-haired woman: medium skin tone -👱🏾‍♀️ blond-haired woman: medium-dark skin tone -👱🏾‍♀ blond-haired woman: medium-dark skin tone -👱🏿‍♀️ blond-haired woman: dark skin tone -👱🏿‍♀ blond-haired woman: dark skin tone -👨‍🦰 man, red haired -👨🏻‍🦰 man, red haired: light skin tone -👨🏼‍🦰 man, red haired: medium-light skin tone -👨🏽‍🦰 man, red haired: medium skin tone -👨🏾‍🦰 man, red haired: medium-dark skin tone -👨🏿‍🦰 man, red haired: dark skin tone -👩‍🦰 woman, red haired -👩🏻‍🦰 woman, red haired: light skin tone -👩🏼‍🦰 woman, red haired: medium-light skin tone -👩🏽‍🦰 woman, red haired: medium skin tone -👩🏾‍🦰 woman, red haired: medium-dark skin tone -👩🏿‍🦰 woman, red haired: dark skin tone -👨‍🦱 man, curly haired -👨🏻‍🦱 man, curly haired: light skin tone -👨🏼‍🦱 man, curly haired: medium-light skin tone -👨🏽‍🦱 man, curly haired: medium skin tone -👨🏾‍🦱 man, curly haired: medium-dark skin tone -👨🏿‍🦱 man, curly haired: dark skin tone -👩‍🦱 woman, curly haired -👩🏻‍🦱 woman, curly haired: light skin tone -👩🏼‍🦱 woman, curly haired: medium-light skin tone -👩🏽‍🦱 woman, curly haired: medium skin tone -👩🏾‍🦱 woman, curly haired: medium-dark skin tone -👩🏿‍🦱 woman, curly haired: dark skin tone -👨‍🦲 man, bald -👨🏻‍🦲 man, bald: light skin tone -👨🏼‍🦲 man, bald: medium-light skin tone -👨🏽‍🦲 man, bald: medium skin tone -👨🏾‍🦲 man, bald: medium-dark skin tone -👨🏿‍🦲 man, bald: dark skin tone -👩‍🦲 woman, bald -👩🏻‍🦲 woman, bald: light skin tone -👩🏼‍🦲 woman, bald: medium-light skin tone -👩🏽‍🦲 woman, bald: medium skin tone -👩🏾‍🦲 woman, bald: medium-dark skin tone -👩🏿‍🦲 woman, bald: dark skin tone -👨‍🦳 man, white haired -👨🏻‍🦳 man, white haired: light skin tone -👨🏼‍🦳 man, white haired: medium-light skin tone -👨🏽‍🦳 man, white haired: medium skin tone -👨🏾‍🦳 man, white haired: medium-dark skin tone -👨🏿‍🦳 man, white haired: dark skin tone -👩‍🦳 woman, white haired -👩🏻‍🦳 woman, white haired: light skin tone -👩🏼‍🦳 woman, white haired: medium-light skin tone -👩🏽‍🦳 woman, white haired: medium skin tone -👩🏾‍🦳 woman, white haired: medium-dark skin tone -👩🏿‍🦳 woman, white haired: dark skin tone -🤵 man in tuxedo -🤵🏻 man in tuxedo: light skin tone -🤵🏼 man in tuxedo: medium-light skin tone -🤵🏽 man in tuxedo: medium skin tone -🤵🏾 man in tuxedo: medium-dark skin tone -🤵🏿 man in tuxedo: dark skin tone -👰 bride with veil -👰🏻 bride with veil: light skin tone -👰🏼 bride with veil: medium-light skin tone -👰🏽 bride with veil: medium skin tone -👰🏾 bride with veil: medium-dark skin tone -👰🏿 bride with veil: dark skin tone -🤰 pregnant woman -🤰🏻 pregnant woman: light skin tone -🤰🏼 pregnant woman: medium-light skin tone -🤰🏽 pregnant woman: medium skin tone -🤰🏾 pregnant woman: medium-dark skin tone -🤰🏿 pregnant woman: dark skin tone -🤱 breast-feeding -🤱🏻 breast-feeding: light skin tone -🤱🏼 breast-feeding: medium-light skin tone -🤱🏽 breast-feeding: medium skin tone -🤱🏾 breast-feeding: medium-dark skin tone -🤱🏿 breast-feeding: dark skin tone -👼 baby angel -👼🏻 baby angel: light skin tone -👼🏼 baby angel: medium-light skin tone -👼🏽 baby angel: medium skin tone -👼🏾 baby angel: medium-dark skin tone -👼🏿 baby angel: dark skin tone -🎅 Santa Claus -🎅🏻 Santa Claus: light skin tone -🎅🏼 Santa Claus: medium-light skin tone -🎅🏽 Santa Claus: medium skin tone -🎅🏾 Santa Claus: medium-dark skin tone -🎅🏿 Santa Claus: dark skin tone -🤶 Mrs. Claus -🤶🏻 Mrs. Claus: light skin tone -🤶🏼 Mrs. Claus: medium-light skin tone -🤶🏽 Mrs. Claus: medium skin tone -🤶🏾 Mrs. Claus: medium-dark skin tone -🤶🏿 Mrs. Claus: dark skin tone -🦸 superhero -🦸🏻 superhero: light skin tone -🦸🏼 superhero: medium-light skin tone -🦸🏽 superhero: medium skin tone -🦸🏾 superhero: medium-dark skin tone -🦸🏿 superhero: dark skin tone -🦸‍♀️ woman superhero -🦸‍♀ woman superhero -🦸🏻‍♀️ woman superhero: light skin tone -🦸🏻‍♀ woman superhero: light skin tone -🦸🏼‍♀️ woman superhero: medium-light skin tone -🦸🏼‍♀ woman superhero: medium-light skin tone -🦸🏽‍♀️ woman superhero: medium skin tone -🦸🏽‍♀ woman superhero: medium skin tone -🦸🏾‍♀️ woman superhero: medium-dark skin tone -🦸🏾‍♀ woman superhero: medium-dark skin tone -🦸🏿‍♀️ woman superhero: dark skin tone -🦸🏿‍♀ woman superhero: dark skin tone -🦸‍♂️ man superhero -🦸‍♂ man superhero -🦸🏻‍♂️ man superhero: light skin tone -🦸🏻‍♂ man superhero: light skin tone -🦸🏼‍♂️ man superhero: medium-light skin tone -🦸🏼‍♂ man superhero: medium-light skin tone -🦸🏽‍♂️ man superhero: medium skin tone -🦸🏽‍♂ man superhero: medium skin tone -🦸🏾‍♂️ man superhero: medium-dark skin tone -🦸🏾‍♂ man superhero: medium-dark skin tone -🦸🏿‍♂️ man superhero: dark skin tone -🦸🏿‍♂ man superhero: dark skin tone -🦹 supervillain -🦹🏻 supervillain: light skin tone -🦹🏼 supervillain: medium-light skin tone -🦹🏽 supervillain: medium skin tone -🦹🏾 supervillain: medium-dark skin tone -🦹🏿 supervillain: dark skin tone -🦹‍♀️ woman supervillain -🦹‍♀ woman supervillain -🦹🏻‍♀️ woman supervillain: light skin tone -🦹🏻‍♀ woman supervillain: light skin tone -🦹🏼‍♀️ woman supervillain: medium-light skin tone -🦹🏼‍♀ woman supervillain: medium-light skin tone -🦹🏽‍♀️ woman supervillain: medium skin tone -🦹🏽‍♀ woman supervillain: medium skin tone -🦹🏾‍♀️ woman supervillain: medium-dark skin tone -🦹🏾‍♀ woman supervillain: medium-dark skin tone -🦹🏿‍♀️ woman supervillain: dark skin tone -🦹🏿‍♀ woman supervillain: dark skin tone -🦹‍♂️ man supervillain -🦹‍♂ man supervillain -🦹🏻‍♂️ man supervillain: light skin tone -🦹🏻‍♂ man supervillain: light skin tone -🦹🏼‍♂️ man supervillain: medium-light skin tone -🦹🏼‍♂ man supervillain: medium-light skin tone -🦹🏽‍♂️ man supervillain: medium skin tone -🦹🏽‍♂ man supervillain: medium skin tone -🦹🏾‍♂️ man supervillain: medium-dark skin tone -🦹🏾‍♂ man supervillain: medium-dark skin tone -🦹🏿‍♂️ man supervillain: dark skin tone -🦹🏿‍♂ man supervillain: dark skin tone -🧙 mage -🧙🏻 mage: light skin tone -🧙🏼 mage: medium-light skin tone -🧙🏽 mage: medium skin tone -🧙🏾 mage: medium-dark skin tone -🧙🏿 mage: dark skin tone -🧙‍♀️ woman mage -🧙‍♀ woman mage -🧙🏻‍♀️ woman mage: light skin tone -🧙🏻‍♀ woman mage: light skin tone -🧙🏼‍♀️ woman mage: medium-light skin tone -🧙🏼‍♀ woman mage: medium-light skin tone -🧙🏽‍♀️ woman mage: medium skin tone -🧙🏽‍♀ woman mage: medium skin tone -🧙🏾‍♀️ woman mage: medium-dark skin tone -🧙🏾‍♀ woman mage: medium-dark skin tone -🧙🏿‍♀️ woman mage: dark skin tone -🧙🏿‍♀ woman mage: dark skin tone -🧙‍♂️ man mage -🧙‍♂ man mage -🧙🏻‍♂️ man mage: light skin tone -🧙🏻‍♂ man mage: light skin tone -🧙🏼‍♂️ man mage: medium-light skin tone -🧙🏼‍♂ man mage: medium-light skin tone -🧙🏽‍♂️ man mage: medium skin tone -🧙🏽‍♂ man mage: medium skin tone -🧙🏾‍♂️ man mage: medium-dark skin tone -🧙🏾‍♂ man mage: medium-dark skin tone -🧙🏿‍♂️ man mage: dark skin tone -🧙🏿‍♂ man mage: dark skin tone -🧚 fairy -🧚🏻 fairy: light skin tone -🧚🏼 fairy: medium-light skin tone -🧚🏽 fairy: medium skin tone -🧚🏾 fairy: medium-dark skin tone -🧚🏿 fairy: dark skin tone -🧚‍♀️ woman fairy -🧚‍♀ woman fairy -🧚🏻‍♀️ woman fairy: light skin tone -🧚🏻‍♀ woman fairy: light skin tone -🧚🏼‍♀️ woman fairy: medium-light skin tone -🧚🏼‍♀ woman fairy: medium-light skin tone -🧚🏽‍♀️ woman fairy: medium skin tone -🧚🏽‍♀ woman fairy: medium skin tone -🧚🏾‍♀️ woman fairy: medium-dark skin tone -🧚🏾‍♀ woman fairy: medium-dark skin tone -🧚🏿‍♀️ woman fairy: dark skin tone -🧚🏿‍♀ woman fairy: dark skin tone -🧚‍♂️ man fairy -🧚‍♂ man fairy -🧚🏻‍♂️ man fairy: light skin tone -🧚🏻‍♂ man fairy: light skin tone -🧚🏼‍♂️ man fairy: medium-light skin tone -🧚🏼‍♂ man fairy: medium-light skin tone -🧚🏽‍♂️ man fairy: medium skin tone -🧚🏽‍♂ man fairy: medium skin tone -🧚🏾‍♂️ man fairy: medium-dark skin tone -🧚🏾‍♂ man fairy: medium-dark skin tone -🧚🏿‍♂️ man fairy: dark skin tone -🧚🏿‍♂ man fairy: dark skin tone -🧛 vampire -🧛🏻 vampire: light skin tone -🧛🏼 vampire: medium-light skin tone -🧛🏽 vampire: medium skin tone -🧛🏾 vampire: medium-dark skin tone -🧛🏿 vampire: dark skin tone -🧛‍♀️ woman vampire -🧛‍♀ woman vampire -🧛🏻‍♀️ woman vampire: light skin tone -🧛🏻‍♀ woman vampire: light skin tone -🧛🏼‍♀️ woman vampire: medium-light skin tone -🧛🏼‍♀ woman vampire: medium-light skin tone -🧛🏽‍♀️ woman vampire: medium skin tone -🧛🏽‍♀ woman vampire: medium skin tone -🧛🏾‍♀️ woman vampire: medium-dark skin tone -🧛🏾‍♀ woman vampire: medium-dark skin tone -🧛🏿‍♀️ woman vampire: dark skin tone -🧛🏿‍♀ woman vampire: dark skin tone -🧛‍♂️ man vampire -🧛‍♂ man vampire -🧛🏻‍♂️ man vampire: light skin tone -🧛🏻‍♂ man vampire: light skin tone -🧛🏼‍♂️ man vampire: medium-light skin tone -🧛🏼‍♂ man vampire: medium-light skin tone -🧛🏽‍♂️ man vampire: medium skin tone -🧛🏽‍♂ man vampire: medium skin tone -🧛🏾‍♂️ man vampire: medium-dark skin tone -🧛🏾‍♂ man vampire: medium-dark skin tone -🧛🏿‍♂️ man vampire: dark skin tone -🧛🏿‍♂ man vampire: dark skin tone -🧜 merperson -🧜🏻 merperson: light skin tone -🧜🏼 merperson: medium-light skin tone -🧜🏽 merperson: medium skin tone -🧜🏾 merperson: medium-dark skin tone -🧜🏿 merperson: dark skin tone -🧜‍♀️ mermaid -🧜‍♀ mermaid -🧜🏻‍♀️ mermaid: light skin tone -🧜🏻‍♀ mermaid: light skin tone -🧜🏼‍♀️ mermaid: medium-light skin tone -🧜🏼‍♀ mermaid: medium-light skin tone -🧜🏽‍♀️ mermaid: medium skin tone -🧜🏽‍♀ mermaid: medium skin tone -🧜🏾‍♀️ mermaid: medium-dark skin tone -🧜🏾‍♀ mermaid: medium-dark skin tone -🧜🏿‍♀️ mermaid: dark skin tone -🧜🏿‍♀ mermaid: dark skin tone -🧜‍♂️ merman -🧜‍♂ merman -🧜🏻‍♂️ merman: light skin tone -🧜🏻‍♂ merman: light skin tone -🧜🏼‍♂️ merman: medium-light skin tone -🧜🏼‍♂ merman: medium-light skin tone -🧜🏽‍♂️ merman: medium skin tone -🧜🏽‍♂ merman: medium skin tone -🧜🏾‍♂️ merman: medium-dark skin tone -🧜🏾‍♂ merman: medium-dark skin tone -🧜🏿‍♂️ merman: dark skin tone -🧜🏿‍♂ merman: dark skin tone -🧝 elf -🧝🏻 elf: light skin tone -🧝🏼 elf: medium-light skin tone -🧝🏽 elf: medium skin tone -🧝🏾 elf: medium-dark skin tone -🧝🏿 elf: dark skin tone -🧝‍♀️ woman elf -🧝‍♀ woman elf -🧝🏻‍♀️ woman elf: light skin tone -🧝🏻‍♀ woman elf: light skin tone -🧝🏼‍♀️ woman elf: medium-light skin tone -🧝🏼‍♀ woman elf: medium-light skin tone -🧝🏽‍♀️ woman elf: medium skin tone -🧝🏽‍♀ woman elf: medium skin tone -🧝🏾‍♀️ woman elf: medium-dark skin tone -🧝🏾‍♀ woman elf: medium-dark skin tone -🧝🏿‍♀️ woman elf: dark skin tone -🧝🏿‍♀ woman elf: dark skin tone -🧝‍♂️ man elf -🧝‍♂ man elf -🧝🏻‍♂️ man elf: light skin tone -🧝🏻‍♂ man elf: light skin tone -🧝🏼‍♂️ man elf: medium-light skin tone -🧝🏼‍♂ man elf: medium-light skin tone -🧝🏽‍♂️ man elf: medium skin tone -🧝🏽‍♂ man elf: medium skin tone -🧝🏾‍♂️ man elf: medium-dark skin tone -🧝🏾‍♂ man elf: medium-dark skin tone -🧝🏿‍♂️ man elf: dark skin tone -🧝🏿‍♂ man elf: dark skin tone -🧞 genie -🧞‍♀️ woman genie -🧞‍♀ woman genie -🧞‍♂️ man genie -🧞‍♂ man genie -🧟 zombie -🧟‍♀️ woman zombie -🧟‍♀ woman zombie -🧟‍♂️ man zombie -🧟‍♂ man zombie -🙍 person frowning -🙍🏻 person frowning: light skin tone -🙍🏼 person frowning: medium-light skin tone -🙍🏽 person frowning: medium skin tone -🙍🏾 person frowning: medium-dark skin tone -🙍🏿 person frowning: dark skin tone -🙍‍♂️ man frowning -🙍‍♂ man frowning -🙍🏻‍♂️ man frowning: light skin tone -🙍🏻‍♂ man frowning: light skin tone -🙍🏼‍♂️ man frowning: medium-light skin tone -🙍🏼‍♂ man frowning: medium-light skin tone -🙍🏽‍♂️ man frowning: medium skin tone -🙍🏽‍♂ man frowning: medium skin tone -🙍🏾‍♂️ man frowning: medium-dark skin tone -🙍🏾‍♂ man frowning: medium-dark skin tone -🙍🏿‍♂️ man frowning: dark skin tone -🙍🏿‍♂ man frowning: dark skin tone -🙍‍♀️ woman frowning -🙍‍♀ woman frowning -🙍🏻‍♀️ woman frowning: light skin tone -🙍🏻‍♀ woman frowning: light skin tone -🙍🏼‍♀️ woman frowning: medium-light skin tone -🙍🏼‍♀ woman frowning: medium-light skin tone -🙍🏽‍♀️ woman frowning: medium skin tone -🙍🏽‍♀ woman frowning: medium skin tone -🙍🏾‍♀️ woman frowning: medium-dark skin tone -🙍🏾‍♀ woman frowning: medium-dark skin tone -🙍🏿‍♀️ woman frowning: dark skin tone -🙍🏿‍♀ woman frowning: dark skin tone -🙎 person pouting -🙎🏻 person pouting: light skin tone -🙎🏼 person pouting: medium-light skin tone -🙎🏽 person pouting: medium skin tone -🙎🏾 person pouting: medium-dark skin tone -🙎🏿 person pouting: dark skin tone -🙎‍♂️ man pouting -🙎‍♂ man pouting -🙎🏻‍♂️ man pouting: light skin tone -🙎🏻‍♂ man pouting: light skin tone -🙎🏼‍♂️ man pouting: medium-light skin tone -🙎🏼‍♂ man pouting: medium-light skin tone -🙎🏽‍♂️ man pouting: medium skin tone -🙎🏽‍♂ man pouting: medium skin tone -🙎🏾‍♂️ man pouting: medium-dark skin tone -🙎🏾‍♂ man pouting: medium-dark skin tone -🙎🏿‍♂️ man pouting: dark skin tone -🙎🏿‍♂ man pouting: dark skin tone -🙎‍♀️ woman pouting -🙎‍♀ woman pouting -🙎🏻‍♀️ woman pouting: light skin tone -🙎🏻‍♀ woman pouting: light skin tone -🙎🏼‍♀️ woman pouting: medium-light skin tone -🙎🏼‍♀ woman pouting: medium-light skin tone -🙎🏽‍♀️ woman pouting: medium skin tone -🙎🏽‍♀ woman pouting: medium skin tone -🙎🏾‍♀️ woman pouting: medium-dark skin tone -🙎🏾‍♀ woman pouting: medium-dark skin tone -🙎🏿‍♀️ woman pouting: dark skin tone -🙎🏿‍♀ woman pouting: dark skin tone -🙅 person gesturing NO -🙅🏻 person gesturing NO: light skin tone -🙅🏼 person gesturing NO: medium-light skin tone -🙅🏽 person gesturing NO: medium skin tone -🙅🏾 person gesturing NO: medium-dark skin tone -🙅🏿 person gesturing NO: dark skin tone -🙅‍♂️ man gesturing NO -🙅‍♂ man gesturing NO -🙅🏻‍♂️ man gesturing NO: light skin tone -🙅🏻‍♂ man gesturing NO: light skin tone -🙅🏼‍♂️ man gesturing NO: medium-light skin tone -🙅🏼‍♂ man gesturing NO: medium-light skin tone -🙅🏽‍♂️ man gesturing NO: medium skin tone -🙅🏽‍♂ man gesturing NO: medium skin tone -🙅🏾‍♂️ man gesturing NO: medium-dark skin tone -🙅🏾‍♂ man gesturing NO: medium-dark skin tone -🙅🏿‍♂️ man gesturing NO: dark skin tone -🙅🏿‍♂ man gesturing NO: dark skin tone -🙅‍♀️ woman gesturing NO -🙅‍♀ woman gesturing NO -🙅🏻‍♀️ woman gesturing NO: light skin tone -🙅🏻‍♀ woman gesturing NO: light skin tone -🙅🏼‍♀️ woman gesturing NO: medium-light skin tone -🙅🏼‍♀ woman gesturing NO: medium-light skin tone -🙅🏽‍♀️ woman gesturing NO: medium skin tone -🙅🏽‍♀ woman gesturing NO: medium skin tone -🙅🏾‍♀️ woman gesturing NO: medium-dark skin tone -🙅🏾‍♀ woman gesturing NO: medium-dark skin tone -🙅🏿‍♀️ woman gesturing NO: dark skin tone -🙅🏿‍♀ woman gesturing NO: dark skin tone -🙆 person gesturing OK -🙆🏻 person gesturing OK: light skin tone -🙆🏼 person gesturing OK: medium-light skin tone -🙆🏽 person gesturing OK: medium skin tone -🙆🏾 person gesturing OK: medium-dark skin tone -🙆🏿 person gesturing OK: dark skin tone -🙆‍♂️ man gesturing OK -🙆‍♂ man gesturing OK -🙆🏻‍♂️ man gesturing OK: light skin tone -🙆🏻‍♂ man gesturing OK: light skin tone -🙆🏼‍♂️ man gesturing OK: medium-light skin tone -🙆🏼‍♂ man gesturing OK: medium-light skin tone -🙆🏽‍♂️ man gesturing OK: medium skin tone -🙆🏽‍♂ man gesturing OK: medium skin tone -🙆🏾‍♂️ man gesturing OK: medium-dark skin tone -🙆🏾‍♂ man gesturing OK: medium-dark skin tone -🙆🏿‍♂️ man gesturing OK: dark skin tone -🙆🏿‍♂ man gesturing OK: dark skin tone -🙆‍♀️ woman gesturing OK -🙆‍♀ woman gesturing OK -🙆🏻‍♀️ woman gesturing OK: light skin tone -🙆🏻‍♀ woman gesturing OK: light skin tone -🙆🏼‍♀️ woman gesturing OK: medium-light skin tone -🙆🏼‍♀ woman gesturing OK: medium-light skin tone -🙆🏽‍♀️ woman gesturing OK: medium skin tone -🙆🏽‍♀ woman gesturing OK: medium skin tone -🙆🏾‍♀️ woman gesturing OK: medium-dark skin tone -🙆🏾‍♀ woman gesturing OK: medium-dark skin tone -🙆🏿‍♀️ woman gesturing OK: dark skin tone -🙆🏿‍♀ woman gesturing OK: dark skin tone -💁 person tipping hand -💁🏻 person tipping hand: light skin tone -💁🏼 person tipping hand: medium-light skin tone -💁🏽 person tipping hand: medium skin tone -💁🏾 person tipping hand: medium-dark skin tone -💁🏿 person tipping hand: dark skin tone -💁‍♂️ man tipping hand -💁‍♂ man tipping hand -💁🏻‍♂️ man tipping hand: light skin tone -💁🏻‍♂ man tipping hand: light skin tone -💁🏼‍♂️ man tipping hand: medium-light skin tone -💁🏼‍♂ man tipping hand: medium-light skin tone -💁🏽‍♂️ man tipping hand: medium skin tone -💁🏽‍♂ man tipping hand: medium skin tone -💁🏾‍♂️ man tipping hand: medium-dark skin tone -💁🏾‍♂ man tipping hand: medium-dark skin tone -💁🏿‍♂️ man tipping hand: dark skin tone -💁🏿‍♂ man tipping hand: dark skin tone -💁‍♀️ woman tipping hand -💁‍♀ woman tipping hand -💁🏻‍♀️ woman tipping hand: light skin tone -💁🏻‍♀ woman tipping hand: light skin tone -💁🏼‍♀️ woman tipping hand: medium-light skin tone -💁🏼‍♀ woman tipping hand: medium-light skin tone -💁🏽‍♀️ woman tipping hand: medium skin tone -💁🏽‍♀ woman tipping hand: medium skin tone -💁🏾‍♀️ woman tipping hand: medium-dark skin tone -💁🏾‍♀ woman tipping hand: medium-dark skin tone -💁🏿‍♀️ woman tipping hand: dark skin tone -💁🏿‍♀ woman tipping hand: dark skin tone -🙋 person raising hand -🙋🏻 person raising hand: light skin tone -🙋🏼 person raising hand: medium-light skin tone -🙋🏽 person raising hand: medium skin tone -🙋🏾 person raising hand: medium-dark skin tone -🙋🏿 person raising hand: dark skin tone -🙋‍♂️ man raising hand -🙋‍♂ man raising hand -🙋🏻‍♂️ man raising hand: light skin tone -🙋🏻‍♂ man raising hand: light skin tone -🙋🏼‍♂️ man raising hand: medium-light skin tone -🙋🏼‍♂ man raising hand: medium-light skin tone -🙋🏽‍♂️ man raising hand: medium skin tone -🙋🏽‍♂ man raising hand: medium skin tone -🙋🏾‍♂️ man raising hand: medium-dark skin tone -🙋🏾‍♂ man raising hand: medium-dark skin tone -🙋🏿‍♂️ man raising hand: dark skin tone -🙋🏿‍♂ man raising hand: dark skin tone -🙋‍♀️ woman raising hand -🙋‍♀ woman raising hand -🙋🏻‍♀️ woman raising hand: light skin tone -🙋🏻‍♀ woman raising hand: light skin tone -🙋🏼‍♀️ woman raising hand: medium-light skin tone -🙋🏼‍♀ woman raising hand: medium-light skin tone -🙋🏽‍♀️ woman raising hand: medium skin tone -🙋🏽‍♀ woman raising hand: medium skin tone -🙋🏾‍♀️ woman raising hand: medium-dark skin tone -🙋🏾‍♀ woman raising hand: medium-dark skin tone -🙋🏿‍♀️ woman raising hand: dark skin tone -🙋🏿‍♀ woman raising hand: dark skin tone -🙇 person bowing -🙇🏻 person bowing: light skin tone -🙇🏼 person bowing: medium-light skin tone -🙇🏽 person bowing: medium skin tone -🙇🏾 person bowing: medium-dark skin tone -🙇🏿 person bowing: dark skin tone -🙇‍♂️ man bowing -🙇‍♂ man bowing -🙇🏻‍♂️ man bowing: light skin tone -🙇🏻‍♂ man bowing: light skin tone -🙇🏼‍♂️ man bowing: medium-light skin tone -🙇🏼‍♂ man bowing: medium-light skin tone -🙇🏽‍♂️ man bowing: medium skin tone -🙇🏽‍♂ man bowing: medium skin tone -🙇🏾‍♂️ man bowing: medium-dark skin tone -🙇🏾‍♂ man bowing: medium-dark skin tone -🙇🏿‍♂️ man bowing: dark skin tone -🙇🏿‍♂ man bowing: dark skin tone -🙇‍♀️ woman bowing -🙇‍♀ woman bowing -🙇🏻‍♀️ woman bowing: light skin tone -🙇🏻‍♀ woman bowing: light skin tone -🙇🏼‍♀️ woman bowing: medium-light skin tone -🙇🏼‍♀ woman bowing: medium-light skin tone -🙇🏽‍♀️ woman bowing: medium skin tone -🙇🏽‍♀ woman bowing: medium skin tone -🙇🏾‍♀️ woman bowing: medium-dark skin tone -🙇🏾‍♀ woman bowing: medium-dark skin tone -🙇🏿‍♀️ woman bowing: dark skin tone -🙇🏿‍♀ woman bowing: dark skin tone -🤦 person facepalming -🤦🏻 person facepalming: light skin tone -🤦🏼 person facepalming: medium-light skin tone -🤦🏽 person facepalming: medium skin tone -🤦🏾 person facepalming: medium-dark skin tone -🤦🏿 person facepalming: dark skin tone -🤦‍♂️ man facepalming -🤦‍♂ man facepalming -🤦🏻‍♂️ man facepalming: light skin tone -🤦🏻‍♂ man facepalming: light skin tone -🤦🏼‍♂️ man facepalming: medium-light skin tone -🤦🏼‍♂ man facepalming: medium-light skin tone -🤦🏽‍♂️ man facepalming: medium skin tone -🤦🏽‍♂ man facepalming: medium skin tone -🤦🏾‍♂️ man facepalming: medium-dark skin tone -🤦🏾‍♂ man facepalming: medium-dark skin tone -🤦🏿‍♂️ man facepalming: dark skin tone -🤦🏿‍♂ man facepalming: dark skin tone -🤦‍♀️ woman facepalming -🤦‍♀ woman facepalming -🤦🏻‍♀️ woman facepalming: light skin tone -🤦🏻‍♀ woman facepalming: light skin tone -🤦🏼‍♀️ woman facepalming: medium-light skin tone -🤦🏼‍♀ woman facepalming: medium-light skin tone -🤦🏽‍♀️ woman facepalming: medium skin tone -🤦🏽‍♀ woman facepalming: medium skin tone -🤦🏾‍♀️ woman facepalming: medium-dark skin tone -🤦🏾‍♀ woman facepalming: medium-dark skin tone -🤦🏿‍♀️ woman facepalming: dark skin tone -🤦🏿‍♀ woman facepalming: dark skin tone -🤷 person shrugging -🤷🏻 person shrugging: light skin tone -🤷🏼 person shrugging: medium-light skin tone -🤷🏽 person shrugging: medium skin tone -🤷🏾 person shrugging: medium-dark skin tone -🤷🏿 person shrugging: dark skin tone -🤷‍♂️ man shrugging -🤷‍♂ man shrugging -🤷🏻‍♂️ man shrugging: light skin tone -🤷🏻‍♂ man shrugging: light skin tone -🤷🏼‍♂️ man shrugging: medium-light skin tone -🤷🏼‍♂ man shrugging: medium-light skin tone -🤷🏽‍♂️ man shrugging: medium skin tone -🤷🏽‍♂ man shrugging: medium skin tone -🤷🏾‍♂️ man shrugging: medium-dark skin tone -🤷🏾‍♂ man shrugging: medium-dark skin tone -🤷🏿‍♂️ man shrugging: dark skin tone -🤷🏿‍♂ man shrugging: dark skin tone -🤷‍♀️ woman shrugging -🤷‍♀ woman shrugging -🤷🏻‍♀️ woman shrugging: light skin tone -🤷🏻‍♀ woman shrugging: light skin tone -🤷🏼‍♀️ woman shrugging: medium-light skin tone -🤷🏼‍♀ woman shrugging: medium-light skin tone -🤷🏽‍♀️ woman shrugging: medium skin tone -🤷🏽‍♀ woman shrugging: medium skin tone -🤷🏾‍♀️ woman shrugging: medium-dark skin tone -🤷🏾‍♀ woman shrugging: medium-dark skin tone -🤷🏿‍♀️ woman shrugging: dark skin tone -🤷🏿‍♀ woman shrugging: dark skin tone -💆 person getting massage -💆🏻 person getting massage: light skin tone -💆🏼 person getting massage: medium-light skin tone -💆🏽 person getting massage: medium skin tone -💆🏾 person getting massage: medium-dark skin tone -💆🏿 person getting massage: dark skin tone -💆‍♂️ man getting massage -💆‍♂ man getting massage -💆🏻‍♂️ man getting massage: light skin tone -💆🏻‍♂ man getting massage: light skin tone -💆🏼‍♂️ man getting massage: medium-light skin tone -💆🏼‍♂ man getting massage: medium-light skin tone -💆🏽‍♂️ man getting massage: medium skin tone -💆🏽‍♂ man getting massage: medium skin tone -💆🏾‍♂️ man getting massage: medium-dark skin tone -💆🏾‍♂ man getting massage: medium-dark skin tone -💆🏿‍♂️ man getting massage: dark skin tone -💆🏿‍♂ man getting massage: dark skin tone -💆‍♀️ woman getting massage -💆‍♀ woman getting massage -💆🏻‍♀️ woman getting massage: light skin tone -💆🏻‍♀ woman getting massage: light skin tone -💆🏼‍♀️ woman getting massage: medium-light skin tone -💆🏼‍♀ woman getting massage: medium-light skin tone -💆🏽‍♀️ woman getting massage: medium skin tone -💆🏽‍♀ woman getting massage: medium skin tone -💆🏾‍♀️ woman getting massage: medium-dark skin tone -💆🏾‍♀ woman getting massage: medium-dark skin tone -💆🏿‍♀️ woman getting massage: dark skin tone -💆🏿‍♀ woman getting massage: dark skin tone -💇 person getting haircut -💇🏻 person getting haircut: light skin tone -💇🏼 person getting haircut: medium-light skin tone -💇🏽 person getting haircut: medium skin tone -💇🏾 person getting haircut: medium-dark skin tone -💇🏿 person getting haircut: dark skin tone -💇‍♂️ man getting haircut -💇‍♂ man getting haircut -💇🏻‍♂️ man getting haircut: light skin tone -💇🏻‍♂ man getting haircut: light skin tone -💇🏼‍♂️ man getting haircut: medium-light skin tone -💇🏼‍♂ man getting haircut: medium-light skin tone -💇🏽‍♂️ man getting haircut: medium skin tone -💇🏽‍♂ man getting haircut: medium skin tone -💇🏾‍♂️ man getting haircut: medium-dark skin tone -💇🏾‍♂ man getting haircut: medium-dark skin tone -💇🏿‍♂️ man getting haircut: dark skin tone -💇🏿‍♂ man getting haircut: dark skin tone -💇‍♀️ woman getting haircut -💇‍♀ woman getting haircut -💇🏻‍♀️ woman getting haircut: light skin tone -💇🏻‍♀ woman getting haircut: light skin tone -💇🏼‍♀️ woman getting haircut: medium-light skin tone -💇🏼‍♀ woman getting haircut: medium-light skin tone -💇🏽‍♀️ woman getting haircut: medium skin tone -💇🏽‍♀ woman getting haircut: medium skin tone -💇🏾‍♀️ woman getting haircut: medium-dark skin tone -💇🏾‍♀ woman getting haircut: medium-dark skin tone -💇🏿‍♀️ woman getting haircut: dark skin tone -💇🏿‍♀ woman getting haircut: dark skin tone -🚶 person walking -🚶🏻 person walking: light skin tone -🚶🏼 person walking: medium-light skin tone -🚶🏽 person walking: medium skin tone -🚶🏾 person walking: medium-dark skin tone -🚶🏿 person walking: dark skin tone -🚶‍♂️ man walking -🚶‍♂ man walking -🚶🏻‍♂️ man walking: light skin tone -🚶🏻‍♂ man walking: light skin tone -🚶🏼‍♂️ man walking: medium-light skin tone -🚶🏼‍♂ man walking: medium-light skin tone -🚶🏽‍♂️ man walking: medium skin tone -🚶🏽‍♂ man walking: medium skin tone -🚶🏾‍♂️ man walking: medium-dark skin tone -🚶🏾‍♂ man walking: medium-dark skin tone -🚶🏿‍♂️ man walking: dark skin tone -🚶🏿‍♂ man walking: dark skin tone -🚶‍♀️ woman walking -🚶‍♀ woman walking -🚶🏻‍♀️ woman walking: light skin tone -🚶🏻‍♀ woman walking: light skin tone -🚶🏼‍♀️ woman walking: medium-light skin tone -🚶🏼‍♀ woman walking: medium-light skin tone -🚶🏽‍♀️ woman walking: medium skin tone -🚶🏽‍♀ woman walking: medium skin tone -🚶🏾‍♀️ woman walking: medium-dark skin tone -🚶🏾‍♀ woman walking: medium-dark skin tone -🚶🏿‍♀️ woman walking: dark skin tone -🚶🏿‍♀ woman walking: dark skin tone -🏃 person running -🏃🏻 person running: light skin tone -🏃🏼 person running: medium-light skin tone -🏃🏽 person running: medium skin tone -🏃🏾 person running: medium-dark skin tone -🏃🏿 person running: dark skin tone -🏃‍♂️ man running -🏃‍♂ man running -🏃🏻‍♂️ man running: light skin tone -🏃🏻‍♂ man running: light skin tone -🏃🏼‍♂️ man running: medium-light skin tone -🏃🏼‍♂ man running: medium-light skin tone -🏃🏽‍♂️ man running: medium skin tone -🏃🏽‍♂ man running: medium skin tone -🏃🏾‍♂️ man running: medium-dark skin tone -🏃🏾‍♂ man running: medium-dark skin tone -🏃🏿‍♂️ man running: dark skin tone -🏃🏿‍♂ man running: dark skin tone -🏃‍♀️ woman running -🏃‍♀ woman running -🏃🏻‍♀️ woman running: light skin tone -🏃🏻‍♀ woman running: light skin tone -🏃🏼‍♀️ woman running: medium-light skin tone -🏃🏼‍♀ woman running: medium-light skin tone -🏃🏽‍♀️ woman running: medium skin tone -🏃🏽‍♀ woman running: medium skin tone -🏃🏾‍♀️ woman running: medium-dark skin tone -🏃🏾‍♀ woman running: medium-dark skin tone -🏃🏿‍♀️ woman running: dark skin tone -🏃🏿‍♀ woman running: dark skin tone -💃 woman dancing -💃🏻 woman dancing: light skin tone -💃🏼 woman dancing: medium-light skin tone -💃🏽 woman dancing: medium skin tone -💃🏾 woman dancing: medium-dark skin tone -💃🏿 woman dancing: dark skin tone -🕺 man dancing -🕺🏻 man dancing: light skin tone -🕺🏼 man dancing: medium-light skin tone -🕺🏽 man dancing: medium skin tone -🕺🏾 man dancing: medium-dark skin tone -🕺🏿 man dancing: dark skin tone -👯 people with bunny ears -👯‍♂️ men with bunny ears -👯‍♂ men with bunny ears -👯‍♀️ women with bunny ears -👯‍♀ women with bunny ears -🧖 person in steamy room -🧖🏻 person in steamy room: light skin tone -🧖🏼 person in steamy room: medium-light skin tone -🧖🏽 person in steamy room: medium skin tone -🧖🏾 person in steamy room: medium-dark skin tone -🧖🏿 person in steamy room: dark skin tone -🧖‍♀️ woman in steamy room -🧖‍♀ woman in steamy room -🧖🏻‍♀️ woman in steamy room: light skin tone -🧖🏻‍♀ woman in steamy room: light skin tone -🧖🏼‍♀️ woman in steamy room: medium-light skin tone -🧖🏼‍♀ woman in steamy room: medium-light skin tone -🧖🏽‍♀️ woman in steamy room: medium skin tone -🧖🏽‍♀ woman in steamy room: medium skin tone -🧖🏾‍♀️ woman in steamy room: medium-dark skin tone -🧖🏾‍♀ woman in steamy room: medium-dark skin tone -🧖🏿‍♀️ woman in steamy room: dark skin tone -🧖🏿‍♀ woman in steamy room: dark skin tone -🧖‍♂️ man in steamy room -🧖‍♂ man in steamy room -🧖🏻‍♂️ man in steamy room: light skin tone -🧖🏻‍♂ man in steamy room: light skin tone -🧖🏼‍♂️ man in steamy room: medium-light skin tone -🧖🏼‍♂ man in steamy room: medium-light skin tone -🧖🏽‍♂️ man in steamy room: medium skin tone -🧖🏽‍♂ man in steamy room: medium skin tone -🧖🏾‍♂️ man in steamy room: medium-dark skin tone -🧖🏾‍♂ man in steamy room: medium-dark skin tone -🧖🏿‍♂️ man in steamy room: dark skin tone -🧖🏿‍♂ man in steamy room: dark skin tone -🧗 person climbing -🧗🏻 person climbing: light skin tone -🧗🏼 person climbing: medium-light skin tone -🧗🏽 person climbing: medium skin tone -🧗🏾 person climbing: medium-dark skin tone -🧗🏿 person climbing: dark skin tone -🧗‍♀️ woman climbing -🧗‍♀ woman climbing -🧗🏻‍♀️ woman climbing: light skin tone -🧗🏻‍♀ woman climbing: light skin tone -🧗🏼‍♀️ woman climbing: medium-light skin tone -🧗🏼‍♀ woman climbing: medium-light skin tone -🧗🏽‍♀️ woman climbing: medium skin tone -🧗🏽‍♀ woman climbing: medium skin tone -🧗🏾‍♀️ woman climbing: medium-dark skin tone -🧗🏾‍♀ woman climbing: medium-dark skin tone -🧗🏿‍♀️ woman climbing: dark skin tone -🧗🏿‍♀ woman climbing: dark skin tone -🧗‍♂️ man climbing -🧗‍♂ man climbing -🧗🏻‍♂️ man climbing: light skin tone -🧗🏻‍♂ man climbing: light skin tone -🧗🏼‍♂️ man climbing: medium-light skin tone -🧗🏼‍♂ man climbing: medium-light skin tone -🧗🏽‍♂️ man climbing: medium skin tone -🧗🏽‍♂ man climbing: medium skin tone -🧗🏾‍♂️ man climbing: medium-dark skin tone -🧗🏾‍♂ man climbing: medium-dark skin tone -🧗🏿‍♂️ man climbing: dark skin tone -🧗🏿‍♂ man climbing: dark skin tone -🧘 person in lotus position -🧘🏻 person in lotus position: light skin tone -🧘🏼 person in lotus position: medium-light skin tone -🧘🏽 person in lotus position: medium skin tone -🧘🏾 person in lotus position: medium-dark skin tone -🧘🏿 person in lotus position: dark skin tone -🧘‍♀️ woman in lotus position -🧘‍♀ woman in lotus position -🧘🏻‍♀️ woman in lotus position: light skin tone -🧘🏻‍♀ woman in lotus position: light skin tone -🧘🏼‍♀️ woman in lotus position: medium-light skin tone -🧘🏼‍♀ woman in lotus position: medium-light skin tone -🧘🏽‍♀️ woman in lotus position: medium skin tone -🧘🏽‍♀ woman in lotus position: medium skin tone -🧘🏾‍♀️ woman in lotus position: medium-dark skin tone -🧘🏾‍♀ woman in lotus position: medium-dark skin tone -🧘🏿‍♀️ woman in lotus position: dark skin tone -🧘🏿‍♀ woman in lotus position: dark skin tone -🧘‍♂️ man in lotus position -🧘‍♂ man in lotus position -🧘🏻‍♂️ man in lotus position: light skin tone -🧘🏻‍♂ man in lotus position: light skin tone -🧘🏼‍♂️ man in lotus position: medium-light skin tone -🧘🏼‍♂ man in lotus position: medium-light skin tone -🧘🏽‍♂️ man in lotus position: medium skin tone -🧘🏽‍♂ man in lotus position: medium skin tone -🧘🏾‍♂️ man in lotus position: medium-dark skin tone -🧘🏾‍♂ man in lotus position: medium-dark skin tone -🧘🏿‍♂️ man in lotus position: dark skin tone -🧘🏿‍♂ man in lotus position: dark skin tone -🛀 person taking bath -🛀🏻 person taking bath: light skin tone -🛀🏼 person taking bath: medium-light skin tone -🛀🏽 person taking bath: medium skin tone -🛀🏾 person taking bath: medium-dark skin tone -🛀🏿 person taking bath: dark skin tone -🛌 person in bed -🛌🏻 person in bed: light skin tone -🛌🏼 person in bed: medium-light skin tone -🛌🏽 person in bed: medium skin tone -🛌🏾 person in bed: medium-dark skin tone -🛌🏿 person in bed: dark skin tone -🕴️ man in suit levitating -🕴 man in suit levitating -🕴🏻 man in suit levitating: light skin tone -🕴🏼 man in suit levitating: medium-light skin tone -🕴🏽 man in suit levitating: medium skin tone -🕴🏾 man in suit levitating: medium-dark skin tone -🕴🏿 man in suit levitating: dark skin tone -🗣️ speaking head -🗣 speaking head -👤 bust in silhouette -👥 busts in silhouette -🤺 person fencing -🏇 horse racing -🏇🏻 horse racing: light skin tone -🏇🏼 horse racing: medium-light skin tone -🏇🏽 horse racing: medium skin tone -🏇🏾 horse racing: medium-dark skin tone -🏇🏿 horse racing: dark skin tone -⛷️ skier -⛷ skier -🏂 snowboarder -🏂🏻 snowboarder: light skin tone -🏂🏼 snowboarder: medium-light skin tone -🏂🏽 snowboarder: medium skin tone -🏂🏾 snowboarder: medium-dark skin tone -🏂🏿 snowboarder: dark skin tone -🏌️ person golfing -🏌 person golfing -🏌🏻 person golfing: light skin tone -🏌🏼 person golfing: medium-light skin tone -🏌🏽 person golfing: medium skin tone -🏌🏾 person golfing: medium-dark skin tone -🏌🏿 person golfing: dark skin tone -🏌️‍♂️ man golfing -🏌‍♂️ man golfing -🏌️‍♂ man golfing -🏌‍♂ man golfing -🏌🏻‍♂️ man golfing: light skin tone -🏌🏻‍♂ man golfing: light skin tone -🏌🏼‍♂️ man golfing: medium-light skin tone -🏌🏼‍♂ man golfing: medium-light skin tone -🏌🏽‍♂️ man golfing: medium skin tone -🏌🏽‍♂ man golfing: medium skin tone -🏌🏾‍♂️ man golfing: medium-dark skin tone -🏌🏾‍♂ man golfing: medium-dark skin tone -🏌🏿‍♂️ man golfing: dark skin tone -🏌🏿‍♂ man golfing: dark skin tone -🏌️‍♀️ woman golfing -🏌‍♀️ woman golfing -🏌️‍♀ woman golfing -🏌‍♀ woman golfing -🏌🏻‍♀️ woman golfing: light skin tone -🏌🏻‍♀ woman golfing: light skin tone -🏌🏼‍♀️ woman golfing: medium-light skin tone -🏌🏼‍♀ woman golfing: medium-light skin tone -🏌🏽‍♀️ woman golfing: medium skin tone -🏌🏽‍♀ woman golfing: medium skin tone -🏌🏾‍♀️ woman golfing: medium-dark skin tone -🏌🏾‍♀ woman golfing: medium-dark skin tone -🏌🏿‍♀️ woman golfing: dark skin tone -🏌🏿‍♀ woman golfing: dark skin tone -🏄 person surfing -🏄🏻 person surfing: light skin tone -🏄🏼 person surfing: medium-light skin tone -🏄🏽 person surfing: medium skin tone -🏄🏾 person surfing: medium-dark skin tone -🏄🏿 person surfing: dark skin tone -🏄‍♂️ man surfing -🏄‍♂ man surfing -🏄🏻‍♂️ man surfing: light skin tone -🏄🏻‍♂ man surfing: light skin tone -🏄🏼‍♂️ man surfing: medium-light skin tone -🏄🏼‍♂ man surfing: medium-light skin tone -🏄🏽‍♂️ man surfing: medium skin tone -🏄🏽‍♂ man surfing: medium skin tone -🏄🏾‍♂️ man surfing: medium-dark skin tone -🏄🏾‍♂ man surfing: medium-dark skin tone -🏄🏿‍♂️ man surfing: dark skin tone -🏄🏿‍♂ man surfing: dark skin tone -🏄‍♀️ woman surfing -🏄‍♀ woman surfing -🏄🏻‍♀️ woman surfing: light skin tone -🏄🏻‍♀ woman surfing: light skin tone -🏄🏼‍♀️ woman surfing: medium-light skin tone -🏄🏼‍♀ woman surfing: medium-light skin tone -🏄🏽‍♀️ woman surfing: medium skin tone -🏄🏽‍♀ woman surfing: medium skin tone -🏄🏾‍♀️ woman surfing: medium-dark skin tone -🏄🏾‍♀ woman surfing: medium-dark skin tone -🏄🏿‍♀️ woman surfing: dark skin tone -🏄🏿‍♀ woman surfing: dark skin tone -🚣 person rowing boat -🚣🏻 person rowing boat: light skin tone -🚣🏼 person rowing boat: medium-light skin tone -🚣🏽 person rowing boat: medium skin tone -🚣🏾 person rowing boat: medium-dark skin tone -🚣🏿 person rowing boat: dark skin tone -🚣‍♂️ man rowing boat -🚣‍♂ man rowing boat -🚣🏻‍♂️ man rowing boat: light skin tone -🚣🏻‍♂ man rowing boat: light skin tone -🚣🏼‍♂️ man rowing boat: medium-light skin tone -🚣🏼‍♂ man rowing boat: medium-light skin tone -🚣🏽‍♂️ man rowing boat: medium skin tone -🚣🏽‍♂ man rowing boat: medium skin tone -🚣🏾‍♂️ man rowing boat: medium-dark skin tone -🚣🏾‍♂ man rowing boat: medium-dark skin tone -🚣🏿‍♂️ man rowing boat: dark skin tone -🚣🏿‍♂ man rowing boat: dark skin tone -🚣‍♀️ woman rowing boat -🚣‍♀ woman rowing boat -🚣🏻‍♀️ woman rowing boat: light skin tone -🚣🏻‍♀ woman rowing boat: light skin tone -🚣🏼‍♀️ woman rowing boat: medium-light skin tone -🚣🏼‍♀ woman rowing boat: medium-light skin tone -🚣🏽‍♀️ woman rowing boat: medium skin tone -🚣🏽‍♀ woman rowing boat: medium skin tone -🚣🏾‍♀️ woman rowing boat: medium-dark skin tone -🚣🏾‍♀ woman rowing boat: medium-dark skin tone -🚣🏿‍♀️ woman rowing boat: dark skin tone -🚣🏿‍♀ woman rowing boat: dark skin tone -🏊 person swimming -🏊🏻 person swimming: light skin tone -🏊🏼 person swimming: medium-light skin tone -🏊🏽 person swimming: medium skin tone -🏊🏾 person swimming: medium-dark skin tone -🏊🏿 person swimming: dark skin tone -🏊‍♂️ man swimming -🏊‍♂ man swimming -🏊🏻‍♂️ man swimming: light skin tone -🏊🏻‍♂ man swimming: light skin tone -🏊🏼‍♂️ man swimming: medium-light skin tone -🏊🏼‍♂ man swimming: medium-light skin tone -🏊🏽‍♂️ man swimming: medium skin tone -🏊🏽‍♂ man swimming: medium skin tone -🏊🏾‍♂️ man swimming: medium-dark skin tone -🏊🏾‍♂ man swimming: medium-dark skin tone -🏊🏿‍♂️ man swimming: dark skin tone -🏊🏿‍♂ man swimming: dark skin tone -🏊‍♀️ woman swimming -🏊‍♀ woman swimming -🏊🏻‍♀️ woman swimming: light skin tone -🏊🏻‍♀ woman swimming: light skin tone -🏊🏼‍♀️ woman swimming: medium-light skin tone -🏊🏼‍♀ woman swimming: medium-light skin tone -🏊🏽‍♀️ woman swimming: medium skin tone -🏊🏽‍♀ woman swimming: medium skin tone -🏊🏾‍♀️ woman swimming: medium-dark skin tone -🏊🏾‍♀ woman swimming: medium-dark skin tone -🏊🏿‍♀️ woman swimming: dark skin tone -🏊🏿‍♀ woman swimming: dark skin tone -⛹️ person bouncing ball -⛹ person bouncing ball -⛹🏻 person bouncing ball: light skin tone -⛹🏼 person bouncing ball: medium-light skin tone -⛹🏽 person bouncing ball: medium skin tone -⛹🏾 person bouncing ball: medium-dark skin tone -⛹🏿 person bouncing ball: dark skin tone -⛹️‍♂️ man bouncing ball -⛹‍♂️ man bouncing ball -⛹️‍♂ man bouncing ball -⛹‍♂ man bouncing ball -⛹🏻‍♂️ man bouncing ball: light skin tone -⛹🏻‍♂ man bouncing ball: light skin tone -⛹🏼‍♂️ man bouncing ball: medium-light skin tone -⛹🏼‍♂ man bouncing ball: medium-light skin tone -⛹🏽‍♂️ man bouncing ball: medium skin tone -⛹🏽‍♂ man bouncing ball: medium skin tone -⛹🏾‍♂️ man bouncing ball: medium-dark skin tone -⛹🏾‍♂ man bouncing ball: medium-dark skin tone -⛹🏿‍♂️ man bouncing ball: dark skin tone -⛹🏿‍♂ man bouncing ball: dark skin tone -⛹️‍♀️ woman bouncing ball -⛹‍♀️ woman bouncing ball -⛹️‍♀ woman bouncing ball -⛹‍♀ woman bouncing ball -⛹🏻‍♀️ woman bouncing ball: light skin tone -⛹🏻‍♀ woman bouncing ball: light skin tone -⛹🏼‍♀️ woman bouncing ball: medium-light skin tone -⛹🏼‍♀ woman bouncing ball: medium-light skin tone -⛹🏽‍♀️ woman bouncing ball: medium skin tone -⛹🏽‍♀ woman bouncing ball: medium skin tone -⛹🏾‍♀️ woman bouncing ball: medium-dark skin tone -⛹🏾‍♀ woman bouncing ball: medium-dark skin tone -⛹🏿‍♀️ woman bouncing ball: dark skin tone -⛹🏿‍♀ woman bouncing ball: dark skin tone -🏋️ person lifting weights -🏋 person lifting weights -🏋🏻 person lifting weights: light skin tone -🏋🏼 person lifting weights: medium-light skin tone -🏋🏽 person lifting weights: medium skin tone -🏋🏾 person lifting weights: medium-dark skin tone -🏋🏿 person lifting weights: dark skin tone -🏋️‍♂️ man lifting weights -🏋‍♂️ man lifting weights -🏋️‍♂ man lifting weights -🏋‍♂ man lifting weights -🏋🏻‍♂️ man lifting weights: light skin tone -🏋🏻‍♂ man lifting weights: light skin tone -🏋🏼‍♂️ man lifting weights: medium-light skin tone -🏋🏼‍♂ man lifting weights: medium-light skin tone -🏋🏽‍♂️ man lifting weights: medium skin tone -🏋🏽‍♂ man lifting weights: medium skin tone -🏋🏾‍♂️ man lifting weights: medium-dark skin tone -🏋🏾‍♂ man lifting weights: medium-dark skin tone -🏋🏿‍♂️ man lifting weights: dark skin tone -🏋🏿‍♂ man lifting weights: dark skin tone -🏋️‍♀️ woman lifting weights -🏋‍♀️ woman lifting weights -🏋️‍♀ woman lifting weights -🏋‍♀ woman lifting weights -🏋🏻‍♀️ woman lifting weights: light skin tone -🏋🏻‍♀ woman lifting weights: light skin tone -🏋🏼‍♀️ woman lifting weights: medium-light skin tone -🏋🏼‍♀ woman lifting weights: medium-light skin tone -🏋🏽‍♀️ woman lifting weights: medium skin tone -🏋🏽‍♀ woman lifting weights: medium skin tone -🏋🏾‍♀️ woman lifting weights: medium-dark skin tone -🏋🏾‍♀ woman lifting weights: medium-dark skin tone -🏋🏿‍♀️ woman lifting weights: dark skin tone -🏋🏿‍♀ woman lifting weights: dark skin tone -🚴 person biking -🚴🏻 person biking: light skin tone -🚴🏼 person biking: medium-light skin tone -🚴🏽 person biking: medium skin tone -🚴🏾 person biking: medium-dark skin tone -🚴🏿 person biking: dark skin tone -🚴‍♂️ man biking -🚴‍♂ man biking -🚴🏻‍♂️ man biking: light skin tone -🚴🏻‍♂ man biking: light skin tone -🚴🏼‍♂️ man biking: medium-light skin tone -🚴🏼‍♂ man biking: medium-light skin tone -🚴🏽‍♂️ man biking: medium skin tone -🚴🏽‍♂ man biking: medium skin tone -🚴🏾‍♂️ man biking: medium-dark skin tone -🚴🏾‍♂ man biking: medium-dark skin tone -🚴🏿‍♂️ man biking: dark skin tone -🚴🏿‍♂ man biking: dark skin tone -🚴‍♀️ woman biking -🚴‍♀ woman biking -🚴🏻‍♀️ woman biking: light skin tone -🚴🏻‍♀ woman biking: light skin tone -🚴🏼‍♀️ woman biking: medium-light skin tone -🚴🏼‍♀ woman biking: medium-light skin tone -🚴🏽‍♀️ woman biking: medium skin tone -🚴🏽‍♀ woman biking: medium skin tone -🚴🏾‍♀️ woman biking: medium-dark skin tone -🚴🏾‍♀ woman biking: medium-dark skin tone -🚴🏿‍♀️ woman biking: dark skin tone -🚴🏿‍♀ woman biking: dark skin tone -🚵 person mountain biking -🚵🏻 person mountain biking: light skin tone -🚵🏼 person mountain biking: medium-light skin tone -🚵🏽 person mountain biking: medium skin tone -🚵🏾 person mountain biking: medium-dark skin tone -🚵🏿 person mountain biking: dark skin tone -🚵‍♂️ man mountain biking -🚵‍♂ man mountain biking -🚵🏻‍♂️ man mountain biking: light skin tone -🚵🏻‍♂ man mountain biking: light skin tone -🚵🏼‍♂️ man mountain biking: medium-light skin tone -🚵🏼‍♂ man mountain biking: medium-light skin tone -🚵🏽‍♂️ man mountain biking: medium skin tone -🚵🏽‍♂ man mountain biking: medium skin tone -🚵🏾‍♂️ man mountain biking: medium-dark skin tone -🚵🏾‍♂ man mountain biking: medium-dark skin tone -🚵🏿‍♂️ man mountain biking: dark skin tone -🚵🏿‍♂ man mountain biking: dark skin tone -🚵‍♀️ woman mountain biking -🚵‍♀ woman mountain biking -🚵🏻‍♀️ woman mountain biking: light skin tone -🚵🏻‍♀ woman mountain biking: light skin tone -🚵🏼‍♀️ woman mountain biking: medium-light skin tone -🚵🏼‍♀ woman mountain biking: medium-light skin tone -🚵🏽‍♀️ woman mountain biking: medium skin tone -🚵🏽‍♀ woman mountain biking: medium skin tone -🚵🏾‍♀️ woman mountain biking: medium-dark skin tone -🚵🏾‍♀ woman mountain biking: medium-dark skin tone -🚵🏿‍♀️ woman mountain biking: dark skin tone -🚵🏿‍♀ woman mountain biking: dark skin tone -🏎️ racing car -🏎 racing car -🏍️ motorcycle -🏍 motorcycle -🤸 person cartwheeling -🤸🏻 person cartwheeling: light skin tone -🤸🏼 person cartwheeling: medium-light skin tone -🤸🏽 person cartwheeling: medium skin tone -🤸🏾 person cartwheeling: medium-dark skin tone -🤸🏿 person cartwheeling: dark skin tone -🤸‍♂️ man cartwheeling -🤸‍♂ man cartwheeling -🤸🏻‍♂️ man cartwheeling: light skin tone -🤸🏻‍♂ man cartwheeling: light skin tone -🤸🏼‍♂️ man cartwheeling: medium-light skin tone -🤸🏼‍♂ man cartwheeling: medium-light skin tone -🤸🏽‍♂️ man cartwheeling: medium skin tone -🤸🏽‍♂ man cartwheeling: medium skin tone -🤸🏾‍♂️ man cartwheeling: medium-dark skin tone -🤸🏾‍♂ man cartwheeling: medium-dark skin tone -🤸🏿‍♂️ man cartwheeling: dark skin tone -🤸🏿‍♂ man cartwheeling: dark skin tone -🤸‍♀️ woman cartwheeling -🤸‍♀ woman cartwheeling -🤸🏻‍♀️ woman cartwheeling: light skin tone -🤸🏻‍♀ woman cartwheeling: light skin tone -🤸🏼‍♀️ woman cartwheeling: medium-light skin tone -🤸🏼‍♀ woman cartwheeling: medium-light skin tone -🤸🏽‍♀️ woman cartwheeling: medium skin tone -🤸🏽‍♀ woman cartwheeling: medium skin tone -🤸🏾‍♀️ woman cartwheeling: medium-dark skin tone -🤸🏾‍♀ woman cartwheeling: medium-dark skin tone -🤸🏿‍♀️ woman cartwheeling: dark skin tone -🤸🏿‍♀ woman cartwheeling: dark skin tone -🤼 people wrestling -🤼‍♂️ men wrestling -🤼‍♂ men wrestling -🤼‍♀️ women wrestling -🤼‍♀ women wrestling -🤽 person playing water polo -🤽🏻 person playing water polo: light skin tone -🤽🏼 person playing water polo: medium-light skin tone -🤽🏽 person playing water polo: medium skin tone -🤽🏾 person playing water polo: medium-dark skin tone -🤽🏿 person playing water polo: dark skin tone -🤽‍♂️ man playing water polo -🤽‍♂ man playing water polo -🤽🏻‍♂️ man playing water polo: light skin tone -🤽🏻‍♂ man playing water polo: light skin tone -🤽🏼‍♂️ man playing water polo: medium-light skin tone -🤽🏼‍♂ man playing water polo: medium-light skin tone -🤽🏽‍♂️ man playing water polo: medium skin tone -🤽🏽‍♂ man playing water polo: medium skin tone -🤽🏾‍♂️ man playing water polo: medium-dark skin tone -🤽🏾‍♂ man playing water polo: medium-dark skin tone -🤽🏿‍♂️ man playing water polo: dark skin tone -🤽🏿‍♂ man playing water polo: dark skin tone -🤽‍♀️ woman playing water polo -🤽‍♀ woman playing water polo -🤽🏻‍♀️ woman playing water polo: light skin tone -🤽🏻‍♀ woman playing water polo: light skin tone -🤽🏼‍♀️ woman playing water polo: medium-light skin tone -🤽🏼‍♀ woman playing water polo: medium-light skin tone -🤽🏽‍♀️ woman playing water polo: medium skin tone -🤽🏽‍♀ woman playing water polo: medium skin tone -🤽🏾‍♀️ woman playing water polo: medium-dark skin tone -🤽🏾‍♀ woman playing water polo: medium-dark skin tone -🤽🏿‍♀️ woman playing water polo: dark skin tone -🤽🏿‍♀ woman playing water polo: dark skin tone -🤾 person playing handball -🤾🏻 person playing handball: light skin tone -🤾🏼 person playing handball: medium-light skin tone -🤾🏽 person playing handball: medium skin tone -🤾🏾 person playing handball: medium-dark skin tone -🤾🏿 person playing handball: dark skin tone -🤾‍♂️ man playing handball -🤾‍♂ man playing handball -🤾🏻‍♂️ man playing handball: light skin tone -🤾🏻‍♂ man playing handball: light skin tone -🤾🏼‍♂️ man playing handball: medium-light skin tone -🤾🏼‍♂ man playing handball: medium-light skin tone -🤾🏽‍♂️ man playing handball: medium skin tone -🤾🏽‍♂ man playing handball: medium skin tone -🤾🏾‍♂️ man playing handball: medium-dark skin tone -🤾🏾‍♂ man playing handball: medium-dark skin tone -🤾🏿‍♂️ man playing handball: dark skin tone -🤾🏿‍♂ man playing handball: dark skin tone -🤾‍♀️ woman playing handball -🤾‍♀ woman playing handball -🤾🏻‍♀️ woman playing handball: light skin tone -🤾🏻‍♀ woman playing handball: light skin tone -🤾🏼‍♀️ woman playing handball: medium-light skin tone -🤾🏼‍♀ woman playing handball: medium-light skin tone -🤾🏽‍♀️ woman playing handball: medium skin tone -🤾🏽‍♀ woman playing handball: medium skin tone -🤾🏾‍♀️ woman playing handball: medium-dark skin tone -🤾🏾‍♀ woman playing handball: medium-dark skin tone -🤾🏿‍♀️ woman playing handball: dark skin tone -🤾🏿‍♀ woman playing handball: dark skin tone -🤹 person juggling -🤹🏻 person juggling: light skin tone -🤹🏼 person juggling: medium-light skin tone -🤹🏽 person juggling: medium skin tone -🤹🏾 person juggling: medium-dark skin tone -🤹🏿 person juggling: dark skin tone -🤹‍♂️ man juggling -🤹‍♂ man juggling -🤹🏻‍♂️ man juggling: light skin tone -🤹🏻‍♂ man juggling: light skin tone -🤹🏼‍♂️ man juggling: medium-light skin tone -🤹🏼‍♂ man juggling: medium-light skin tone -🤹🏽‍♂️ man juggling: medium skin tone -🤹🏽‍♂ man juggling: medium skin tone -🤹🏾‍♂️ man juggling: medium-dark skin tone -🤹🏾‍♂ man juggling: medium-dark skin tone -🤹🏿‍♂️ man juggling: dark skin tone -🤹🏿‍♂ man juggling: dark skin tone -🤹‍♀️ woman juggling -🤹‍♀ woman juggling -🤹🏻‍♀️ woman juggling: light skin tone -🤹🏻‍♀ woman juggling: light skin tone -🤹🏼‍♀️ woman juggling: medium-light skin tone -🤹🏼‍♀ woman juggling: medium-light skin tone -🤹🏽‍♀️ woman juggling: medium skin tone -🤹🏽‍♀ woman juggling: medium skin tone -🤹🏾‍♀️ woman juggling: medium-dark skin tone -🤹🏾‍♀ woman juggling: medium-dark skin tone -🤹🏿‍♀️ woman juggling: dark skin tone -🤹🏿‍♀ woman juggling: dark skin tone -👫 man and woman holding hands -👬 two men holding hands -👭 two women holding hands -💏 kiss -👩‍❤️‍💋‍👨 kiss: woman, man -👩‍❤‍💋‍👨 kiss: woman, man -👨‍❤️‍💋‍👨 kiss: man, man -👨‍❤‍💋‍👨 kiss: man, man -👩‍❤️‍💋‍👩 kiss: woman, woman -👩‍❤‍💋‍👩 kiss: woman, woman -💑 couple with heart -👩‍❤️‍👨 couple with heart: woman, man -👩‍❤‍👨 couple with heart: woman, man -👨‍❤️‍👨 couple with heart: man, man -👨‍❤‍👨 couple with heart: man, man -👩‍❤️‍👩 couple with heart: woman, woman -👩‍❤‍👩 couple with heart: woman, woman -👪 family -👨‍👩‍👦 family: man, woman, boy -👨‍👩‍👧 family: man, woman, girl -👨‍👩‍👧‍👦 family: man, woman, girl, boy -👨‍👩‍👦‍👦 family: man, woman, boy, boy -👨‍👩‍👧‍👧 family: man, woman, girl, girl -👨‍👨‍👦 family: man, man, boy -👨‍👨‍👧 family: man, man, girl -👨‍👨‍👧‍👦 family: man, man, girl, boy -👨‍👨‍👦‍👦 family: man, man, boy, boy -👨‍👨‍👧‍👧 family: man, man, girl, girl -👩‍👩‍👦 family: woman, woman, boy -👩‍👩‍👧 family: woman, woman, girl -👩‍👩‍👧‍👦 family: woman, woman, girl, boy -👩‍👩‍👦‍👦 family: woman, woman, boy, boy -👩‍👩‍👧‍👧 family: woman, woman, girl, girl -👨‍👦 family: man, boy -👨‍👦‍👦 family: man, boy, boy -👨‍👧 family: man, girl -👨‍👧‍👦 family: man, girl, boy -👨‍👧‍👧 family: man, girl, girl -👩‍👦 family: woman, boy -👩‍👦‍👦 family: woman, boy, boy -👩‍👧 family: woman, girl -👩‍👧‍👦 family: woman, girl, boy -👩‍👧‍👧 family: woman, girl, girl -🤳 selfie -🤳🏻 selfie: light skin tone -🤳🏼 selfie: medium-light skin tone -🤳🏽 selfie: medium skin tone -🤳🏾 selfie: medium-dark skin tone -🤳🏿 selfie: dark skin tone -💪 flexed biceps -💪🏻 flexed biceps: light skin tone -💪🏼 flexed biceps: medium-light skin tone -💪🏽 flexed biceps: medium skin tone -💪🏾 flexed biceps: medium-dark skin tone -💪🏿 flexed biceps: dark skin tone -🦵 leg -🦵🏻 leg: light skin tone -🦵🏼 leg: medium-light skin tone -🦵🏽 leg: medium skin tone -🦵🏾 leg: medium-dark skin tone -🦵🏿 leg: dark skin tone -🦶 foot -🦶🏻 foot: light skin tone -🦶🏼 foot: medium-light skin tone -🦶🏽 foot: medium skin tone -🦶🏾 foot: medium-dark skin tone -🦶🏿 foot: dark skin tone -👈 backhand index pointing left -👈🏻 backhand index pointing left: light skin tone -👈🏼 backhand index pointing left: medium-light skin tone -👈🏽 backhand index pointing left: medium skin tone -👈🏾 backhand index pointing left: medium-dark skin tone -👈🏿 backhand index pointing left: dark skin tone -👉 backhand index pointing right -👉🏻 backhand index pointing right: light skin tone -👉🏼 backhand index pointing right: medium-light skin tone -👉🏽 backhand index pointing right: medium skin tone -👉🏾 backhand index pointing right: medium-dark skin tone -👉🏿 backhand index pointing right: dark skin tone -☝️ index pointing up -☝ index pointing up -☝🏻 index pointing up: light skin tone -☝🏼 index pointing up: medium-light skin tone -☝🏽 index pointing up: medium skin tone -☝🏾 index pointing up: medium-dark skin tone -☝🏿 index pointing up: dark skin tone -👆 backhand index pointing up -👆🏻 backhand index pointing up: light skin tone -👆🏼 backhand index pointing up: medium-light skin tone -👆🏽 backhand index pointing up: medium skin tone -👆🏾 backhand index pointing up: medium-dark skin tone -👆🏿 backhand index pointing up: dark skin tone -🖕 middle finger -🖕🏻 middle finger: light skin tone -🖕🏼 middle finger: medium-light skin tone -🖕🏽 middle finger: medium skin tone -🖕🏾 middle finger: medium-dark skin tone -🖕🏿 middle finger: dark skin tone -👇 backhand index pointing down -👇🏻 backhand index pointing down: light skin tone -👇🏼 backhand index pointing down: medium-light skin tone -👇🏽 backhand index pointing down: medium skin tone -👇🏾 backhand index pointing down: medium-dark skin tone -👇🏿 backhand index pointing down: dark skin tone -✌️ victory hand -✌ victory hand -✌🏻 victory hand: light skin tone -✌🏼 victory hand: medium-light skin tone -✌🏽 victory hand: medium skin tone -✌🏾 victory hand: medium-dark skin tone -✌🏿 victory hand: dark skin tone -🤞 crossed fingers -🤞🏻 crossed fingers: light skin tone -🤞🏼 crossed fingers: medium-light skin tone -🤞🏽 crossed fingers: medium skin tone -🤞🏾 crossed fingers: medium-dark skin tone -🤞🏿 crossed fingers: dark skin tone -🖖 vulcan salute -🖖🏻 vulcan salute: light skin tone -🖖🏼 vulcan salute: medium-light skin tone -🖖🏽 vulcan salute: medium skin tone -🖖🏾 vulcan salute: medium-dark skin tone -🖖🏿 vulcan salute: dark skin tone -🤘 sign of the horns -🤘🏻 sign of the horns: light skin tone -🤘🏼 sign of the horns: medium-light skin tone -🤘🏽 sign of the horns: medium skin tone -🤘🏾 sign of the horns: medium-dark skin tone -🤘🏿 sign of the horns: dark skin tone -🤙 call me hand -🤙🏻 call me hand: light skin tone -🤙🏼 call me hand: medium-light skin tone -🤙🏽 call me hand: medium skin tone -🤙🏾 call me hand: medium-dark skin tone -🤙🏿 call me hand: dark skin tone -🖐️ hand with fingers splayed -🖐 hand with fingers splayed -🖐🏻 hand with fingers splayed: light skin tone -🖐🏼 hand with fingers splayed: medium-light skin tone -🖐🏽 hand with fingers splayed: medium skin tone -🖐🏾 hand with fingers splayed: medium-dark skin tone -🖐🏿 hand with fingers splayed: dark skin tone -✋ raised hand -✋🏻 raised hand: light skin tone -✋🏼 raised hand: medium-light skin tone -✋🏽 raised hand: medium skin tone -✋🏾 raised hand: medium-dark skin tone -✋🏿 raised hand: dark skin tone -👌 OK hand -👌🏻 OK hand: light skin tone -👌🏼 OK hand: medium-light skin tone -👌🏽 OK hand: medium skin tone -👌🏾 OK hand: medium-dark skin tone -👌🏿 OK hand: dark skin tone -👍 thumbs up -👍🏻 thumbs up: light skin tone -👍🏼 thumbs up: medium-light skin tone -👍🏽 thumbs up: medium skin tone -👍🏾 thumbs up: medium-dark skin tone -👍🏿 thumbs up: dark skin tone -👎 thumbs down -👎🏻 thumbs down: light skin tone -👎🏼 thumbs down: medium-light skin tone -👎🏽 thumbs down: medium skin tone -👎🏾 thumbs down: medium-dark skin tone -👎🏿 thumbs down: dark skin tone -✊ raised fist -✊🏻 raised fist: light skin tone -✊🏼 raised fist: medium-light skin tone -✊🏽 raised fist: medium skin tone -✊🏾 raised fist: medium-dark skin tone -✊🏿 raised fist: dark skin tone -👊 oncoming fist -👊🏻 oncoming fist: light skin tone -👊🏼 oncoming fist: medium-light skin tone -👊🏽 oncoming fist: medium skin tone -👊🏾 oncoming fist: medium-dark skin tone -👊🏿 oncoming fist: dark skin tone -🤛 left-facing fist -🤛🏻 left-facing fist: light skin tone -🤛🏼 left-facing fist: medium-light skin tone -🤛🏽 left-facing fist: medium skin tone -🤛🏾 left-facing fist: medium-dark skin tone -🤛🏿 left-facing fist: dark skin tone -🤜 right-facing fist -🤜🏻 right-facing fist: light skin tone -🤜🏼 right-facing fist: medium-light skin tone -🤜🏽 right-facing fist: medium skin tone -🤜🏾 right-facing fist: medium-dark skin tone -🤜🏿 right-facing fist: dark skin tone -🤚 raised back of hand -🤚🏻 raised back of hand: light skin tone -🤚🏼 raised back of hand: medium-light skin tone -🤚🏽 raised back of hand: medium skin tone -🤚🏾 raised back of hand: medium-dark skin tone -🤚🏿 raised back of hand: dark skin tone -👋 waving hand -👋🏻 waving hand: light skin tone -👋🏼 waving hand: medium-light skin tone -👋🏽 waving hand: medium skin tone -👋🏾 waving hand: medium-dark skin tone -👋🏿 waving hand: dark skin tone -🤟 love-you gesture -🤟🏻 love-you gesture: light skin tone -🤟🏼 love-you gesture: medium-light skin tone -🤟🏽 love-you gesture: medium skin tone -🤟🏾 love-you gesture: medium-dark skin tone -🤟🏿 love-you gesture: dark skin tone -✍️ writing hand -✍ writing hand -✍🏻 writing hand: light skin tone -✍🏼 writing hand: medium-light skin tone -✍🏽 writing hand: medium skin tone -✍🏾 writing hand: medium-dark skin tone -✍🏿 writing hand: dark skin tone -👏 clapping hands -👏🏻 clapping hands: light skin tone -👏🏼 clapping hands: medium-light skin tone -👏🏽 clapping hands: medium skin tone -👏🏾 clapping hands: medium-dark skin tone -👏🏿 clapping hands: dark skin tone -👐 open hands -👐🏻 open hands: light skin tone -👐🏼 open hands: medium-light skin tone -👐🏽 open hands: medium skin tone -👐🏾 open hands: medium-dark skin tone -👐🏿 open hands: dark skin tone -🙌 raising hands -🙌🏻 raising hands: light skin tone -🙌🏼 raising hands: medium-light skin tone -🙌🏽 raising hands: medium skin tone -🙌🏾 raising hands: medium-dark skin tone -🙌🏿 raising hands: dark skin tone -🤲 palms up together -🤲🏻 palms up together: light skin tone -🤲🏼 palms up together: medium-light skin tone -🤲🏽 palms up together: medium skin tone -🤲🏾 palms up together: medium-dark skin tone -🤲🏿 palms up together: dark skin tone -🙏 folded hands -🙏🏻 folded hands: light skin tone -🙏🏼 folded hands: medium-light skin tone -🙏🏽 folded hands: medium skin tone -🙏🏾 folded hands: medium-dark skin tone -🙏🏿 folded hands: dark skin tone -🤝 handshake -💅 nail polish -💅🏻 nail polish: light skin tone -💅🏼 nail polish: medium-light skin tone -💅🏽 nail polish: medium skin tone -💅🏾 nail polish: medium-dark skin tone -💅🏿 nail polish: dark skin tone -👂 ear -👂🏻 ear: light skin tone -👂🏼 ear: medium-light skin tone -👂🏽 ear: medium skin tone -👂🏾 ear: medium-dark skin tone -👂🏿 ear: dark skin tone -👃 nose -👃🏻 nose: light skin tone -👃🏼 nose: medium-light skin tone -👃🏽 nose: medium skin tone -👃🏾 nose: medium-dark skin tone -👃🏿 nose: dark skin tone -🦰 red-haired -🦱 curly-haired -🦲 bald -🦳 white-haired -👣 footprints -👀 eyes -👁️ eye -👁 eye -👁️‍🗨️ eye in speech bubble -👁‍🗨️ eye in speech bubble -👁️‍🗨 eye in speech bubble -👁‍🗨 eye in speech bubble -🧠 brain -🦴 bone -🦷 tooth -👅 tongue -👄 mouth -💋 kiss mark -💘 heart with arrow -❤️ red heart -❤ red heart -💓 beating heart -💔 broken heart -💕 two hearts -💖 sparkling heart -💗 growing heart -💙 blue heart -💚 green heart -💛 yellow heart -🧡 orange heart -💜 purple heart -🖤 black heart -💝 heart with ribbon -💞 revolving hearts -💟 heart decoration -❣️ heavy heart exclamation -❣ heavy heart exclamation -💌 love letter -💤 zzz -💢 anger symbol -💣 bomb -💥 collision -💦 sweat droplets -💨 dashing away -💫 dizzy -💬 speech balloon -🗨️ left speech bubble -🗨 left speech bubble -🗯️ right anger bubble -🗯 right anger bubble -💭 thought balloon -🕳️ hole -🕳 hole -👓 glasses -🕶️ sunglasses -🕶 sunglasses -🥽 goggles -🥼 lab coat -👔 necktie -👕 t-shirt -👖 jeans -🧣 scarf -🧤 gloves -🧥 coat -🧦 socks -👗 dress -👘 kimono -👙 bikini -👚 woman’s clothes -👛 purse -👜 handbag -👝 clutch bag -🛍️ shopping bags -🛍 shopping bags -🎒 school backpack -👞 man’s shoe -👟 running shoe -🥾 hiking boot -🥿 woman’s flat shoe -👠 high-heeled shoe -👡 woman’s sandal -👢 woman’s boot -👑 crown -👒 woman’s hat -🎩 top hat -🎓 graduation cap -🧢 billed cap -⛑️ rescue worker’s helmet -⛑ rescue worker’s helmet -📿 prayer beads -💄 lipstick -💍 ring -💎 gem stone -🐵 monkey face -🐒 monkey -🦍 gorilla -🐶 dog face -🐕 dog -🐩 poodle -🐺 wolf face -🦊 fox face -🦝 raccoon -🐱 cat face -🐈 cat -🦁 lion face -🐯 tiger face -🐅 tiger -🐆 leopard -🐴 horse face -🐎 horse -🦄 unicorn face -🦓 zebra -🦌 deer -🐮 cow face -🐂 ox -🐃 water buffalo -🐄 cow -🐷 pig face -🐖 pig -🐗 boar -🐽 pig nose -🐏 ram -🐑 ewe -🐐 goat -🐪 camel -🐫 two-hump camel -🦙 llama -🦒 giraffe -🐘 elephant -🦏 rhinoceros -🦛 hippopotamus -🐭 mouse face -🐁 mouse -🐀 rat -🐹 hamster face -🐰 rabbit face -🐇 rabbit -🐿️ chipmunk -🐿 chipmunk -🦔 hedgehog -🦇 bat -🐻 bear face -🐨 koala -🐼 panda face -🦘 kangaroo -🦡 badger -🐾 paw prints -🦃 turkey -🐔 chicken -🐓 rooster -🐣 hatching chick -🐤 baby chick -🐥 front-facing baby chick -🐦 bird -🐧 penguin -🕊️ dove -🕊 dove -🦅 eagle -🦆 duck -🦢 swan -🦉 owl -🦚 peacock -🦜 parrot -🐸 frog face -🐊 crocodile -🐢 turtle -🦎 lizard -🐍 snake -🐲 dragon face -🐉 dragon -🦕 sauropod -🦖 T-Rex -🐳 spouting whale -🐋 whale -🐬 dolphin -🐟 fish -🐠 tropical fish -🐡 blowfish -🦈 shark -🐙 octopus -🐚 spiral shell -🦀 crab -🦞 lobster -🦐 shrimp -🦑 squid -🐌 snail -🦋 butterfly -🐛 bug -🐜 ant -🐝 honeybee -🐞 lady beetle -🦗 cricket -🕷️ spider -🕷 spider -🕸️ spider web -🕸 spider web -🦂 scorpion -🦟 mosquito -🦠 microbe -💐 bouquet -🌸 cherry blossom -💮 white flower -🏵️ rosette -🏵 rosette -🌹 rose -🥀 wilted flower -🌺 hibiscus -🌻 sunflower -🌼 blossom -🌷 tulip -🌱 seedling -🌲 evergreen tree -🌳 deciduous tree -🌴 palm tree -🌵 cactus -🌾 sheaf of rice -🌿 herb -☘️ shamrock -☘ shamrock -🍀 four leaf clover -🍁 maple leaf -🍂 fallen leaf -🍃 leaf fluttering in wind -🍇 grapes -🍈 melon -🍉 watermelon -🍊 tangerine -🍋 lemon -🍌 banana -🍍 pineapple -🥭 mango -🍎 red apple -🍏 green apple -🍐 pear -🍑 peach -🍒 cherries -🍓 strawberry -🥝 kiwi fruit -🍅 tomato -🥥 coconut -🥑 avocado -🍆 eggplant -🥔 potato -🥕 carrot -🌽 ear of corn -🌶️ hot pepper -🌶 hot pepper -🥒 cucumber -🥬 leafy green -🥦 broccoli -🍄 mushroom -🥜 peanuts -🌰 chestnut -🍞 bread -🥐 croissant -🥖 baguette bread -🥨 pretzel -🥯 bagel -🥞 pancakes -🧀 cheese wedge -🍖 meat on bone -🍗 poultry leg -🥩 cut of meat -🥓 bacon -🍔 hamburger -🍟 french fries -🍕 pizza -🌭 hot dog -🥪 sandwich -🌮 taco -🌯 burrito -🥙 stuffed flatbread -🥚 egg -🍳 cooking -🥘 shallow pan of food -🍲 pot of food -🥣 bowl with spoon -🥗 green salad -🍿 popcorn -🧂 salt -🥫 canned food -🍱 bento box -🍘 rice cracker -🍙 rice ball -🍚 cooked rice -🍛 curry rice -🍜 steaming bowl -🍝 spaghetti -🍠 roasted sweet potato -🍢 oden -🍣 sushi -🍤 fried shrimp -🍥 fish cake with swirl -🥮 moon cake -🍡 dango -🥟 dumpling -🥠 fortune cookie -🥡 takeout box -🍦 soft ice cream -🍧 shaved ice -🍨 ice cream -🍩 doughnut -🍪 cookie -🎂 birthday cake -🍰 shortcake -🧁 cupcake -🥧 pie -🍫 chocolate bar -🍬 candy -🍭 lollipop -🍮 custard -🍯 honey pot -🍼 baby bottle -🥛 glass of milk -☕ hot beverage -🍵 teacup without handle -🍶 sake -🍾 bottle with popping cork -🍷 wine glass -🍸 cocktail glass -🍹 tropical drink -🍺 beer mug -🍻 clinking beer mugs -🥂 clinking glasses -🥃 tumbler glass -🥤 cup with straw -🥢 chopsticks -🍽️ fork and knife with plate -🍽 fork and knife with plate -🍴 fork and knife -🥄 spoon -🔪 kitchen knife -🏺 amphora -🌍 globe showing Europe-Africa -🌎 globe showing Americas -🌏 globe showing Asia-Australia -🌐 globe with meridians -🗺️ world map -🗺 world map -🗾 map of Japan -🧭 compass -🏔️ snow-capped mountain -🏔 snow-capped mountain -⛰️ mountain -⛰ mountain -🌋 volcano -🗻 mount fuji -🏕️ camping -🏕 camping -🏖️ beach with umbrella -🏖 beach with umbrella -🏜️ desert -🏜 desert -🏝️ desert island -🏝 desert island -🏞️ national park -🏞 national park -🏟️ stadium -🏟 stadium -🏛️ classical building -🏛 classical building -🏗️ building construction -🏗 building construction -🧱 bricks -🏘️ houses -🏘 houses -🏚️ derelict house -🏚 derelict house -🏠 house -🏡 house with garden -🏢 office building -🏣 Japanese post office -🏤 post office -🏥 hospital -🏦 bank -🏨 hotel -🏩 love hotel -🏪 convenience store -🏫 school -🏬 department store -🏭 factory -🏯 Japanese castle -🏰 castle -💒 wedding -🗼 Tokyo tower -🗽 Statue of Liberty -⛪ church -🕌 mosque -🕍 synagogue -⛩️ shinto shrine -⛩ shinto shrine -🕋 kaaba -⛲ fountain -⛺ tent -🌁 foggy -🌃 night with stars -🏙️ cityscape -🏙 cityscape -🌄 sunrise over mountains -🌅 sunrise -🌆 cityscape at dusk -🌇 sunset -🌉 bridge at night -♨️ hot springs -♨ hot springs -🌌 milky way -🎠 carousel horse -🎡 ferris wheel -🎢 roller coaster -💈 barber pole -🎪 circus tent -🚂 locomotive -🚃 railway car -🚄 high-speed train -🚅 bullet train -🚆 train -🚇 metro -🚈 light rail -🚉 station -🚊 tram -🚝 monorail -🚞 mountain railway -🚋 tram car -🚌 bus -🚍 oncoming bus -🚎 trolleybus -🚐 minibus -🚑 ambulance -🚒 fire engine -🚓 police car -🚔 oncoming police car -🚕 taxi -🚖 oncoming taxi -🚗 automobile -🚘 oncoming automobile -🚙 sport utility vehicle -🚚 delivery truck -🚛 articulated lorry -🚜 tractor -🚲 bicycle -🛴 kick scooter -🛹 skateboard -🛵 motor scooter -🚏 bus stop -🛣️ motorway -🛣 motorway -🛤️ railway track -🛤 railway track -🛢️ oil drum -🛢 oil drum -⛽ fuel pump -🚨 police car light -🚥 horizontal traffic light -🚦 vertical traffic light -🛑 stop sign -🚧 construction -⚓ anchor -⛵ sailboat -🛶 canoe -🚤 speedboat -🛳️ passenger ship -🛳 passenger ship -⛴️ ferry -⛴ ferry -🛥️ motor boat -🛥 motor boat -🚢 ship -✈️ airplane -✈ airplane -🛩️ small airplane -🛩 small airplane -🛫 airplane departure -🛬 airplane arrival -💺 seat -🚁 helicopter -🚟 suspension railway -🚠 mountain cableway -🚡 aerial tramway -🛰️ satellite -🛰 satellite -🚀 rocket -🛸 flying saucer -🛎️ bellhop bell -🛎 bellhop bell -🧳 luggage -⌛ hourglass done -⏳ hourglass not done -⌚ watch -⏰ alarm clock -⏱️ stopwatch -⏱ stopwatch -⏲️ timer clock -⏲ timer clock -🕰️ mantelpiece clock -🕰 mantelpiece clock -🕛 twelve o’clock -🕧 twelve-thirty -🕐 one o’clock -🕜 one-thirty -🕑 two o’clock -🕝 two-thirty -🕒 three o’clock -🕞 three-thirty -🕓 four o’clock -🕟 four-thirty -🕔 five o’clock -🕠 five-thirty -🕕 six o’clock -🕡 six-thirty -🕖 seven o’clock -🕢 seven-thirty -🕗 eight o’clock -🕣 eight-thirty -🕘 nine o’clock -🕤 nine-thirty -🕙 ten o’clock -🕥 ten-thirty -🕚 eleven o’clock -🕦 eleven-thirty -🌑 new moon -🌒 waxing crescent moon -🌓 first quarter moon -🌔 waxing gibbous moon -🌕 full moon -🌖 waning gibbous moon -🌗 last quarter moon -🌘 waning crescent moon -🌙 crescent moon -🌚 new moon face -🌛 first quarter moon face -🌜 last quarter moon face -🌡️ thermometer -🌡 thermometer -☀️ sun -☀ sun -🌝 full moon face -🌞 sun with face -⭐ star -🌟 glowing star -🌠 shooting star -☁️ cloud -☁ cloud -⛅ sun behind cloud -⛈️ cloud with lightning and rain -⛈ cloud with lightning and rain -🌤️ sun behind small cloud -🌤 sun behind small cloud -🌥️ sun behind large cloud -🌥 sun behind large cloud -🌦️ sun behind rain cloud -🌦 sun behind rain cloud -🌧️ cloud with rain -🌧 cloud with rain -🌨️ cloud with snow -🌨 cloud with snow -🌩️ cloud with lightning -🌩 cloud with lightning -🌪️ tornado -🌪 tornado -🌫️ fog -🌫 fog -🌬️ wind face -🌬 wind face -🌀 cyclone -🌈 rainbow -🌂 closed umbrella -☂️ umbrella -☂ umbrella -☔ umbrella with rain drops -⛱️ umbrella on ground -⛱ umbrella on ground -⚡ high voltage -❄️ snowflake -❄ snowflake -☃️ snowman -☃ snowman -⛄ snowman without snow -☄️ comet -☄ comet -🔥 fire -💧 droplet -🌊 water wave -🎃 jack-o-lantern -🎄 Christmas tree -🎆 fireworks -🎇 sparkler -🧨 firecracker -✨ sparkles -🎈 balloon -🎉 party popper -🎊 confetti ball -🎋 tanabata tree -🎍 pine decoration -🎎 Japanese dolls -🎏 carp streamer -🎐 wind chime -🎑 moon viewing ceremony -🧧 red envelope -🎀 ribbon -🎁 wrapped gift -🎗️ reminder ribbon -🎗 reminder ribbon -🎟️ admission tickets -🎟 admission tickets -🎫 ticket -🎖️ military medal -🎖 military medal -🏆 trophy -🏅 sports medal -🥇 1st place medal -🥈 2nd place medal -🥉 3rd place medal -⚽ soccer ball -⚾ baseball -🥎 softball -🏀 basketball -🏐 volleyball -🏈 american football -🏉 rugby football -🎾 tennis -🥏 flying disc -🎳 bowling -🏏 cricket game -🏑 field hockey -🏒 ice hockey -🥍 lacrosse -🏓 ping pong -🏸 badminton -🥊 boxing glove -🥋 martial arts uniform -🥅 goal net -⛳ flag in hole -⛸️ ice skate -⛸ ice skate -🎣 fishing pole -🎽 running shirt -🎿 skis -🛷 sled -🥌 curling stone -🎯 direct hit -🎱 pool 8 ball -🔮 crystal ball -🧿 nazar amulet -🎮 video game -🕹️ joystick -🕹 joystick -🎰 slot machine -🎲 game die -🧩 jigsaw -🧸 teddy bear -♠️ spade suit -♠ spade suit -♥️ heart suit -♥ heart suit -♦️ diamond suit -♦ diamond suit -♣️ club suit -♣ club suit -♟️ chess pawn -♟ chess pawn -🃏 joker -🀄 mahjong red dragon -🎴 flower playing cards -🎭 performing arts -🖼️ framed picture -🖼 framed picture -🎨 artist palette -🧵 thread -🧶 yarn -🔇 muted speaker -🔈 speaker low volume -🔉 speaker medium volume -🔊 speaker high volume -📢 loudspeaker -📣 megaphone -📯 postal horn -🔔 bell -🔕 bell with slash -🎼 musical score -🎵 musical note -🎶 musical notes -🎙️ studio microphone -🎙 studio microphone -🎚️ level slider -🎚 level slider -🎛️ control knobs -🎛 control knobs -🎤 microphone -🎧 headphone -📻 radio -🎷 saxophone -🎸 guitar -🎹 musical keyboard -🎺 trumpet -🎻 violin -🥁 drum -📱 mobile phone -📲 mobile phone with arrow -☎️ telephone -☎ telephone -📞 telephone receiver -📟 pager -📠 fax machine -🔋 battery -🔌 electric plug -💻 laptop computer -🖥️ desktop computer -🖥 desktop computer -🖨️ printer -🖨 printer -⌨️ keyboard -⌨ keyboard -🖱️ computer mouse -🖱 computer mouse -🖲️ trackball -🖲 trackball -💽 computer disk -💾 floppy disk -💿 optical disk -📀 dvd -🧮 abacus -🎥 movie camera -🎞️ film frames -🎞 film frames -📽️ film projector -📽 film projector -🎬 clapper board -📺 television -📷 camera -📸 camera with flash -📹 video camera -📼 videocassette -🔍 magnifying glass tilted left -🔎 magnifying glass tilted right -🕯️ candle -🕯 candle -💡 light bulb -🔦 flashlight -🏮 red paper lantern -📔 notebook with decorative cover -📕 closed book -📖 open book -📗 green book -📘 blue book -📙 orange book -📚 books -📓 notebook -📒 ledger -📃 page with curl -📜 scroll -📄 page facing up -📰 newspaper -🗞️ rolled-up newspaper -🗞 rolled-up newspaper -📑 bookmark tabs -🔖 bookmark -🏷️ label -🏷 label -💰 money bag -💴 yen banknote -💵 dollar banknote -💶 euro banknote -💷 pound banknote -💸 money with wings -💳 credit card -🧾 receipt -💹 chart increasing with yen -💱 currency exchange -💲 heavy dollar sign -✉️ envelope -✉ envelope -📧 e-mail -📨 incoming envelope -📩 envelope with arrow -📤 outbox tray -📥 inbox tray -📦 package -📫 closed mailbox with raised flag -📪 closed mailbox with lowered flag -📬 open mailbox with raised flag -📭 open mailbox with lowered flag -📮 postbox -🗳️ ballot box with ballot -🗳 ballot box with ballot -✏️ pencil -✏ pencil -✒️ black nib -✒ black nib -🖋️ fountain pen -🖋 fountain pen -🖊️ pen -🖊 pen -🖌️ paintbrush -🖌 paintbrush -🖍️ crayon -🖍 crayon -📝 memo -💼 briefcase -📁 file folder -📂 open file folder -🗂️ card index dividers -🗂 card index dividers -📅 calendar -📆 tear-off calendar -🗒️ spiral notepad -🗒 spiral notepad -🗓️ spiral calendar -🗓 spiral calendar -📇 card index -📈 chart increasing -📉 chart decreasing -📊 bar chart -📋 clipboard -📌 pushpin -📍 round pushpin -📎 paperclip -🖇️ linked paperclips -🖇 linked paperclips -📏 straight ruler -📐 triangular ruler -✂️ scissors -✂ scissors -🗃️ card file box -🗃 card file box -🗄️ file cabinet -🗄 file cabinet -🗑️ wastebasket -🗑 wastebasket -🔒 locked -🔓 unlocked -🔏 locked with pen -🔐 locked with key -🔑 key -🗝️ old key -🗝 old key -🔨 hammer -⛏️ pick -⛏ pick -⚒️ hammer and pick -⚒ hammer and pick -🛠️ hammer and wrench -🛠 hammer and wrench -🗡️ dagger -🗡 dagger -⚔️ crossed swords -⚔ crossed swords -🔫 pistol -🏹 bow and arrow -🛡️ shield -🛡 shield -🔧 wrench -🔩 nut and bolt -⚙️ gear -⚙ gear -🗜️ clamp -🗜 clamp -⚖️ balance scale -⚖ balance scale -🔗 link -⛓️ chains -⛓ chains -🧰 toolbox -🧲 magnet -⚗️ alembic -⚗ alembic -🧪 test tube -🧫 petri dish -🧬 dna -🔬 microscope -🔭 telescope -📡 satellite antenna -💉 syringe -💊 pill -🚪 door -🛏️ bed -🛏 bed -🛋️ couch and lamp -🛋 couch and lamp -🚽 toilet -🚿 shower -🛁 bathtub -🧴 lotion bottle -🧷 safety pin -🧹 broom -🧺 basket -🧻 roll of paper -🧼 soap -🧽 sponge -🧯 fire extinguisher -🛒 shopping cart -🚬 cigarette -⚰️ coffin -⚰ coffin -⚱️ funeral urn -⚱ funeral urn -🗿 moai -🏧 ATM sign -🚮 litter in bin sign -🚰 potable water -♿ wheelchair symbol -🚹 men’s room -🚺 women’s room -🚻 restroom -🚼 baby symbol -🚾 water closet -🛂 passport control -🛃 customs -🛄 baggage claim -🛅 left luggage -⚠️ warning -⚠ warning -🚸 children crossing -⛔ no entry -🚫 prohibited -🚳 no bicycles -🚭 no smoking -🚯 no littering -🚱 non-potable water -🚷 no pedestrians -📵 no mobile phones -🔞 no one under eighteen -☢️ radioactive -☢ radioactive -☣️ biohazard -☣ biohazard -⬆️ up arrow -⬆ up arrow -↗️ up-right arrow -↗ up-right arrow -➡️ right arrow -➡ right arrow -↘️ down-right arrow -↘ down-right arrow -⬇️ down arrow -⬇ down arrow -↙️ down-left arrow -↙ down-left arrow -⬅️ left arrow -⬅ left arrow -↖️ up-left arrow -↖ up-left arrow -↕️ up-down arrow -↕ up-down arrow -↔️ left-right arrow -↔ left-right arrow -↩️ right arrow curving left -↩ right arrow curving left -↪️ left arrow curving right -↪ left arrow curving right -⤴️ right arrow curving up -⤴ right arrow curving up -⤵️ right arrow curving down -⤵ right arrow curving down -🔃 clockwise vertical arrows -🔄 counterclockwise arrows button -🔙 BACK arrow -🔚 END arrow -🔛 ON! arrow -🔜 SOON arrow -🔝 TOP arrow -🛐 place of worship -⚛️ atom symbol -⚛ atom symbol -🕉️ om -🕉 om -✡️ star of David -✡ star of David -☸️ wheel of dharma -☸ wheel of dharma -☯️ yin yang -☯ yin yang -✝️ latin cross -✝ latin cross -☦️ orthodox cross -☦ orthodox cross -☪️ star and crescent -☪ star and crescent -☮️ peace symbol -☮ peace symbol -🕎 menorah -🔯 dotted six-pointed star -♈ Aries -♉ Taurus -♊ Gemini -♋ Cancer -♌ Leo -♍ Virgo -♎ Libra -♏ Scorpio -♐ Sagittarius -♑ Capricorn -♒ Aquarius -♓ Pisces -⛎ Ophiuchus -🔀 shuffle tracks button -🔁 repeat button -🔂 repeat single button -▶️ play button -▶ play button -⏩ fast-forward button -⏭️ next track button -⏭ next track button -⏯️ play or pause button -⏯ play or pause button -◀️ reverse button -◀ reverse button -⏪ fast reverse button -⏮️ last track button -⏮ last track button -🔼 upwards button -⏫ fast up button -🔽 downwards button -⏬ fast down button -⏸️ pause button -⏸ pause button -⏹️ stop button -⏹ stop button -⏺️ record button -⏺ record button -⏏️ eject button -⏏ eject button -🎦 cinema -🔅 dim button -🔆 bright button -📶 antenna bars -📳 vibration mode -📴 mobile phone off -♀️ female sign -♀ female sign -♂️ male sign -♂ male sign -⚕️ medical symbol -⚕ medical symbol -♾️ infinity -♾ infinity -♻️ recycling symbol -♻ recycling symbol -⚜️ fleur-de-lis -⚜ fleur-de-lis -🔱 trident emblem -📛 name badge -🔰 Japanese symbol for beginner -⭕ heavy large circle -✅ white heavy check mark -☑️ ballot box with check -☑ ballot box with check -✔️ heavy check mark -✔ heavy check mark -✖️ heavy multiplication x -✖ heavy multiplication x -❌ cross mark -❎ cross mark button -➕ heavy plus sign -➖ heavy minus sign -➗ heavy division sign -➰ curly loop -➿ double curly loop -〽️ part alternation mark -〽 part alternation mark -✳️ eight-spoked asterisk -✳ eight-spoked asterisk -✴️ eight-pointed star -✴ eight-pointed star -❇️ sparkle -❇ sparkle -‼️ double exclamation mark -‼ double exclamation mark -⁉️ exclamation question mark -⁉ exclamation question mark -❓ question mark -❔ white question mark -❕ white exclamation mark -❗ exclamation mark -〰️ wavy dash -〰 wavy dash -©️ copyright -© copyright -®️ registered -® registered -™️ trade mark -™ trade mark -#️⃣ keycap: # -#⃣ keycap: # -*️⃣ keycap: * -*⃣ keycap: * -0️⃣ keycap: 0 -0⃣ keycap: 0 -1️⃣ keycap: 1 -1⃣ keycap: 1 -2️⃣ keycap: 2 -2⃣ keycap: 2 -3️⃣ keycap: 3 -3⃣ keycap: 3 -4️⃣ keycap: 4 -4⃣ keycap: 4 -5️⃣ keycap: 5 -5⃣ keycap: 5 -6️⃣ keycap: 6 -6⃣ keycap: 6 -7️⃣ keycap: 7 -7⃣ keycap: 7 -8️⃣ keycap: 8 -8⃣ keycap: 8 -9️⃣ keycap: 9 -9⃣ keycap: 9 -🔟 keycap: 10 -💯 hundred points -🔠 input latin uppercase -🔡 input latin lowercase -🔢 input numbers -🔣 input symbols -🔤 input latin letters -🅰️ A button (blood type) -🅰 A button (blood type) -🆎 AB button (blood type) -🅱️ B button (blood type) -🅱 B button (blood type) -🆑 CL button -🆒 COOL button -🆓 FREE button -ℹ️ information -ℹ information -🆔 ID button -Ⓜ️ circled M -Ⓜ circled M -🆕 NEW button -🆖 NG button -🅾️ O button (blood type) -🅾 O button (blood type) -🆗 OK button -🅿️ P button -🅿 P button -🆘 SOS button -🆙 UP! button -🆚 VS button -🈁 Japanese “here” button -🈂️ Japanese “service charge” button -🈂 Japanese “service charge” button -🈷️ Japanese “monthly amount” button -🈷 Japanese “monthly amount” button -🈶 Japanese “not free of charge” button -🈯 Japanese “reserved” button -🉐 Japanese “bargain” button -🈹 Japanese “discount” button -🈚 Japanese “free of charge” button -🈲 Japanese “prohibited” button -🉑 Japanese “acceptable” button -🈸 Japanese “application” button -🈴 Japanese “passing grade” button -🈳 Japanese “vacancy” button -㊗️ Japanese “congratulations” button -㊗ Japanese “congratulations” button -㊙️ Japanese “secret” button -㊙ Japanese “secret” button -🈺 Japanese “open for business” button -🈵 Japanese “no vacancy” button -▪️ black small square -▪ black small square -▫️ white small square -▫ white small square -◻️ white medium square -◻ white medium square -◼️ black medium square -◼ black medium square -◽ white medium-small square -◾ black medium-small square -⬛ black large square -⬜ white large square -🔶 large orange diamond -🔷 large blue diamond -🔸 small orange diamond -🔹 small blue diamond -🔺 red triangle pointed up -🔻 red triangle pointed down -💠 diamond with a dot -🔘 radio button -🔲 black square button -🔳 white square button -⚪ white circle -⚫ black circle -🔴 red circle -🔵 blue circle -🏁 chequered flag -🚩 triangular flag -🎌 crossed flags -🏴 black flag -🏳️ white flag -🏳 white flag -🏳️‍🌈 rainbow flag -🏳‍🌈 rainbow flag -🏴‍☠️ pirate flag -🏴‍☠ pirate flag -🇦🇨 Ascension Island -🇦🇩 Andorra -🇦🇪 United Arab Emirates -🇦🇫 Afghanistan -🇦🇬 Antigua & Barbuda -🇦🇮 Anguilla -🇦🇱 Albania -🇦🇲 Armenia -🇦🇴 Angola -🇦🇶 Antarctica -🇦🇷 Argentina -🇦🇸 American Samoa -🇦🇹 Austria -🇦🇺 Australia -🇦🇼 Aruba -🇦🇽 Åland Islands -🇦🇿 Azerbaijan -🇧🇦 Bosnia & Herzegovina -🇧🇧 Barbados -🇧🇩 Bangladesh -🇧🇪 Belgium -🇧🇫 Burkina Faso -🇧🇬 Bulgaria -🇧🇭 Bahrain -🇧🇮 Burundi -🇧🇯 Benin -🇧🇱 St. Barthélemy -🇧🇲 Bermuda -🇧🇳 Brunei -🇧🇴 Bolivia -🇧🇶 Caribbean Netherlands -🇧🇷 Brazil -🇧🇸 Bahamas -🇧🇹 Bhutan -🇧🇻 Bouvet Island -🇧🇼 Botswana -🇧🇾 Belarus -🇧🇿 Belize -🇨🇦 Canada -🇨🇨 Cocos (Keeling) Islands -🇨🇩 Congo - Kinshasa -🇨🇫 Central African Republic -🇨🇬 Congo - Brazzaville -🇨🇭 Switzerland -🇨🇮 Côte d’Ivoire -🇨🇰 Cook Islands -🇨🇱 Chile -🇨🇲 Cameroon -🇨🇳 China -🇨🇴 Colombia -🇨🇵 Clipperton Island -🇨🇷 Costa Rica -🇨🇺 Cuba -🇨🇻 Cape Verde -🇨🇼 Curaçao -🇨🇽 Christmas Island -🇨🇾 Cyprus -🇨🇿 Czechia -🇩🇪 Germany -🇩🇬 Diego Garcia -🇩🇯 Djibouti -🇩🇰 Denmark -🇩🇲 Dominica -🇩🇴 Dominican Republic -🇩🇿 Algeria -🇪🇦 Ceuta & Melilla -🇪🇨 Ecuador -🇪🇪 Estonia -🇪🇬 Egypt -🇪🇭 Western Sahara -🇪🇷 Eritrea -🇪🇸 Spain -🇪🇹 Ethiopia -🇪🇺 European Union -🇫🇮 Finland -🇫🇯 Fiji -🇫🇰 Falkland Islands -🇫🇲 Micronesia -🇫🇴 Faroe Islands -🇫🇷 France -🇬🇦 Gabon -🇬🇧 United Kingdom -🇬🇩 Grenada -🇬🇪 Georgia -🇬🇫 French Guiana -🇬🇬 Guernsey -🇬🇭 Ghana -🇬🇮 Gibraltar -🇬🇱 Greenland -🇬🇲 Gambia -🇬🇳 Guinea -🇬🇵 Guadeloupe -🇬🇶 Equatorial Guinea -🇬🇷 Greece -🇬🇸 South Georgia & South Sandwich Islands -🇬🇹 Guatemala -🇬🇺 Guam -🇬🇼 Guinea-Bissau -🇬🇾 Guyana -🇭🇰 Hong Kong SAR China -🇭🇲 Heard & McDonald Islands -🇭🇳 Honduras -🇭🇷 Croatia -🇭🇹 Haiti -🇭🇺 Hungary -🇮🇨 Canary Islands -🇮🇩 Indonesia -🇮🇪 Ireland -🇮🇱 Israel -🇮🇲 Isle of Man -🇮🇳 India -🇮🇴 British Indian Ocean Territory -🇮🇶 Iraq -🇮🇷 Iran -🇮🇸 Iceland -🇮🇹 Italy -🇯🇪 Jersey -🇯🇲 Jamaica -🇯🇴 Jordan -🇯🇵 Japan -🇰🇪 Kenya -🇰🇬 Kyrgyzstan -🇰🇭 Cambodia -🇰🇮 Kiribati -🇰🇲 Comoros -🇰🇳 St. Kitts & Nevis -🇰🇵 North Korea -🇰🇷 South Korea -🇰🇼 Kuwait -🇰🇾 Cayman Islands -🇰🇿 Kazakhstan -🇱🇦 Laos -🇱🇧 Lebanon -🇱🇨 St. Lucia -🇱🇮 Liechtenstein -🇱🇰 Sri Lanka -🇱🇷 Liberia -🇱🇸 Lesotho -🇱🇹 Lithuania -🇱🇺 Luxembourg -🇱🇻 Latvia -🇱🇾 Libya -🇲🇦 Morocco -🇲🇨 Monaco -🇲🇩 Moldova -🇲🇪 Montenegro -🇲🇫 St. Martin -🇲🇬 Madagascar -🇲🇭 Marshall Islands -🇲🇰 Macedonia -🇲🇱 Mali -🇲🇲 Myanmar (Burma) -🇲🇳 Mongolia -🇲🇴 Macau SAR China -🇲🇵 Northern Mariana Islands -🇲🇶 Martinique -🇲🇷 Mauritania -🇲🇸 Montserrat -🇲🇹 Malta -🇲🇺 Mauritius -🇲🇻 Maldives -🇲🇼 Malawi -🇲🇽 Mexico -🇲🇾 Malaysia -🇲🇿 Mozambique -🇳🇦 Namibia -🇳🇨 New Caledonia -🇳🇪 Niger -🇳🇫 Norfolk Island -🇳🇬 Nigeria -🇳🇮 Nicaragua -🇳🇱 Netherlands -🇳🇴 Norway -🇳🇵 Nepal -🇳🇷 Nauru -🇳🇺 Niue -🇳🇿 New Zealand -🇴🇲 Oman -🇵🇦 Panama -🇵🇪 Peru -🇵🇫 French Polynesia -🇵🇬 Papua New Guinea -🇵🇭 Philippines -🇵🇰 Pakistan -🇵🇱 Poland -🇵🇲 St. Pierre & Miquelon -🇵🇳 Pitcairn Islands -🇵🇷 Puerto Rico -🇵🇸 Palestinian Territories -🇵🇹 Portugal -🇵🇼 Palau -🇵🇾 Paraguay -🇶🇦 Qatar -🇷🇪 Réunion -🇷🇴 Romania -🇷🇸 Serbia -🇷🇺 Russia -🇷🇼 Rwanda -🇸🇦 Saudi Arabia -🇸🇧 Solomon Islands -🇸🇨 Seychelles -🇸🇩 Sudan -🇸🇪 Sweden -🇸🇬 Singapore -🇸🇭 St. Helena -🇸🇮 Slovenia -🇸🇯 Svalbard & Jan Mayen -🇸🇰 Slovakia -🇸🇱 Sierra Leone -🇸🇲 San Marino -🇸🇳 Senegal -🇸🇴 Somalia -🇸🇷 Suriname -🇸🇸 South Sudan -🇸🇹 São Tomé & Príncipe -🇸🇻 El Salvador -🇸🇽 Sint Maarten -🇸🇾 Syria -🇸🇿 Swaziland -🇹🇦 Tristan da Cunha -🇹🇨 Turks & Caicos Islands -🇹🇩 Chad -🇹🇫 French Southern Territories -🇹🇬 Togo -🇹🇭 Thailand -🇹🇯 Tajikistan -🇹🇰 Tokelau -🇹🇱 Timor-Leste -🇹🇲 Turkmenistan -🇹🇳 Tunisia -🇹🇴 Tonga -🇹🇷 Turkey -🇹🇹 Trinidad & Tobago -🇹🇻 Tuvalu -🇹🇼 Taiwan -🇹🇿 Tanzania -🇺🇦 Ukraine -🇺🇬 Uganda -🇺🇲 U.S. Outlying Islands -🇺🇳 United Nations -🇺🇸 United States -🇺🇾 Uruguay -🇺🇿 Uzbekistan -🇻🇦 Vatican City -🇻🇨 St. Vincent & Grenadines -🇻🇪 Venezuela -🇻🇬 British Virgin Islands -🇻🇮 U.S. Virgin Islands -🇻🇳 Vietnam -🇻🇺 Vanuatu -🇼🇫 Wallis & Futuna -🇼🇸 Samoa -🇽🇰 Kosovo -🇾🇪 Yemen -🇾🇹 Mayotte -🇿🇦 South Africa -🇿🇲 Zambia -🇿🇼 Zimbabwe -🏴󠁧󠁢󠁥󠁮󠁧󠁿 England -🏴󠁧󠁢󠁳󠁣󠁴󠁿 Scotland -🏴󠁧󠁢󠁷󠁬󠁳󠁿 Wales \ No newline at end of file diff --git a/build/pyinstaller/vaderSentiment/vaderSentiment.py b/build/pyinstaller/vaderSentiment/vaderSentiment.py deleted file mode 100644 index b2c722c68a6..00000000000 --- a/build/pyinstaller/vaderSentiment/vaderSentiment.py +++ /dev/null @@ -1,687 +0,0 @@ -# coding: utf-8 -# Author: C.J. Hutto -# Thanks to George Berry for reducing the time complexity from something like O(N^4) to O(N). -# Thanks to Ewan Klein and Pierpaolo Pantone for bringing VADER into NLTK. Those modifications were awesome. -# For license information, see LICENSE.TXT - -""" -If you use the VADER sentiment analysis tools, please cite: -Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for -Sentiment Analysis of Social Media Text. Eighth International Conference on -Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014. -""" -import os -import re -import math -import string -import codecs -import json -from itertools import product -from inspect import getsourcefile -from io import open - -# ##Constants## - -# (empirically derived mean sentiment intensity rating increase for booster words) -B_INCR = 0.293 -B_DECR = -0.293 - -# (empirically derived mean sentiment intensity rating increase for using ALLCAPs to emphasize a word) -C_INCR = 0.733 -N_SCALAR = -0.74 - -NEGATE = \ - ["aint", "arent", "cannot", "cant", "couldnt", "darent", "didnt", "doesnt", - "ain't", "aren't", "can't", "couldn't", "daren't", "didn't", "doesn't", - "dont", "hadnt", "hasnt", "havent", "isnt", "mightnt", "mustnt", "neither", - "don't", "hadn't", "hasn't", "haven't", "isn't", "mightn't", "mustn't", - "neednt", "needn't", "never", "none", "nope", "nor", "not", "nothing", "nowhere", - "oughtnt", "shant", "shouldnt", "uhuh", "wasnt", "werent", - "oughtn't", "shan't", "shouldn't", "uh-uh", "wasn't", "weren't", - "without", "wont", "wouldnt", "won't", "wouldn't", "rarely", "seldom", "despite"] - -# booster/dampener 'intensifiers' or 'degree adverbs' -# http://en.wiktionary.org/wiki/Category:English_degree_adverbs - -BOOSTER_DICT = \ - {"absolutely": B_INCR, "amazingly": B_INCR, "awfully": B_INCR, - "completely": B_INCR, "considerable": B_INCR, "considerably": B_INCR, - "decidedly": B_INCR, "deeply": B_INCR, "effing": B_INCR, "enormous": B_INCR, "enormously": B_INCR, - "entirely": B_INCR, "especially": B_INCR, "exceptional": B_INCR, "exceptionally": B_INCR, - "extreme": B_INCR, "extremely": B_INCR, - "fabulously": B_INCR, "flipping": B_INCR, "flippin": B_INCR, "frackin": B_INCR, "fracking": B_INCR, - "fricking": B_INCR, "frickin": B_INCR, "frigging": B_INCR, "friggin": B_INCR, "fully": B_INCR, - "fuckin": B_INCR, "fucking": B_INCR, "fuggin": B_INCR, "fugging": B_INCR, - "greatly": B_INCR, "hella": B_INCR, "highly": B_INCR, "hugely": B_INCR, - "incredible": B_INCR, "incredibly": B_INCR, "intensely": B_INCR, - "major": B_INCR, "majorly": B_INCR, "more": B_INCR, "most": B_INCR, "particularly": B_INCR, - "purely": B_INCR, "quite": B_INCR, "really": B_INCR, "remarkably": B_INCR, - "so": B_INCR, "substantially": B_INCR, - "thoroughly": B_INCR, "total": B_INCR, "totally": B_INCR, "tremendous": B_INCR, "tremendously": B_INCR, - "uber": B_INCR, "unbelievably": B_INCR, "unusually": B_INCR, "utter": B_INCR, "utterly": B_INCR, - "very": B_INCR, - "almost": B_DECR, "barely": B_DECR, "hardly": B_DECR, "just enough": B_DECR, - "kind of": B_DECR, "kinda": B_DECR, "kindof": B_DECR, "kind-of": B_DECR, - "less": B_DECR, "little": B_DECR, "marginal": B_DECR, "marginally": B_DECR, - "occasional": B_DECR, "occasionally": B_DECR, "partly": B_DECR, - "scarce": B_DECR, "scarcely": B_DECR, "slight": B_DECR, "slightly": B_DECR, "somewhat": B_DECR, - "sort of": B_DECR, "sorta": B_DECR, "sortof": B_DECR, "sort-of": B_DECR} - -# check for sentiment laden idioms that do not contain lexicon words (future work, not yet implemented) -SENTIMENT_LADEN_IDIOMS = {"cut the mustard": 2, "hand to mouth": -2, - "back handed": -2, "blow smoke": -2, "blowing smoke": -2, - "upper hand": 1, "break a leg": 2, - "cooking with gas": 2, "in the black": 2, "in the red": -2, - "on the ball": 2, "under the weather": -2} - -# check for special case idioms and phrases containing lexicon words -SPECIAL_CASES = {"the shit": 3, "the bomb": 3, "bad ass": 1.5, "badass": 1.5, "bus stop": 0.0, - "yeah right": -2, "kiss of death": -1.5, "to die for": 3, "beating heart": 3.5} - - -# #Static methods# # - -def negated(input_words, include_nt=True): - """ - Determine if input contains negation words - """ - input_words = [str(w).lower() for w in input_words] - neg_words = [] - neg_words.extend(NEGATE) - for word in neg_words: - if word in input_words: - return True - if include_nt: - for word in input_words: - if "n't" in word: - return True - '''if "least" in input_words: - i = input_words.index("least") - if i > 0 and input_words[i - 1] != "at": - return True''' - return False - - -def normalize(score, alpha=15): - """ - Normalize the score to be between -1 and 1 using an alpha that - approximates the max expected value - """ - norm_score = score / math.sqrt((score * score) + alpha) - if norm_score < -1.0: - return -1.0 - elif norm_score > 1.0: - return 1.0 - else: - return norm_score - - -def allcap_differential(words): - """ - Check whether just some words in the input are ALL CAPS - :param list words: The words to inspect - :returns: `True` if some but not all items in `words` are ALL CAPS - """ - is_different = False - allcap_words = 0 - for word in words: - if word.isupper(): - allcap_words += 1 - cap_differential = len(words) - allcap_words - if 0 < cap_differential < len(words): - is_different = True - return is_different - - -def scalar_inc_dec(word, valence, is_cap_diff): - """ - Check if the preceding words increase, decrease, or negate/nullify the - valence - """ - scalar = 0.0 - word_lower = word.lower() - if word_lower in BOOSTER_DICT: - scalar = BOOSTER_DICT[word_lower] - if valence < 0: - scalar *= -1 - # check if booster/dampener word is in ALLCAPS (while others aren't) - if word.isupper() and is_cap_diff: - if valence > 0: - scalar += C_INCR - else: - scalar -= C_INCR - return scalar - - -class SentiText(object): - """ - Identify sentiment-relevant string-level properties of input text. - """ - - def __init__(self, text): - if not isinstance(text, str): - text = str(text).encode('utf-8') - self.text = text - self.words_and_emoticons = self._words_and_emoticons() - # doesn't separate words from\ - # adjacent punctuation (keeps emoticons & contractions) - self.is_cap_diff = allcap_differential(self.words_and_emoticons) - - @staticmethod - def _strip_punc_if_word(token): - """ - Removes all trailing and leading punctuation - If the resulting string has two or fewer characters, - then it was likely an emoticon, so return original string - (ie ":)" stripped would be "", so just return ":)" - """ - stripped = token.strip(string.punctuation) - if len(stripped) <= 2: - return token - return stripped - - def _words_and_emoticons(self): - """ - Removes leading and trailing puncutation - Leaves contractions and most emoticons - Does not preserve punc-plus-letter emoticons (e.g. :D) - """ - wes = self.text.split() - stripped = list(map(self._strip_punc_if_word, wes)) - return stripped - -class SentimentIntensityAnalyzer(object): - """ - Give a sentiment intensity score to sentences. - """ - - def __init__(self, lexicon_file="vader_lexicon.txt", emoji_lexicon="emoji_utf8_lexicon.txt"): - _this_module_file_path_ = os.path.abspath(getsourcefile(lambda: 0)) - lexicon_full_filepath = os.path.join(os.path.dirname(_this_module_file_path_), lexicon_file) - with codecs.open(lexicon_full_filepath, encoding='utf-8') as f: - self.lexicon_full_filepath = f.read() - self.lexicon = self.make_lex_dict() - - emoji_full_filepath = os.path.join(os.path.dirname(_this_module_file_path_), emoji_lexicon) - with codecs.open(emoji_full_filepath, encoding='utf-8') as f: - self.emoji_full_filepath = f.read() - self.emojis = self.make_emoji_dict() - - def make_lex_dict(self): - """ - Convert lexicon file to a dictionary - """ - lex_dict = {} - for line in self.lexicon_full_filepath.rstrip('\n').split('\n'): - if not line: - continue - (word, measure) = line.strip().split('\t')[0:2] - lex_dict[word] = float(measure) - return lex_dict - - def make_emoji_dict(self): - """ - Convert emoji lexicon file to a dictionary - """ - emoji_dict = {} - for line in self.emoji_full_filepath.rstrip('\n').split('\n'): - (emoji, description) = line.strip().split('\t')[0:2] - emoji_dict[emoji] = description - return emoji_dict - - def polarity_scores(self, text): - """ - Return a float for sentiment strength based on the input text. - Positive values are positive valence, negative value are negative - valence. - """ - # convert emojis to their textual descriptions - text_no_emoji = "" - prev_space = True - for chr in text: - if chr in self.emojis: - # get the textual description - description = self.emojis[chr] - if not prev_space: - text_no_emoji += ' ' - text_no_emoji += description - prev_space = False - else: - text_no_emoji += chr - prev_space = chr == ' ' - text = text_no_emoji.strip() - - sentitext = SentiText(text) - - sentiments = [] - words_and_emoticons = sentitext.words_and_emoticons - for i, item in enumerate(words_and_emoticons): - valence = 0 - # check for vader_lexicon words that may be used as modifiers or negations - if item.lower() in BOOSTER_DICT: - sentiments.append(valence) - continue - if (i < len(words_and_emoticons) - 1 and item.lower() == "kind" and - words_and_emoticons[i + 1].lower() == "of"): - sentiments.append(valence) - continue - - sentiments = self.sentiment_valence(valence, sentitext, item, i, sentiments) - - sentiments = self._but_check(words_and_emoticons, sentiments) - - valence_dict = self.score_valence(sentiments, text) - - return valence_dict - - def sentiment_valence(self, valence, sentitext, item, i, sentiments): - is_cap_diff = sentitext.is_cap_diff - words_and_emoticons = sentitext.words_and_emoticons - item_lowercase = item.lower() - if item_lowercase in self.lexicon: - # get the sentiment valence - valence = self.lexicon[item_lowercase] - - # check for "no" as negation for an adjacent lexicon item vs "no" as its own stand-alone lexicon item - if item_lowercase == "no" and i != len(words_and_emoticons)-1 and words_and_emoticons[i + 1].lower() in self.lexicon: - # don't use valence of "no" as a lexicon item. Instead set it's valence to 0.0 and negate the next item - valence = 0.0 - if (i > 0 and words_and_emoticons[i - 1].lower() == "no") \ - or (i > 1 and words_and_emoticons[i - 2].lower() == "no") \ - or (i > 2 and words_and_emoticons[i - 3].lower() == "no" and words_and_emoticons[i - 1].lower() in ["or", "nor"] ): - valence = self.lexicon[item_lowercase] * N_SCALAR - - # check if sentiment laden word is in ALL CAPS (while others aren't) - if item.isupper() and is_cap_diff: - if valence > 0: - valence += C_INCR - else: - valence -= C_INCR - - for start_i in range(0, 3): - # dampen the scalar modifier of preceding words and emoticons - # (excluding the ones that immediately preceed the item) based - # on their distance from the current item. - if i > start_i and words_and_emoticons[i - (start_i + 1)].lower() not in self.lexicon: - s = scalar_inc_dec(words_and_emoticons[i - (start_i + 1)], valence, is_cap_diff) - if start_i == 1 and s != 0: - s = s * 0.95 - if start_i == 2 and s != 0: - s = s * 0.9 - valence = valence + s - valence = self._negation_check(valence, words_and_emoticons, start_i, i) - if start_i == 2: - valence = self._special_idioms_check(valence, words_and_emoticons, i) - - valence = self._least_check(valence, words_and_emoticons, i) - sentiments.append(valence) - return sentiments - - def _least_check(self, valence, words_and_emoticons, i): - # check for negation case using "least" - if i > 1 and words_and_emoticons[i - 1].lower() not in self.lexicon \ - and words_and_emoticons[i - 1].lower() == "least": - if words_and_emoticons[i - 2].lower() != "at" and words_and_emoticons[i - 2].lower() != "very": - valence = valence * N_SCALAR - elif i > 0 and words_and_emoticons[i - 1].lower() not in self.lexicon \ - and words_and_emoticons[i - 1].lower() == "least": - valence = valence * N_SCALAR - return valence - - @staticmethod - def _but_check(words_and_emoticons, sentiments): - # check for modification in sentiment due to contrastive conjunction 'but' - words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons] - if 'but' in words_and_emoticons_lower: - bi = words_and_emoticons_lower.index('but') - for sentiment in sentiments: - si = sentiments.index(sentiment) - if si < bi: - sentiments.pop(si) - sentiments.insert(si, sentiment * 0.5) - elif si > bi: - sentiments.pop(si) - sentiments.insert(si, sentiment * 1.5) - return sentiments - - @staticmethod - def _special_idioms_check(valence, words_and_emoticons, i): - words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons] - onezero = "{0} {1}".format(words_and_emoticons_lower[i - 1], words_and_emoticons_lower[i]) - - twoonezero = "{0} {1} {2}".format(words_and_emoticons_lower[i - 2], - words_and_emoticons_lower[i - 1], words_and_emoticons_lower[i]) - - twoone = "{0} {1}".format(words_and_emoticons_lower[i - 2], words_and_emoticons_lower[i - 1]) - - threetwoone = "{0} {1} {2}".format(words_and_emoticons_lower[i - 3], - words_and_emoticons_lower[i - 2], words_and_emoticons_lower[i - 1]) - - threetwo = "{0} {1}".format(words_and_emoticons_lower[i - 3], words_and_emoticons_lower[i - 2]) - - sequences = [onezero, twoonezero, twoone, threetwoone, threetwo] - - for seq in sequences: - if seq in SPECIAL_CASES: - valence = SPECIAL_CASES[seq] - break - - if len(words_and_emoticons_lower) - 1 > i: - zeroone = "{0} {1}".format(words_and_emoticons_lower[i], words_and_emoticons_lower[i + 1]) - if zeroone in SPECIAL_CASES: - valence = SPECIAL_CASES[zeroone] - if len(words_and_emoticons_lower) - 1 > i + 1: - zeroonetwo = "{0} {1} {2}".format(words_and_emoticons_lower[i], words_and_emoticons_lower[i + 1], - words_and_emoticons_lower[i + 2]) - if zeroonetwo in SPECIAL_CASES: - valence = SPECIAL_CASES[zeroonetwo] - - # check for booster/dampener bi-grams such as 'sort of' or 'kind of' - n_grams = [threetwoone, threetwo, twoone] - for n_gram in n_grams: - if n_gram in BOOSTER_DICT: - valence = valence + BOOSTER_DICT[n_gram] - return valence - - @staticmethod - def _sentiment_laden_idioms_check(valence, senti_text_lower): - # Future Work - # check for sentiment laden idioms that don't contain a lexicon word - idioms_valences = [] - for idiom in SENTIMENT_LADEN_IDIOMS: - if idiom in senti_text_lower: - print(idiom, senti_text_lower) - valence = SENTIMENT_LADEN_IDIOMS[idiom] - idioms_valences.append(valence) - if len(idioms_valences) > 0: - valence = sum(idioms_valences) / float(len(idioms_valences)) - return valence - - @staticmethod - def _negation_check(valence, words_and_emoticons, start_i, i): - words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons] - if start_i == 0: - if negated([words_and_emoticons_lower[i - (start_i + 1)]]): # 1 word preceding lexicon word (w/o stopwords) - valence = valence * N_SCALAR - if start_i == 1: - if words_and_emoticons_lower[i - 2] == "never" and \ - (words_and_emoticons_lower[i - 1] == "so" or - words_and_emoticons_lower[i - 1] == "this"): - valence = valence * 1.25 - elif words_and_emoticons_lower[i - 2] == "without" and \ - words_and_emoticons_lower[i - 1] == "doubt": - valence = valence - elif negated([words_and_emoticons_lower[i - (start_i + 1)]]): # 2 words preceding the lexicon word position - valence = valence * N_SCALAR - if start_i == 2: - if words_and_emoticons_lower[i - 3] == "never" and \ - (words_and_emoticons_lower[i - 2] == "so" or words_and_emoticons_lower[i - 2] == "this") or \ - (words_and_emoticons_lower[i - 1] == "so" or words_and_emoticons_lower[i - 1] == "this"): - valence = valence * 1.25 - elif words_and_emoticons_lower[i - 3] == "without" and \ - (words_and_emoticons_lower[i - 2] == "doubt" or words_and_emoticons_lower[i - 1] == "doubt"): - valence = valence - elif negated([words_and_emoticons_lower[i - (start_i + 1)]]): # 3 words preceding the lexicon word position - valence = valence * N_SCALAR - return valence - - def _punctuation_emphasis(self, text): - # add emphasis from exclamation points and question marks - ep_amplifier = self._amplify_ep(text) - qm_amplifier = self._amplify_qm(text) - punct_emph_amplifier = ep_amplifier + qm_amplifier - return punct_emph_amplifier - - @staticmethod - def _amplify_ep(text): - # check for added emphasis resulting from exclamation points (up to 4 of them) - ep_count = text.count("!") - if ep_count > 4: - ep_count = 4 - # (empirically derived mean sentiment intensity rating increase for - # exclamation points) - ep_amplifier = ep_count * 0.292 - return ep_amplifier - - @staticmethod - def _amplify_qm(text): - # check for added emphasis resulting from question marks (2 or 3+) - qm_count = text.count("?") - qm_amplifier = 0 - if qm_count > 1: - if qm_count <= 3: - # (empirically derived mean sentiment intensity rating increase for - # question marks) - qm_amplifier = qm_count * 0.18 - else: - qm_amplifier = 0.96 - return qm_amplifier - - @staticmethod - def _sift_sentiment_scores(sentiments): - # want separate positive versus negative sentiment scores - pos_sum = 0.0 - neg_sum = 0.0 - neu_count = 0 - for sentiment_score in sentiments: - if sentiment_score > 0: - pos_sum += (float(sentiment_score) + 1) # compensates for neutral words that are counted as 1 - if sentiment_score < 0: - neg_sum += (float(sentiment_score) - 1) # when used with math.fabs(), compensates for neutrals - if sentiment_score == 0: - neu_count += 1 - return pos_sum, neg_sum, neu_count - - def score_valence(self, sentiments, text): - if sentiments: - sum_s = float(sum(sentiments)) - # compute and add emphasis from punctuation in text - punct_emph_amplifier = self._punctuation_emphasis(text) - if sum_s > 0: - sum_s += punct_emph_amplifier - elif sum_s < 0: - sum_s -= punct_emph_amplifier - - compound = normalize(sum_s) - # discriminate between positive, negative and neutral sentiment scores - pos_sum, neg_sum, neu_count = self._sift_sentiment_scores(sentiments) - - if pos_sum > math.fabs(neg_sum): - pos_sum += punct_emph_amplifier - elif pos_sum < math.fabs(neg_sum): - neg_sum -= punct_emph_amplifier - - total = pos_sum + math.fabs(neg_sum) + neu_count - pos = math.fabs(pos_sum / total) - neg = math.fabs(neg_sum / total) - neu = math.fabs(neu_count / total) - - else: - compound = 0.0 - pos = 0.0 - neg = 0.0 - neu = 0.0 - - sentiment_dict = \ - {"neg": round(neg, 3), - "neu": round(neu, 3), - "pos": round(pos, 3), - "compound": round(compound, 4)} - - return sentiment_dict - - -if __name__ == '__main__': - # --- examples ------- - sentences = ["VADER is smart, handsome, and funny.", # positive sentence example - "VADER is smart, handsome, and funny!", - # punctuation emphasis handled correctly (sentiment intensity adjusted) - "VADER is very smart, handsome, and funny.", - # booster words handled correctly (sentiment intensity adjusted) - "VADER is VERY SMART, handsome, and FUNNY.", # emphasis for ALLCAPS handled - "VADER is VERY SMART, handsome, and FUNNY!!!", - # combination of signals - VADER appropriately adjusts intensity - "VADER is VERY SMART, uber handsome, and FRIGGIN FUNNY!!!", - # booster words & punctuation make this close to ceiling for score - "VADER is not smart, handsome, nor funny.", # negation sentence example - "The book was good.", # positive sentence - "At least it isn't a horrible book.", # negated negative sentence with contraction - "The book was only kind of good.", - # qualified positive sentence is handled correctly (intensity adjusted) - "The plot was good, but the characters are uncompelling and the dialog is not great.", - # mixed negation sentence - "Today SUX!", # negative slang with capitalization emphasis - "Today only kinda sux! But I'll get by, lol", - # mixed sentiment example with slang and constrastive conjunction "but" - "Make sure you :) or :D today!", # emoticons handled - "Catch utf-8 emoji such as 💘 and 💋 and 😁", # emojis handled - "Not bad at all" # Capitalized negation - ] - - analyzer = SentimentIntensityAnalyzer() - - print("----------------------------------------------------") - print(" - Analyze typical example cases, including handling of:") - print(" -- negations") - print(" -- punctuation emphasis & punctuation flooding") - print(" -- word-shape as emphasis (capitalization difference)") - print(" -- degree modifiers (intensifiers such as 'very' and dampeners such as 'kind of')") - print(" -- slang words as modifiers such as 'uber' or 'friggin' or 'kinda'") - print(" -- contrastive conjunction 'but' indicating a shift in sentiment; sentiment of later text is dominant") - print(" -- use of contractions as negations") - print(" -- sentiment laden emoticons such as :) and :D") - print(" -- utf-8 encoded emojis such as 💘 and 💋 and 😁") - print(" -- sentiment laden slang words (e.g., 'sux')") - print(" -- sentiment laden initialisms and acronyms (for example: 'lol') \n") - for sentence in sentences: - vs = analyzer.polarity_scores(sentence) - print("{:-<65} {}".format(sentence, str(vs))) - print("----------------------------------------------------") - print(" - About the scoring: ") - print(""" -- The 'compound' score is computed by summing the valence scores of each word in the lexicon, adjusted - according to the rules, and then normalized to be between -1 (most extreme negative) and +1 (most extreme positive). - This is the most useful metric if you want a single unidimensional measure of sentiment for a given sentence. - Calling it a 'normalized, weighted composite score' is accurate.""") - print(""" -- The 'pos', 'neu', and 'neg' scores are ratios for proportions of text that fall in each category (so these - should all add up to be 1... or close to it with float operation). These are the most useful metrics if - you want multidimensional measures of sentiment for a given sentence.""") - print("----------------------------------------------------") - - # input("\nPress Enter to continue the demo...\n") # for DEMO purposes... - - tricky_sentences = ["Sentiment analysis has never been good.", - "Sentiment analysis has never been this good!", - "Most automated sentiment analysis tools are shit.", - "With VADER, sentiment analysis is the shit!", - "Other sentiment analysis tools can be quite bad.", - "On the other hand, VADER is quite bad ass", - "VADER is such a badass!", # slang with punctuation emphasis - "Without a doubt, excellent idea.", - "Roger Dodger is one of the most compelling variations on this theme.", - "Roger Dodger is at least compelling as a variation on the theme.", - "Roger Dodger is one of the least compelling variations on this theme.", - "Not such a badass after all.", # Capitalized negation with slang - "Without a doubt, an excellent idea." # "without {any} doubt" as negation - ] - print("----------------------------------------------------") - print(" - Analyze examples of tricky sentences that cause trouble to other sentiment analysis tools.") - print(" -- special case idioms - e.g., 'never good' vs 'never this good', or 'bad' vs 'bad ass'.") - print(" -- special uses of 'least' as negation versus comparison \n") - for sentence in tricky_sentences: - vs = analyzer.polarity_scores(sentence) - print("{:-<69} {}".format(sentence, str(vs))) - print("----------------------------------------------------") - - # input("\nPress Enter to continue the demo...\n") # for DEMO purposes... - - print("----------------------------------------------------") - print( - " - VADER works best when analysis is done at the sentence level (but it can work on single words or entire novels).") - paragraph = "It was one of the worst movies I've seen, despite good reviews. Unbelievably bad acting!! Poor direction. VERY poor production. The movie was bad. Very bad movie. VERY BAD movie!" - print(" -- For example, given the following paragraph text from a hypothetical movie review:\n\t'{}'".format( - paragraph)) - print( - " -- You could use NLTK to break the paragraph into sentence tokens for VADER, then average the results for the paragraph like this: \n") - # simple example to tokenize paragraph into sentences for VADER - from nltk import tokenize - - sentence_list = tokenize.sent_tokenize(paragraph) - paragraphSentiments = 0.0 - for sentence in sentence_list: - vs = analyzer.polarity_scores(sentence) - print("{:-<69} {}".format(sentence, str(vs["compound"]))) - paragraphSentiments += vs["compound"] - print("AVERAGE SENTIMENT FOR PARAGRAPH: \t" + str(round(paragraphSentiments / len(sentence_list), 4))) - print("----------------------------------------------------") - - # input("\nPress Enter to continue the demo...\n") # for DEMO purposes... - - print("----------------------------------------------------") - print(" - Analyze sentiment of IMAGES/VIDEO data based on annotation 'tags' or image labels. \n") - conceptList = ["balloons", "cake", "candles", "happy birthday", "friends", "laughing", "smiling", "party"] - conceptSentiments = 0.0 - for concept in conceptList: - vs = analyzer.polarity_scores(concept) - print("{:-<15} {}".format(concept, str(vs['compound']))) - conceptSentiments += vs["compound"] - print("AVERAGE SENTIMENT OF TAGS/LABELS: \t" + str(round(conceptSentiments / len(conceptList), 4))) - print("\t") - conceptList = ["riot", "fire", "fight", "blood", "mob", "war", "police", "tear gas"] - conceptSentiments = 0.0 - for concept in conceptList: - vs = analyzer.polarity_scores(concept) - print("{:-<15} {}".format(concept, str(vs['compound']))) - conceptSentiments += vs["compound"] - print("AVERAGE SENTIMENT OF TAGS/LABELS: \t" + str(round(conceptSentiments / len(conceptList), 4))) - print("----------------------------------------------------") - - # input("\nPress Enter to continue the demo...") # for DEMO purposes... - - do_translate = input( - "\nWould you like to run VADER demo examples with NON-ENGLISH text? \n (Note: requires Internet access and uses the 'requests' library) \n Type 'y' or 'n', then press Enter: ") - if do_translate.lower().lstrip().__contains__("y"): - import requests - print("\n----------------------------------------------------") - print(" - Analyze sentiment of NON ENGLISH text...for example:") - print(" -- French, German, Spanish, Italian, Russian, Japanese, Arabic, Chinese(Simplified) , Chinese(Traditional)") - print(" -- many other languages supported. \n") - languages = ["English", "French", "German", "Spanish", "Italian", "Russian", "Japanese", "Arabic", "Chinese(Simplified)", "Chinese(Traditional)"] - language_codes = ["en", "fr", "de", "es", "it", "ru", "ja", "ar", "zh-CN", "zh-TW"] - nonEnglish_sentences = ["I'm surprised to see just how amazingly helpful VADER is!", - "Je suis surpris de voir comment VADER est incroyablement utile !", - "Ich bin überrascht zu sehen, nur wie erstaunlich nützlich VADER!", - "Me sorprende ver sólo cómo increíblemente útil VADER!", - "Sono sorpreso di vedere solo come incredibilmente utile VADER è!", - "Я удивлен увидеть, как раз как удивительно полезно ВЕЙДЕРА!", - "私はちょうどどのように驚くほど役に立つベイダーを見て驚いています!", - "أنا مندهش لرؤية فقط كيف مثير للدهشة فيدر فائدة!", - "我很惊讶地看到VADER是如此有用!", - "我很驚訝地看到VADER是如此有用!" - ] - for sentence in nonEnglish_sentences: - to_lang = "en" - from_lang = language_codes[nonEnglish_sentences.index(sentence)] - if (from_lang == "en") or (from_lang == "en-US"): - translation = sentence - translator_name = "No translation needed" - else: # please note usage limits for My Memory Translation Service: http://mymemory.translated.net/doc/usagelimits.php - # using MY MEMORY NET http://mymemory.translated.net - api_url = "http://mymemory.translated.net/api/get?q={}&langpair={}|{}".format(sentence, from_lang, - to_lang) - hdrs = { - 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11', - 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', - 'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3', - 'Accept-Encoding': 'none', - 'Accept-Language': 'en-US,en;q=0.8', - 'Connection': 'keep-alive'} - response = requests.get(api_url, headers=hdrs) - response_json = json.loads(response.text) - translation = response_json["responseData"]["translatedText"] - translator_name = "MemoryNet Translation Service" - vs = analyzer.polarity_scores(translation) - print("- {: <8}: {: <69}\t {} ({})".format(languages[nonEnglish_sentences.index(sentence)], sentence, - str(vs['compound']), translator_name)) - print("----------------------------------------------------") - - print("\n\n Demo Done!") \ No newline at end of file diff --git a/build/pyinstaller/vaderSentiment/vader_lexicon.txt b/build/pyinstaller/vaderSentiment/vader_lexicon.txt deleted file mode 100644 index 5b1f9f67f5c..00000000000 --- a/build/pyinstaller/vaderSentiment/vader_lexicon.txt +++ /dev/null @@ -1,7520 +0,0 @@ -$: -1.5 0.80623 [-1, -1, -1, -1, -3, -1, -3, -1, -2, -1] -%) -0.4 1.0198 [-1, 0, -1, 0, 0, -2, -1, 2, -1, 0] -%-) -1.5 1.43178 [-2, 0, -2, -2, -1, 2, -2, -3, -2, -3] -&-: -0.4 1.42829 [-3, -1, 0, 0, -1, -1, -1, 2, -1, 2] -&: -0.7 0.64031 [0, -1, -1, -1, 1, -1, -1, -1, -1, -1] -( '}{' ) 1.6 0.66332 [1, 2, 2, 1, 1, 2, 2, 1, 3, 1] -(% -0.9 0.9434 [0, 0, 1, -1, -1, -1, -2, -2, -1, -2] -('-: 2.2 1.16619 [4, 1, 4, 3, 1, 2, 3, 1, 2, 1] -(': 2.3 0.9 [1, 3, 3, 2, 2, 4, 2, 3, 1, 2] -((-: 2.1 0.53852 [2, 2, 2, 1, 2, 3, 2, 2, 3, 2] -(* 1.1 1.13578 [2, 1, 1, -1, 1, 2, 2, -1, 2, 2] -(-% -0.7 1.26886 [-1, 2, 0, -1, -1, -2, 0, 0, -3, -1] -(-* 1.3 1.26886 [4, 1, 2, 0, 2, -1, 1, 2, 1, 1] -(-: 1.6 0.8 [2, 2, 1, 3, 1, 1, 1, 3, 1, 1] -(-:0 2.8 0.87178 [3, 2, 3, 4, 3, 2, 3, 1, 4, 3] -(-:< -0.4 2.15407 [-3, 3, -1, -1, 2, -1, -2, 3, -3, -1] -(-:o 1.5 0.67082 [3, 1, 1, 2, 2, 2, 1, 1, 1, 1] -(-:O 1.5 0.67082 [3, 1, 1, 2, 2, 2, 1, 1, 1, 1] -(-:{ -0.1 1.57797 [-2, -3, 1, -2, 1, 1, 0, 0, 2, 1] -(-:|>* 1.9 0.83066 [3, 2, 2, 1, 0, 2, 3, 2, 2, 2] -(-; 1.3 1.18743 [3, 2, 3, 0, 1, -1, 1, 2, 1, 1] -(-;| 2.1 1.13578 [3, 2, 2, 4, 1, 1, 1, 4, 2, 1] -(8 2.6 1.0198 [4, 2, 1, 3, 3, 3, 3, 1, 2, 4] -(: 2.2 1.16619 [3, 1, 1, 2, 1, 2, 4, 3, 4, 1] -(:0 2.4 1.11355 [0, 2, 3, 4, 3, 2, 3, 3, 1, 3] -(:< -0.2 2.03961 [-2, -3, 1, 1, 2, -1, 2, 1, -4, 1] -(:o 2.5 0.92195 [3, 3, 1, 3, 3, 1, 2, 2, 4, 3] -(:O 2.5 0.92195 [3, 3, 1, 3, 3, 1, 2, 2, 4, 3] -(; 1.1 1.22066 [3, 1, 1, -1, 1, 2, 2, -1, 1, 2] -(;< 0.3 1.00499 [1, 2, -1, -1, 0, 0, 1, -1, 1, 1] -(= 2.2 1.16619 [3, 1, 2, 2, 1, 1, 4, 3, 4, 1] -(?: 2.1 0.83066 [2, 2, 1, 3, 2, 2, 4, 1, 2, 2] -(^: 1.5 0.67082 [1, 2, 2, 1, 3, 2, 1, 1, 1, 1] -(^; 1.5 0.5 [1, 2, 2, 1, 2, 1, 2, 1, 1, 2] -(^;0 2.0 0.7746 [2, 2, 1, 2, 1, 4, 2, 2, 2, 2] -(^;o 1.9 0.83066 [2, 2, 1, 2, 1, 4, 2, 1, 2, 2] -(o: 1.6 0.8 [2, 1, 3, 1, 1, 1, 2, 3, 1, 1] -)': -2.0 0.44721 [-2, -2, -2, -2, -1, -3, -2, -2, -2, -2] -)-': -2.1 0.53852 [-2, -2, -3, -2, -1, -2, -3, -2, -2, -2] -)-: -2.1 0.9434 [-3, -2, -4, -1, -3, -2, -2, -2, -1, -1] -)-:< -2.2 0.4 [-2, -2, -2, -2, -2, -2, -3, -3, -2, -2] -)-:{ -2.1 0.9434 [-1, -3, -2, -1, -2, -2, -3, -4, -1, -2] -): -1.8 0.87178 [-1, -3, -1, -2, -1, -3, -1, -3, -1, -2] -):< -1.9 0.53852 [-1, -3, -2, -2, -2, -1, -2, -2, -2, -2] -):{ -2.3 0.78102 [-1, -2, -3, -3, -2, -2, -4, -2, -2, -2] -);< -2.6 0.8 [-2, -2, -2, -3, -2, -3, -2, -2, -4, -4] -*) 0.6 1.42829 [1, -1, 1, -3, 1, 1, 2, 1, 1, 2] -*-) 0.3 1.61555 [1, -3, -2, 2, 1, 1, -1, 2, 1, 1] -*-: 2.1 1.51327 [2, 2, 4, 4, 2, 1, -1, 4, 1, 2] -*-; 2.4 1.62481 [2, 3, 4, 4, 2, 1, -1, 4, 1, 4] -*: 1.9 1.04403 [2, 1, 1, 3, 1, 2, 4, 3, 1, 1] -*<|:-) 1.6 1.28062 [0, 1, 3, 1, 1, 2, 3, 0, 4, 1] -*\0/* 2.3 1.00499 [2, 0, 3, 1, 3, 3, 2, 3, 3, 3] -*^: 1.6 1.42829 [2, 2, 1, 3, 2, 2, 3, 3, -1, -1] -,-: 1.2 0.4 [1, 1, 2, 1, 1, 1, 1, 1, 2, 1] ----'-;-{@ 2.3 1.18743 [0, 1, 3, 4, 2, 3, 2, 2, 2, 4] ---<--<@ 2.2 1.249 [0, 1, 2, 4, 2, 1, 3, 2, 3, 4] -.-: -1.2 0.4 [-1, -1, -1, -1, -1, -1, -2, -1, -2, -1] -..###-: -1.7 0.78102 [-2, -3, -3, -2, -1, -1, -1, -1, -1, -2] -..###: -1.9 1.04403 [-4, -1, -3, -1, -2, -2, -1, -3, -1, -1] -/-: -1.3 0.64031 [-1, -1, -1, -1, -1, -1, -1, -2, -3, -1] -/: -1.3 0.45826 [-2, -1, -1, -1, -2, -1, -1, -2, -1, -1] -/:< -1.4 0.4899 [-1, -2, -2, -1, -1, -1, -1, -1, -2, -2] -/= -0.9 0.53852 [-1, -1, -1, 0, -1, -2, -1, -1, -1, 0] -/^: -1.0 0.7746 [-2, -1, -2, 1, -1, -1, -1, -1, -1, -1] -/o: -1.4 0.66332 [0, -2, -1, -1, -2, -2, -1, -2, -1, -2] -0-8 0.1 1.44568 [2, -1, -2, 0, 2, 0, 2, 0, -2, 0] -0-| -1.2 0.4 [-2, -1, -1, -1, -1, -1, -1, -1, -2, -1] -0:) 1.9 1.04403 [2, 2, 2, 1, 0, 2, 4, 1, 3, 2] -0:-) 1.4 0.91652 [2, 1, 0, 1, 2, 3, 2, 1, 2, 0] -0:-3 1.5 0.92195 [2, 1, 0, 2, 2, 3, 2, 1, 2, 0] -0:03 1.9 1.22066 [2, 3, 2, 0, 0, 1, 4, 2, 3, 2] -0;^) 1.6 0.91652 [0, 1, 3, 1, 2, 1, 2, 1, 2, 3] -0_o -0.3 0.78102 [0, -2, 0, 1, 0, 0, -1, 0, -1, 0] -10q 2.1 1.22066 [1, 3, 1, 2, 1, 4, 3, 4, 1, 1] -1337 2.1 1.13578 [3, 1, 4, 0, 2, 3, 1, 2, 2, 3] -143 3.2 0.74833 [4, 4, 2, 3, 2, 3, 4, 3, 4, 3] -1432 2.6 0.8 [4, 3, 3, 2, 2, 4, 2, 2, 2, 2] -14aa41 2.4 0.91652 [3, 2, 2, 4, 2, 2, 1, 2, 4, 2] -182 -2.9 1.3 [-4, 0, -3, -3, -1, -3, -4, -4, -4, -3] -187 -3.1 1.22066 [-4, 0, -4, -3, -2, -4, -3, -3, -4, -4] -2g2b4g 2.8 0.6 [4, 2, 3, 2, 3, 3, 3, 3, 2, 3] -2g2bt -0.1 1.57797 [-1, 2, -1, 1, 0, 2, 0, -3, -2, 1] -2qt 2.1 0.83066 [3, 3, 3, 3, 2, 1, 2, 1, 2, 1] -3:( -2.2 0.87178 [-4, -3, -2, -3, -2, -1, -1, -2, -2, -2] -3:) 0.5 1.28452 [-2, 1, -2, 1, 1, 1, 1, 2, 1, 1] -3:-( -2.3 0.78102 [-2, -3, -2, -2, -2, -2, -4, -1, -3, -2] -3:-) -1.4 1.35647 [-1, -2, 1, 1, -2, -2, -3, -1, -3, -2] -4col -2.2 1.16619 [-2, -3, -1, -3, -4, -1, -2, -1, -4, -1] -4q -3.1 1.51327 [-3, -3, -4, -2, -4, -4, -4, 1, -4, -4] -5fs 1.5 1.11803 [1, 2, 1, 1, 2, 3, 2, 3, -1, 1] -8) 1.9 0.7 [2, 2, 2, 1, 1, 2, 2, 3, 3, 1] -8-d 1.7 0.64031 [1, 2, 0, 2, 2, 2, 2, 2, 2, 2] -8-o -0.3 0.78102 [1, -1, 0, 0, 0, -1, 0, -2, 0, 0] -86 -1.6 1.0198 [-1, -1, -1, -1, -1, -4, -1, -2, -1, -3] -8d 2.9 0.53852 [3, 3, 4, 2, 3, 3, 3, 3, 2, 3] -:###.. -2.4 0.91652 [-3, -2, -4, -3, -1, -2, -2, -3, -1, -3] -:$ -0.2 1.83303 [-2, -1, 0, 0, -1, 1, 4, -3, 1, -1] -:& -0.6 1.0198 [-2, -1, 0, 0, -1, -1, 1, -2, 1, -1] -:'( -2.2 0.74833 [-2, -1, -2, -2, -2, -2, -4, -3, -2, -2] -:') 2.3 0.78102 [3, 1, 3, 2, 2, 2, 2, 4, 2, 2] -:'-( -2.4 0.66332 [-2, -1, -2, -3, -2, -3, -3, -3, -2, -3] -:'-) 2.7 0.64031 [2, 1, 3, 3, 3, 3, 3, 3, 3, 3] -:( -1.9 1.13578 [-2, -3, -2, 0, -1, -1, -2, -3, -1, -4] -:) 2.0 1.18322 [2, 2, 1, 1, 1, 1, 4, 3, 4, 1] -:* 2.5 1.0247 [3, 2, 1, 1, 2, 3, 4, 3, 4, 2] -:-###.. -2.5 0.92195 [-3, -2, -3, -2, -4, -3, -1, -3, -1, -3] -:-& -0.5 0.92195 [-1, -1, 0, -1, -1, -1, -1, 0, 2, -1] -:-( -1.5 0.5 [-2, -1, -1, -1, -2, -2, -2, -1, -2, -1] -:-) 1.3 0.45826 [1, 1, 1, 1, 2, 1, 2, 1, 2, 1] -:-)) 2.8 1.07703 [3, 4, 4, 1, 2, 2, 4, 2, 4, 2] -:-* 1.7 0.64031 [1, 2, 1, 1, 1, 3, 2, 2, 2, 2] -:-, 1.1 0.53852 [1, 1, 1, 0, 1, 1, 1, 1, 2, 2] -:-. -0.9 0.53852 [-1, -1, 0, -1, 0, -1, -1, -1, -2, -1] -:-/ -1.2 0.6 [0, -1, -1, -1, -1, -2, -2, -1, -1, -2] -:-< -1.5 0.5 [-2, -1, -1, -2, -1, -2, -2, -1, -2, -1] -:-d 2.3 0.45826 [2, 2, 3, 3, 2, 3, 2, 2, 2, 2] -:-D 2.3 0.45826 [2, 2, 3, 3, 2, 3, 2, 2, 2, 2] -:-o 0.1 1.3 [2, -1, -2, 0, 1, 1, 2, 0, -1, -1] -:-p 1.2 0.4 [1, 2, 1, 1, 1, 1, 2, 1, 1, 1] -:-[ -1.6 0.4899 [-1, -2, -1, -2, -2, -1, -2, -1, -2, -2] -:-\ -0.9 0.3 [-1, -1, -1, -1, -1, -1, -1, 0, -1, -1] -:-c -1.3 0.45826 [-1, -1, -1, -2, -2, -1, -2, -1, -1, -1] -:-p 1.5 0.5 [1, 1, 1, 1, 1, 2, 2, 2, 2, 2] -:-| -0.7 0.64031 [-1, -1, 0, 0, 0, -1, -1, -2, 0, -1] -:-|| -2.5 0.67082 [-2, -2, -2, -3, -2, -3, -3, -2, -2, -4] -:-Þ 0.9 1.04403 [1, -1, 1, 2, 1, -1, 1, 2, 2, 1] -:/ -1.4 0.66332 [-1, -1, -1, -1, -1, -1, -3, -2, -2, -1] -:3 2.3 1.26886 [4, 1, 1, 1, 2, 2, 4, 3, 4, 1] -:< -2.1 0.7 [-3, -1, -2, -2, -2, -2, -3, -3, -2, -1] -:> 2.1 1.22066 [3, 1, 1, 1, 1, 2, 4, 3, 4, 1] -:?) 1.3 0.64031 [3, 1, 1, 1, 1, 2, 1, 1, 1, 1] -:?c -1.6 0.4899 [-1, -2, -1, -1, -2, -2, -1, -2, -2, -2] -:@ -2.5 0.80623 [-1, -3, -3, -2, -1, -3, -3, -3, -3, -3] -:d 2.3 1.1 [4, 2, 2, 1, 2, 1, 4, 3, 3, 1] -:D 2.3 1.1 [4, 2, 2, 1, 2, 1, 4, 3, 3, 1] -:l -1.7 0.9 [-1, -3, -1, -1, -1, -3, -2, -3, -1, -1] -:o -0.4 1.35647 [2, -1, -2, 0, 1, 0, -3, 0, -1, 0] -:p 1.0 0.7746 [-1, 1, 1, 1, 1, 1, 2, 1, 2, 1] -:s -1.2 0.9798 [-2, -2, -1, -1, -1, 1, -3, -1, -1, -1] -:[ -2.0 0.63246 [-2, -2, -1, -2, -2, -3, -3, -2, -1, -2] -:\ -1.3 0.45826 [-2, -1, -1, -1, -1, -1, -2, -1, -1, -2] -:] 2.2 1.16619 [3, 1, 1, 1, 3, 1, 4, 2, 2, 4] -:^) 2.1 1.13578 [3, 2, 4, 1, 1, 1, 1, 2, 4, 2] -:^* 2.6 0.91652 [2, 1, 2, 3, 4, 4, 3, 2, 3, 2] -:^/ -1.2 0.6 [-2, -1, -2, 0, -1, -1, -1, -1, -2, -1] -:^\ -1.0 0.44721 [-1, -1, -1, -1, -1, -2, 0, -1, -1, -1] -:^| -1.0 0.0 [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1] -:c -2.1 0.83066 [-3, -2, -1, -2, -2, -1, -3, -3, -3, -1] -:c) 2.0 1.18322 [2, 1, 1, 1, 1, 2, 3, 4, 4, 1] -:o) 2.1 0.9434 [1, 3, 3, 1, 1, 3, 2, 3, 1, 3] -:o/ -1.4 0.4899 [-1, -1, -1, -2, -1, -1, -2, -2, -1, -2] -:o\ -1.1 0.3 [-1, -1, -1, -2, -1, -1, -1, -1, -1, -1] -:o| -0.6 1.0198 [0, 0, 0, 0, -1, 0, 0, -3, 0, -2] -:P 1.4 0.8 [3, 1, 0, 2, 1, 1, 2, 2, 1, 1] -:{ -1.9 0.83066 [-2, -1, -1, -2, -2, -1, -3, -3, -3, -1] -:| -0.4 1.11355 [-1, -1, 0, -1, -1, -1, 1, -2, 2, 0] -:} 2.1 1.22066 [3, 1, 1, 1, 2, 1, 4, 3, 4, 1] -:Þ 1.1 0.53852 [1, 1, 1, 1, 0, 1, 1, 2, 2, 1] -;) 0.9 1.04403 [2, -1, 1, 1, 1, 1, -1, 2, 2, 1] -;-) 1.0 1.73205 [1, -2, 1, -2, 1, 4, 2, 1, 2, 2] -;-* 2.2 0.74833 [2, 2, 1, 3, 4, 2, 2, 2, 2, 2] -;-] 0.7 1.67631 [1, -2, 1, -3, 1, 2, 2, 1, 2, 2] -;d 0.8 1.249 [2, -1, 2, 1, 1, 1, -2, 2, 1, 1] -;D 0.8 1.249 [2, -1, 2, 1, 1, 1, -2, 2, 1, 1] -;] 0.6 1.11355 [1, -1, 1, 1, 1, 1, -2, 2, 1, 1] -;^) 1.4 0.91652 [2, 2, 1, 2, 1, 2, -1, 1, 2, 2] --: -2.0 0.89443 [-2, -3, -2, -4, -1, -1, -1, -2, -2, -2] ->.< -1.3 0.45826 [-1, -2, -1, -2, -2, -1, -1, -1, -1, -1] ->: -2.1 1.13578 [-4, -1, -1, -4, -2, -3, -1, -1, -2, -2] ->:( -2.7 0.64031 [-2, -3, -2, -3, -3, -2, -4, -2, -3, -3] ->:) 0.4 1.42829 [1, 1, 2, 1, -1, -2, 1, 2, -2, 1] ->:-( -2.7 0.78102 [-3, -2, -3, -2, -4, -2, -3, -2, -2, -4] ->:-) -0.4 1.68523 [1, 2, 1, -2, -2, -1, -1, -3, -1, 2] ->:/ -1.6 0.8 [-1, -2, -1, -3, -1, -1, -1, -1, -2, -3] ->:o -1.2 1.16619 [-3, -1, -2, 0, -2, -2, 0, -1, 1, -2] ->:p 1.0 0.7746 [-1, 1, 1, 2, 1, 2, 1, 1, 1, 1] ->:[ -2.1 0.53852 [-2, -2, -2, -2, -3, -3, -2, -1, -2, -2] ->:\ -1.7 0.64031 [-1, -2, -1, -2, -2, -3, -1, -1, -2, -2] ->;( -2.9 0.7 [-3, -4, -3, -2, -2, -3, -3, -3, -2, -4] ->;) 0.1 1.04403 [-1, 1, 0, -1, 2, 0, -1, 1, 1, -1] ->_>^ 2.1 0.9434 [2, 2, 1, 4, 3, 2, 1, 3, 1, 2] -@: -2.1 0.9434 [-3, -2, -3, -1, -2, -4, -1, -2, -1, -2] -@>-->-- 2.1 1.22066 [1, 1, 0, 2, 4, 2, 4, 2, 3, 2] -@}-;-'--- 2.2 1.32665 [0, 1, 3, 2, 1, 4, 4, 1, 3, 3] -aas 2.5 0.80623 [2, 3, 3, 4, 1, 2, 3, 2, 2, 3] -aayf 2.7 0.78102 [2, 3, 2, 4, 3, 2, 2, 3, 4, 2] -afu -2.9 0.83066 [-3, -3, -3, -3, -3, -1, -4, -4, -2, -3] -alol 2.8 0.74833 [2, 2, 2, 3, 3, 2, 3, 4, 4, 3] -ambw 2.9 0.7 [2, 3, 4, 2, 3, 2, 3, 3, 4, 3] -aml 3.4 0.66332 [4, 3, 2, 4, 3, 3, 4, 4, 3, 4] -atab -1.9 1.22066 [-2, 0, -1, -2, -1, -1, -2, -4, -4, -2] -awol -1.3 0.78102 [0, -1, -1, -1, -1, -1, -2, -2, -3, -1] -ayc 0.2 0.9798 [0, 1, -1, 1, 0, 1, 0, -1, 2, -1] -ayor -1.2 0.6 [-1, -1, -2, -2, -1, -1, -1, 0, -2, -1] -aug-00 0.3 1.18743 [2, 0, -2, 0, 0, 1, -1, 2, 1, 0] -bfd -2.7 0.78102 [-3, -2, -4, -2, -3, -2, -3, -2, -4, -2] -bfe -2.6 1.35647 [-3, -3, -4, -2, -3, -2, 1, -3, -4, -3] -bff 2.9 0.83066 [3, 3, 4, 2, 4, 2, 2, 3, 4, 2] -bffn 1.0 0.89443 [2, 1, -1, 1, 0, 1, 2, 1, 2, 1] -bl 2.3 1.1 [2, 1, 4, 1, 2, 2, 4, 3, 1, 3] -bsod -2.2 1.07703 [-1, -4, -3, -3, 0, -2, -3, -2, -2, -2] -btd -2.1 0.83066 [-1, -2, -3, -3, -3, -1, -3, -2, -1, -2] -btdt -0.1 1.22066 [0, -1, 0, -1, 0, 3, 1, -1, -1, -1] -bz 0.4 1.35647 [-1, 0, 0, 0, 4, 1, -1, 1, 0, 0] -b^d 2.6 0.8 [3, 2, 2, 4, 3, 1, 3, 3, 3, 2] -cwot -2.3 0.45826 [-3, -2, -2, -2, -2, -3, -2, -3, -2, -2] -d-': -2.5 0.67082 [-3, -3, -2, -2, -2, -4, -2, -3, -2, -2] -d8 -3.2 0.6 [-3, -3, -3, -3, -4, -4, -2, -3, -3, -4] -d: -2.9 0.83066 [-3, -3, -3, -3, -2, -4, -1, -3, -3, -4] -d:< -3.2 0.9798 [-4, -4, -4, -1, -3, -3, -4, -2, -3, -4] -d; -2.9 0.83066 [-1, -3, -3, -3, -3, -4, -2, -3, -3, -4] -d= -3.0 0.89443 [-4, -3, -3, -3, -2, -4, -1, -3, -3, -4] -doa -2.3 1.00499 [-2, -3, -3, -2, -2, -2, -4, 0, -2, -3] -dx -3.0 0.63246 [-3, -2, -3, -3, -4, -3, -4, -2, -3, -3] -ez 1.5 0.67082 [3, 2, 2, 1, 1, 1, 2, 1, 1, 1] -fav 2.4 0.91652 [3, 1, 3, 2, 2, 3, 1, 2, 3, 4] -fcol -1.8 0.74833 [-2, -2, -1, -2, -1, -2, -1, -3, -3, -1] -ff 1.8 1.249 [4, 2, 1, 2, 1, 3, 3, 0, 2, 0] -ffs -2.8 0.9798 [-2, -2, -3, -3, -2, -4, -4, -4, -1, -3] -fkm -2.4 1.35647 [-4, -1, -4, -2, -2, -3, -1, 0, -3, -4] -foaf 1.8 1.249 [2, 1, 2, 0, 4, 1, 1, 1, 2, 4] -ftw 2.0 0.7746 [2, 1, 1, 2, 2, 2, 3, 3, 1, 3] -fu -3.7 0.45826 [-3, -4, -4, -3, -3, -4, -4, -4, -4, -4] -fubar -3.0 1.09545 [-4, -3, -3, -4, -3, -3, -3, -4, 0, -3] -fwb 2.5 1.43178 [2, 3, 4, 0, 1, 2, 4, 1, 4, 4] -fyi 0.8 1.66132 [0, 1, 0, -1, 0, 0, 4, 4, 0, 0] -fysa 0.4 0.91652 [0, 0, 0, 1, 0, 3, 0, 0, 0, 0] -g1 1.4 0.4899 [2, 1, 1, 1, 2, 1, 2, 1, 1, 2] -gg 1.2 0.74833 [0, 2, 2, 1, 0, 1, 2, 2, 1, 1] -gga 1.7 0.45826 [2, 2, 1, 2, 2, 1, 2, 2, 1, 2] -gigo -0.6 1.11355 [-2, -1, 1, 0, 0, 0, -1, -2, -2, 1] -gj 2.0 1.0 [2, 1, 2, 1, 1, 3, 4, 2, 3, 1] -gl 1.3 0.64031 [1, 1, 1, 1, 3, 1, 1, 2, 1, 1] -gla 2.5 0.92195 [1, 2, 2, 4, 2, 4, 2, 3, 3, 2] -gn 1.2 0.74833 [1, 1, 1, 1, 3, 1, 1, 2, 1, 0] -gr8 2.7 0.78102 [1, 3, 3, 4, 3, 2, 3, 2, 3, 3] -grrr -0.4 1.42829 [-2, -1, 0, 1, -2, -1, -1, 3, 0, -1] -gt 1.1 0.53852 [1, 1, 1, 1, 1, 1, 2, 1, 0, 2] -h&k 2.3 0.78102 [2, 2, 2, 3, 4, 2, 3, 2, 1, 2] -hagd 2.2 0.87178 [2, 2, 3, 2, 1, 3, 4, 1, 2, 2] -hagn 2.2 0.87178 [2, 2, 3, 2, 1, 3, 4, 1, 2, 2] -hago 1.2 0.4 [1, 2, 1, 1, 1, 2, 1, 1, 1, 1] -hak 1.9 0.7 [3, 1, 2, 2, 1, 2, 3, 2, 1, 2] -hand 2.2 0.87178 [2, 2, 1, 3, 2, 3, 4, 1, 2, 2] -heart 3.2 0.63246 [3, 3, 4, 3, 4, 2, 3, 4, 3, 3] -hearts 3.3 0.48305 [4, 3, 3, 3, 4, 3, 3, 3, 4, 3] -hho1/2k 1.4 1.11355 [1, -1, 2, 3, 1, 1, 1, 2, 3, 1] -hhoj 2.0 1.09545 [4, 2, 1, 1, 2, 1, 1, 4, 2, 2] -hhok 0.9 0.9434 [1, 2, 1, 0, -1, 0, 2, 1, 1, 2] -hugz 2.0 0.7746 [2, 3, 1, 3, 1, 3, 1, 2, 2, 2] -hi5 1.9 0.53852 [2, 2, 2, 1, 3, 2, 1, 2, 2, 2] -idk -0.4 0.66332 [0, 0, 0, 0, -1, -2, 0, 0, 0, -1] -ijs 0.7 1.84662 [0, -1, 0, -1, 0, 4, 0, 4, -1, 2] -ilu 3.4 0.66332 [3, 4, 3, 4, 2, 3, 4, 3, 4, 4] -iluaaf 2.7 1.1 [3, 3, 3, 2, 3, 0, 4, 3, 2, 4] -ily 3.4 0.66332 [3, 4, 3, 4, 2, 3, 4, 3, 4, 4] -ily2 2.6 0.66332 [3, 2, 3, 2, 3, 2, 3, 4, 2, 2] -iou 0.7 1.34536 [0, 0, -1, 2, 0, 0, 0, 4, 1, 1] -iyq 2.3 1.18743 [3, 3, 1, 1, 2, 1, 4, 4, 3, 1] -j/j 2.0 1.34164 [4, 1, 1, 1, 1, 4, 4, 1, 2, 1] -j/k 1.6 1.2 [1, 2, 1, 3, 0, 0, 2, 2, 1, 4] -j/p 1.4 0.66332 [1, 1, 0, 2, 1, 2, 2, 2, 1, 2] -j/t -0.2 1.46969 [1, -1, -1, -2, 1, 1, 2, -2, 1, -2] -j/w 1.0 1.0 [1, 1, 1, 3, 0, 0, 0, 2, 0, 2] -j4f 1.4 0.8 [2, 1, 1, 0, 3, 1, 1, 1, 2, 2] -j4g 1.7 1.18743 [1, 4, 1, 1, 3, 1, 3, 0, 2, 1] -jho 0.8 0.4 [1, 1, 1, 1, 0, 1, 1, 1, 0, 1] -jhomf 1.0 0.63246 [1, 1, 1, 0, 1, 0, 2, 2, 1, 1] -jj 1.0 0.63246 [1, 1, 1, 1, 2, 0, 2, 1, 1, 0] -jk 0.9 1.22066 [1, 0, 0, 1, 0, 0, 2, 1, 4, 0] -jp 0.8 0.74833 [1, 1, 1, 0, 2, 0, 2, 0, 1, 0] -jt 0.9 0.83066 [1, 1, 0, 2, 2, 0, 2, 0, 1, 0] -jw 1.6 1.68523 [3, 0, 0, 0, 0, 0, 3, 4, 2, 4] -jealz -1.2 0.9798 [-1, -1, -1, 1, -2, -2, -1, -3, -1, -1] -k4y 2.3 1.00499 [2, 1, 1, 2, 4, 2, 3, 4, 2, 2] -kfy 2.3 0.64031 [2, 2, 2, 1, 3, 2, 3, 3, 2, 3] -kia -3.2 0.6 [-3, -3, -3, -4, -3, -2, -3, -3, -4, -4] -kk 1.5 1.0247 [2, 1, 0, 0, 1, 2, 3, 3, 2, 1] -kmuf 2.2 1.4 [2, 2, 2, 3, 4, 3, -1, 1, 4, 2] -l 2.0 0.7746 [2, 1, 2, 3, 2, 3, 1, 3, 2, 1] -l&r 2.2 0.74833 [3, 2, 2, 3, 1, 3, 1, 3, 2, 2] -laoj 1.3 1.73494 [1, -2, -1, 3, 3, 2, 4, 1, 1, 1] -lmao 2.0 1.18322 [3, 0, 3, 0, 3, 1, 3, 2, 3, 2] -lmbao 1.8 1.77764 [3, 2, 2, 2, 1, 3, -3, 2, 4, 2] -lmfao 2.5 1.28452 [3, 2, 3, 3, 3, -1, 4, 2, 3, 2] -lmso 2.7 0.78102 [3, 3, 4, 3, 3, 1, 3, 3, 2, 2] -lol 2.9 0.83066 [4, 2, 2, 2, 4, 2, 3, 3, 4, 3] -lolz 2.7 0.78102 [2, 3, 3, 2, 2, 4, 4, 3, 2, 2] -lts 1.6 0.66332 [1, 1, 2, 2, 1, 3, 1, 1, 2, 2] -ly 2.6 0.91652 [2, 2, 1, 3, 4, 4, 3, 2, 2, 3] -ly4e 2.7 0.78102 [3, 3, 3, 2, 1, 3, 3, 4, 2, 3] -lya 3.3 0.78102 [3, 4, 4, 4, 2, 2, 3, 4, 3, 4] -lyb 3.0 0.63246 [3, 3, 4, 3, 2, 3, 2, 4, 3, 3] -lyl 3.1 0.7 [4, 3, 4, 3, 2, 3, 3, 2, 4, 3] -lylab 2.7 0.78102 [3, 3, 3, 1, 3, 4, 2, 2, 3, 3] -lylas 2.6 0.8 [3, 3, 3, 1, 3, 4, 2, 2, 2, 3] -lylb 1.6 1.56205 [2, 2, 3, -2, 4, 1, 3, 1, 1, 1] -m8 1.4 1.0198 [3, 0, 1, 0, 1, 3, 2, 2, 1, 1] -mia -1.2 0.4 [-2, -1, -1, -2, -1, -1, -1, -1, -1, -1] -mml 2.0 1.0 [1, 1, 2, 3, 3, 2, 1, 2, 4, 1] -mofo -2.4 2.2 [-4, -4, -4, 0, -3, -2, -2, -4, 3, -4] -muah 2.8 1.07703 [1, 2, 4, 4, 4, 2, 4, 2, 2, 3] -mubar -1.0 2.36643 [-4, -2, -3, -2, -2, -2, 1, 4, 2, -2] -musm 0.9 2.07123 [-1, 1, 1, 1, 4, 3, 1, -4, 1, 2] -mwah 2.5 0.80623 [2, 2, 2, 4, 2, 3, 2, 2, 4, 2] -n1 1.9 1.04403 [1, 1, 3, 2, 2, 3, 4, 1, 1, 1] -nbd 1.3 1.34536 [2, 1, 0, 0, 0, 4, 2, 0, 3, 1] -nbif -0.5 0.67082 [-1, -2, 0, 0, 0, 0, -1, -1, 0, 0] -nfc -2.7 0.9 [-3, -2, -2, -3, -1, -2, -4, -3, -4, -3] -nfw -2.4 1.0198 [-2, -2, -1, -3, -1, -2, -4, -3, -4, -2] -nh 2.2 0.6 [2, 2, 2, 2, 1, 3, 3, 3, 2, 2] -nimby -0.8 0.6 [0, 0, -1, 0, -1, -2, -1, -1, -1, -1] -nimjd -0.7 0.78102 [0, -2, -1, -2, 0, -1, 0, 0, 0, -1] -nimq -0.2 0.6 [0, 0, 0, 0, 0, 0, 0, 0, -2, 0] -nimy -1.4 1.68523 [-1, -2, -3, -2, -1, 2, -3, 0, 0, -4] -nitl -1.5 0.92195 [-1, -1, -2, -3, -1, -3, -1, -2, 0, -1] -nme -2.1 1.13578 [-1, -2, -2, -1, -4, -2, -3, -3, 0, -3] -noyb -0.7 1.67631 [-1, -2, 0, -1, -1, -2, -2, -1, 4, -1] -np 1.4 1.0198 [0, 1, 1, 1, 1, 2, 2, 4, 1, 1] -ntmu 1.4 0.66332 [1, 1, 0, 1, 2, 2, 2, 2, 2, 1] -o-8 -0.5 1.5 [2, -1, 0, 0, -2, -2, 0, -2, 2, -2] -o-: -0.3 1.18743 [2, -1, 0, 0, -1, -2, 0, -2, 1, 0] -o-| -1.1 0.53852 [-1, -1, -1, 0, -1, -1, -1, -2, -2, -1] -o.o -0.6 0.8 [-1, -1, -2, 0, 1, 0, -1, 0, -1, -1] -O.o -0.6 0.8 [-1, -1, -2, 0, 1, 0, -1, 0, -1, -1] -o.O -0.6 0.8 [-1, -1, -2, 0, 1, 0, -1, 0, -1, -1] -o: -0.2 0.87178 [-1, 0, -1, -2, 0, 1, 0, 1, 0, 0] -o:) 1.5 0.67082 [3, 1, 1, 2, 2, 2, 1, 1, 1, 1] -o:-) 2.0 1.18322 [1, 4, 1, 2, 4, 1, 1, 2, 3, 1] -o:-3 2.2 0.9798 [1, 4, 2, 3, 3, 2, 1, 2, 3, 1] -o:3 2.3 0.78102 [3, 3, 2, 2, 1, 2, 4, 2, 2, 2] -o:< -0.3 1.1 [-1, -1, -2, 0, -1, 0, 1, 2, 0, -1] -o;^) 1.6 0.8 [1, 2, 1, 2, 1, 2, 2, 0, 3, 2] -ok 1.6 1.42829 [0, 0, 1, 1, 1, 4, 3, 4, 1, 1] -o_o -0.5 0.92195 [0, -1, 0, -2, -2, 0, -1, 1, 0, 0] -O_o -0.5 0.92195 [0, -1, 0, -2, -2, 0, -1, 1, 0, 0] -o_O -0.5 0.92195 [0, -1, 0, -2, -2, 0, -1, 1, 0, 0] -pita -2.4 1.2 [-2, -1, -1, -4, -4, -2, -4, -2, -3, -1] -pls 0.3 0.45826 [0, 1, 1, 1, 0, 0, 0, 0, 0, 0] -plz 0.3 0.45826 [0, 1, 1, 1, 0, 0, 0, 0, 0, 0] -pmbi 0.8 1.32665 [3, 0, 0, 1, 1, -2, 2, 2, 0, 1] -pmfji 0.3 0.78102 [0, 0, 1, 0, 2, -1, 0, 1, 0, 0] -pmji 0.7 1.00499 [1, 2, 0, -1, 0, 0, 2, 2, 1, 0] -po -2.6 0.91652 [-2, -3, -4, -3, -3, -3, -1, -3, -1, -3] -ptl 2.6 1.11355 [3, 4, 2, 4, 1, 2, 3, 1, 4, 2] -pu -1.1 1.3 [-3, -1, -3, -2, -1, -1, -1, -1, 1, 1] -qq -2.2 0.6 [-2, -2, -1, -3, -3, -2, -2, -3, -2, -2] -qt 1.8 0.6 [2, 2, 1, 2, 1, 3, 2, 1, 2, 2] -r&r 2.4 1.0198 [2, 4, 2, 3, 1, 4, 2, 2, 1, 3] -rofl 2.7 0.78102 [3, 2, 2, 2, 4, 4, 2, 3, 3, 2] -roflmao 2.5 1.11803 [4, 2, 2, 4, 1, 1, 2, 4, 3, 2] -rotfl 2.6 0.66332 [3, 2, 3, 3, 1, 3, 3, 3, 2, 3] -rotflmao 2.8 1.07703 [4, 3, 2, 4, 1, 1, 4, 3, 3, 3] -rotflmfao 2.5 1.11803 [3, 4, 1, 3, 3, 3, 0, 3, 2, 3] -rotflol 3.0 1.09545 [1, 4, 4, 4, 2, 2, 2, 3, 4, 4] -rotgl 2.9 0.7 [4, 3, 2, 2, 3, 3, 3, 2, 4, 3] -rotglmao 1.8 2.4 [3, 3, 4, 3, -1, 1, 4, -4, 2, 3] -s: -1.1 0.83066 [-1, -1, -2, -2, -1, -1, -2, -1, 1, -1] -sapfu -1.1 1.57797 [-2, 0, -3, -1, -1, 1, -2, 2, -2, -3] -sete 2.8 0.87178 [3, 3, 3, 2, 3, 3, 4, 4, 1, 2] -sfete 2.7 0.78102 [4, 3, 3, 3, 2, 4, 2, 2, 2, 2] -sgtm 2.4 1.0198 [2, 1, 1, 2, 3, 3, 2, 2, 4, 4] -slap 0.6 2.15407 [2, -1, 1, -1, 0, 4, -3, 4, 1, -1] -slaw 2.1 1.04403 [3, 2, 0, 2, 2, 2, 3, 1, 4, 2] -smh -1.3 0.64031 [-2, -1, 0, -1, -1, -2, -2, -1, -2, -1] -snafu -2.5 1.11803 [-3, -4, -3, -3, -1, 0, -2, -3, -3, -3] -sob -2.8 0.9798 [-3, -4, -3, -2, -2, -1, -2, -4, -4, -3] -swak 2.3 1.00499 [2, 2, 2, 1, 4, 2, 3, 2, 1, 4] -tgif 2.3 1.34536 [1, 3, 3, 3, -1, 2, 4, 2, 3, 3] -thks 1.4 0.4899 [1, 2, 1, 2, 1, 2, 1, 1, 2, 1] -thx 1.5 0.92195 [0, 1, 3, 2, 1, 2, 1, 1, 3, 1] -tia 2.3 0.9 [3, 1, 2, 1, 4, 3, 2, 3, 2, 2] -tmi -0.3 1.61555 [-1, -1, 2, -1, 1, -2, -2, -1, 3, -1] -tnx 1.1 0.53852 [2, 1, 1, 0, 1, 1, 2, 1, 1, 1] -true 1.8 1.32665 [2, 1, 1, 0, 1, 4, 3, 1, 4, 1] -tx 1.5 0.92195 [3, 2, 1, 0, 2, 1, 3, 1, 1, 1] -txs 1.1 0.7 [1, 2, 0, 1, 2, 0, 1, 2, 1, 1] -ty 1.6 0.66332 [1, 2, 3, 1, 2, 2, 1, 2, 1, 1] -tyvm 2.5 1.11803 [2, 2, 1, 3, 1, 4, 2, 4, 2, 4] -urw 1.9 1.13578 [1, 2, 1, 2, 4, 2, 4, 1, 1, 1] -vbg 2.1 1.75784 [2, 3, 3, 3, 3, -3, 3, 2, 2, 3] -vbs 3.1 0.53852 [2, 3, 3, 3, 4, 4, 3, 3, 3, 3] -vip 2.3 1.00499 [2, 1, 1, 3, 4, 2, 2, 4, 2, 2] -vwd 2.6 0.91652 [4, 2, 4, 2, 1, 3, 3, 2, 3, 2] -vwp 2.1 0.7 [3, 1, 2, 2, 3, 2, 2, 3, 1, 2] -wag -0.2 0.74833 [-1, 0, 0, 0, 0, 0, -2, 1, 0, 0] -wd 2.7 1.1 [3, 1, 4, 3, 4, 2, 1, 3, 2, 4] -wilco 0.9 0.9434 [1, 3, 1, 0, 1, 0, 2, 1, 0, 0] -wp 1.0 0.0 [1, 1, 1, 1, 1, 1, 1, 1, 1, 1] -wtf -2.8 0.74833 [-4, -3, -2, -3, -2, -2, -2, -4, -3, -3] -wtg 2.1 0.7 [1, 3, 2, 3, 2, 2, 2, 1, 2, 3] -wth -2.4 0.4899 [-2, -3, -2, -3, -2, -2, -2, -3, -3, -2] -x-d 2.7 0.78102 [1, 3, 4, 2, 3, 3, 3, 2, 3, 3] -x-p 1.8 0.87178 [2, 1, 3, 1, 3, 1, 3, 1, 2, 1] -xd 2.7 0.9 [1, 4, 4, 3, 2, 2, 3, 3, 2, 3] -xlnt 3.0 0.89443 [4, 3, 3, 1, 4, 4, 3, 3, 3, 2] -xoxo 3.0 0.7746 [2, 2, 4, 2, 3, 3, 4, 3, 3, 4] -xoxozzz 2.3 0.78102 [3, 1, 2, 2, 2, 2, 3, 2, 4, 2] -xp 1.2 0.4 [1, 1, 1, 1, 2, 1, 2, 1, 1, 1] -xqzt 1.6 1.42829 [0, 2, 1, 2, 4, -1, 3, 1, 1, 3] -xtc 0.8 1.93907 [2, 0, -3, 3, 3, -1, 3, 1, -1, 1] -yolo 1.1 0.83066 [0, 1, 1, 2, 1, 1, 1, 3, 0, 1] -yoyo 0.4 1.85472 [-1, 0, -1, -1, 4, 2, -2, 2, 2, -1] -yvw 1.6 0.4899 [1, 2, 1, 1, 2, 2, 2, 1, 2, 2] -yw 1.8 1.32665 [1, 1, 1, 4, 1, 1, 4, 0, 3, 2] -ywia 2.5 1.11803 [3, 2, 3, 4, 1, 1, 1, 3, 3, 4] -zzz -1.2 0.87178 [0, -1, 0, -1, -3, -1, -1, -2, -2, -1] -[-; 0.5 1.28452 [1, -1, -1, 1, 1, 1, 2, -2, 2, 1] -[: 1.3 0.45826 [1, 1, 2, 1, 2, 2, 1, 1, 1, 1] -[; 1.0 1.34164 [2, 1, 2, 2, 1, 2, 2, -2, -1, 1] -[= 1.7 0.64031 [2, 2, 1, 1, 1, 2, 2, 3, 2, 1] -\-: -1.0 1.18322 [-3, -1, -1, -1, -1, -1, 2, -2, -1, -1] -\: -1.0 0.0 [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1] -\:< -1.7 1.18743 [-1, -3, -2, -2, -3, -3, -2, -1, 1, -1] -\= -1.1 0.3 [-1, -1, -1, -1, -1, -1, -1, -2, -1, -1] -\^: -1.3 0.45826 [-1, -1, -1, -2, -1, -1, -1, -2, -2, -1] -\o/ 2.2 0.9798 [2, 1, 1, 2, 4, 2, 2, 4, 2, 2] -\o: -1.2 0.4 [-1, -1, -1, -1, -2, -1, -1, -2, -1, -1] -]-: -2.1 0.53852 [-2, -3, -3, -2, -2, -2, -1, -2, -2, -2] -]: -1.6 0.66332 [-1, -2, -1, -2, -3, -2, -1, -1, -1, -2] -]:< -2.5 0.80623 [-2, -2, -2, -3, -4, -2, -2, -2, -2, -4] -^<_< 1.4 1.11355 [3, 1, 3, 2, 1, 1, 1, -1, 2, 1] -^urs -2.8 0.6 [-2, -3, -3, -2, -3, -3, -2, -3, -4, -3] -abandon -1.9 0.53852 [-1, -2, -2, -2, -2, -3, -2, -2, -1, -2] -abandoned -2.0 1.09545 [-1, -1, -3, -2, -1, -4, -1, -3, -3, -1] -abandoner -1.9 0.83066 [-1, -1, -3, -2, -1, -3, -1, -2, -3, -2] -abandoners -1.9 0.83066 [-2, -3, -2, -3, -2, -1, -2, -2, 0, -2] -abandoning -1.6 0.8 [-3, -2, -3, -2, -1, -1, -1, -1, -1, -1] -abandonment -2.4 1.0198 [-4, -2, -1, -4, -2, -1, -2, -3, -3, -2] -abandonments -1.7 0.45826 [-2, -1, -2, -2, -1, -2, -1, -2, -2, -2] -abandons -1.3 0.9 [-2, -1, -1, -2, -1, -2, -1, -2, 1, -2] -abducted -2.3 1.18743 [-3, -1, 0, -3, -1, -3, -4, -2, -3, -3] -abduction -2.8 0.87178 [-4, -3, -3, -4, -1, -3, -2, -2, -3, -3] -abductions -2.0 1.41421 [-3, -4, -1, -3, -1, -3, 1, -2, -1, -3] -abhor -2.0 1.09545 [-3, -3, -1, -1, -2, -1, -3, -3, 0, -3] -abhorred -2.4 1.49666 [-4, -4, 0, -3, -2, -1, -4, -3, -3, 0] -abhorrent -3.1 1.3 [-4, -4, -4, -2, 0, -4, -2, -3, -4, -4] -abhors -2.9 1.51327 [0, -4, -3, -3, -4, -4, 0, -4, -3, -4] -abilities 1.0 0.63246 [1, 2, 0, 1, 0, 1, 1, 1, 1, 2] -ability 1.3 0.64031 [1, 1, 1, 0, 1, 2, 2, 2, 2, 1] -aboard 0.1 0.3 [0, 0, 0, 0, 1, 0, 0, 0, 0, 0] -absentee -1.1 0.53852 [-1, -1, 0, -2, -1, -1, -2, -1, -1, -1] -absentees -0.8 0.6 [-1, 0, 0, -1, -1, 0, -2, -1, -1, -1] -absolve 1.2 1.46969 [2, -3, 2, 2, 1, 1, 2, 1, 2, 2] -absolved 1.5 0.92195 [3, 1, 2, 1, 0, 2, 3, 1, 1, 1] -absolves 1.3 1.00499 [3, 1, 1, 0, 0, 2, 3, 1, 1, 1] -absolving 1.6 0.8 [3, 1, 2, 1, 1, 2, 3, 1, 1, 1] -abuse -3.2 0.6 [-4, -2, -3, -4, -3, -4, -3, -3, -3, -3] -abused -2.3 0.64031 [-2, -2, -3, -2, -2, -4, -2, -2, -2, -2] -abuser -2.6 0.4899 [-3, -2, -3, -3, -2, -3, -2, -2, -3, -3] -abusers -2.6 1.0198 [-2, -3, -3, -3, -3, -2, -3, -4, -3, 0] -abuses -2.6 0.66332 [-3, -2, -3, -3, -3, -3, -1, -2, -3, -3] -abusing -2.0 1.41421 [-1, -2, -2, -4, -4, -2, -3, -1, 1, -2] -abusive -3.2 0.74833 [-4, -3, -3, -4, -4, -3, -4, -2, -3, -2] -abusively -2.8 0.6 [-3, -4, -3, -2, -3, -2, -2, -3, -3, -3] -abusiveness -2.5 0.92195 [-2, -4, -2, -3, -2, -3, -4, -2, -1, -2] -abusivenesses -3.0 0.63246 [-3, -3, -4, -3, -4, -2, -2, -3, -3, -3] -accept 1.6 0.91652 [2, 1, 2, 1, 1, 2, 4, 1, 1, 1] -acceptabilities 1.6 0.66332 [0, 2, 2, 2, 1, 2, 2, 2, 1, 2] -acceptability 1.1 0.53852 [1, 0, 1, 2, 1, 2, 1, 1, 1, 1] -acceptable 1.3 0.45826 [1, 2, 1, 1, 1, 2, 1, 1, 2, 1] -acceptableness 1.3 0.9 [1, 0, 2, 1, 2, 1, 1, 0, 2, 3] -acceptably 1.5 0.67082 [3, 2, 1, 1, 1, 2, 1, 1, 2, 1] -acceptance 2.0 0.63246 [3, 1, 3, 2, 1, 2, 2, 2, 2, 2] -acceptances 1.7 0.78102 [3, 1, 1, 1, 2, 2, 1, 2, 3, 1] -acceptant 1.6 0.8 [0, 1, 2, 2, 2, 1, 2, 1, 3, 2] -acceptation 1.3 0.78102 [0, 1, 2, 1, 1, 1, 1, 3, 2, 1] -acceptations 0.9 0.83066 [1, 2, 0, 2, 0, 1, 0, 2, 1, 0] -accepted 1.1 0.3 [1, 1, 1, 1, 1, 2, 1, 1, 1, 1] -accepting 1.6 0.66332 [2, 2, 2, 1, 1, 2, 1, 3, 1, 1] -accepts 1.3 0.45826 [1, 2, 1, 1, 1, 2, 2, 1, 1, 1] -accident -2.1 0.83066 [-2, -2, -1, -3, -4, -2, -2, -1, -2, -2] -accidental -0.3 0.45826 [-1, -1, 0, 0, 0, 0, 0, 0, -1, 0] -accidentally -1.4 0.91652 [-2, 0, -2, 0, -3, -1, -1, -1, -2, -2] -accidents -1.3 0.78102 [-1, -1, -1, -1, -2, 0, -3, -1, -2, -1] -accomplish 1.8 0.6 [1, 2, 3, 2, 2, 2, 1, 1, 2, 2] -accomplished 1.9 0.53852 [2, 2, 2, 1, 2, 2, 3, 1, 2, 2] -accomplishes 1.7 0.9 [2, 2, 1, 0, 2, 3, 3, 1, 1, 2] -accusation -1.0 1.09545 [-1, -1, -2, -2, -2, -1, -1, -1, 2, -1] -accusations -1.3 1.26886 [-2, -2, -1, -3, -2, -1, -1, 2, -2, -1] -accuse -0.8 1.53623 [-3, -1, -1, -2, 1, -2, 1, -2, 2, -1] -accused -1.2 1.46969 [-2, -1, -2, 2, -2, -3, -2, -2, -1, 1] -accuses -1.4 1.0198 [-2, -1, -2, 1, -2, -3, -1, -2, -1, -1] -accusing -0.7 1.34536 [-2, -1, -1, 1, -3, -1, -1, 2, -1, 0] -ache -1.6 1.2 [-1, -2, -2, -2, -1, -4, -1, 1, -2, -2] -ached -1.6 0.8 [-2, -2, -1, -2, -1, -2, -3, 0, -1, -2] -aches -1.0 0.7746 [-1, -2, -1, -1, -1, 1, -2, -1, -1, -1] -achievable 1.3 0.45826 [2, 1, 1, 1, 1, 1, 1, 2, 2, 1] -aching -2.2 0.74833 [-2, -3, -2, -1, -3, -3, -2, -3, -1, -2] -acquit 0.8 1.72047 [-3, 3, -1, 3, 2, 1, 1, 1, 0, 1] -acquits 0.1 1.37477 [1, -3, -1, 0, 2, 0, -1, 1, 1, 1] -acquitted 1.0 0.89443 [2, 2, 1, 1, 2, 0, 1, 1, -1, 1] -acquitting 1.3 0.78102 [3, 2, 0, 1, 1, 1, 2, 1, 1, 1] -acrimonious -1.7 1.73494 [-1, -3, -2, -3, 3, -3, -1, -2, -2, -3] -active 1.7 1.26886 [1, 2, 1, 1, 1, 4, 2, 4, 0, 1] -actively 1.3 0.78102 [0, 1, 0, 2, 2, 1, 1, 2, 2, 2] -activeness 0.6 0.8 [0, 2, 0, 0, 1, 0, 1, 0, 2, 0] -activenesses 0.8 0.74833 [2, 0, 1, 0, 0, 0, 1, 2, 1, 1] -actives 1.1 0.7 [2, 1, 0, 1, 1, 0, 1, 1, 2, 2] -adequate 0.9 0.7 [0, 0, 1, 1, 0, 2, 1, 1, 2, 1] -admirability 2.4 0.4899 [2, 3, 3, 3, 3, 2, 2, 2, 2, 2] -admirable 2.6 0.66332 [2, 3, 3, 3, 4, 3, 2, 2, 2, 2] -admirableness 2.2 0.87178 [2, 2, 3, 3, 3, 1, 3, 1, 3, 1] -admirably 2.5 0.67082 [2, 3, 3, 3, 4, 2, 2, 2, 2, 2] -admiral 1.3 1.18743 [0, 0, 1, 3, 3, 2, 2, 0, 2, 0] -admirals 1.5 0.80623 [2, 2, 0, 2, 2, 0, 1, 2, 2, 2] -admiralties 1.6 0.66332 [2, 2, 2, 1, 0, 2, 2, 2, 1, 2] -admiralty 1.2 1.53623 [0, 4, 0, 0, 0, 2, 2, 3, 2, -1] -admiration 2.5 0.80623 [3, 1, 1, 3, 3, 2, 3, 3, 3, 3] -admirations 1.6 0.66332 [2, 2, 1, 1, 2, 2, 2, 2, 2, 0] -admire 2.1 0.83066 [3, 3, 1, 3, 3, 2, 1, 2, 1, 2] -admired 2.3 0.78102 [4, 2, 2, 2, 2, 2, 3, 3, 1, 2] -admirer 1.8 0.74833 [2, 1, 1, 2, 3, 2, 3, 1, 1, 2] -admirers 1.7 1.00499 [2, 3, 2, 2, 2, 1, -1, 2, 2, 2] -admires 1.5 0.67082 [3, 1, 1, 2, 1, 2, 2, 1, 1, 1] -admiring 1.6 0.8 [1, 2, 1, 1, 3, 3, 2, 1, 1, 1] -admiringly 2.3 0.64031 [1, 3, 3, 2, 2, 2, 2, 3, 3, 2] -admit 0.8 1.07703 [0, 0, 0, 0, 0, 1, 3, 2, 2, 0] -admits 1.2 0.87178 [1, 2, 2, 2, 0, 0, 1, 2, 0, 2] -admitted 0.4 0.66332 [0, 1, 0, 1, 0, 0, 2, 0, 0, 0] -admonished -1.9 0.9434 [-2, -2, -2, -1, -2, -3, -1, -1, -1, -4] -adopt 0.7 0.64031 [0, 0, 1, 1, 1, 0, 1, 0, 1, 2] -adopts 0.7 0.64031 [0, 0, 1, 2, 1, 0, 1, 1, 0, 1] -adorability 2.2 0.74833 [2, 2, 2, 2, 1, 2, 3, 2, 4, 2] -adorable 2.2 0.6 [3, 2, 2, 3, 2, 2, 1, 3, 2, 2] -adorableness 2.5 0.67082 [2, 3, 3, 2, 3, 2, 1, 3, 3, 3] -adorably 2.1 0.7 [3, 1, 2, 3, 2, 2, 1, 3, 2, 2] -adoration 2.9 0.7 [3, 3, 3, 2, 3, 3, 4, 2, 4, 2] -adorations 2.2 0.87178 [2, 2, 3, 1, 3, 1, 3, 3, 1, 3] -adore 2.6 0.91652 [3, 3, 1, 2, 3, 3, 3, 4, 1, 3] -adored 1.8 0.87178 [2, 3, 3, 2, 2, 1, 1, 0, 2, 2] -adorer 1.7 1.1 [2, 4, 3, 1, 2, 1, 1, 0, 2, 1] -adorers 2.1 0.7 [3, 2, 1, 2, 2, 2, 3, 2, 3, 1] -adores 1.6 0.66332 [2, 1, 3, 2, 2, 1, 1, 1, 2, 1] -adoring 2.6 0.66332 [2, 3, 3, 3, 1, 3, 3, 2, 3, 3] -adoringly 2.4 0.8 [2, 3, 2, 3, 3, 3, 3, 1, 1, 3] -adorn 0.9 0.53852 [1, 1, 1, 0, 2, 1, 1, 0, 1, 1] -adorned 0.8 1.249 [1, 1, 0, 2, -1, 3, -1, 2, 1, 0] -adorner 1.3 0.78102 [1, 1, 1, 2, 1, 3, 1, 2, 1, 0] -adorners 0.9 0.9434 [2, 2, 0, 1, -1, 2, 1, 1, 0, 1] -adorning 1.0 0.7746 [0, 0, 1, 1, 1, 2, 2, 1, 0, 2] -adornment 1.3 0.78102 [1, 3, 1, 0, 2, 2, 1, 1, 1, 1] -adornments 0.8 1.16619 [2, -1, 0, 0, 2, 1, 2, -1, 1, 2] -adorns 0.5 1.56525 [3, -1, 1, 0, 2, -1, 3, -1, 0, -1] -advanced 1.0 0.63246 [1, 0, 1, 1, 1, 0, 1, 2, 1, 2] -advantage 1.0 0.63246 [1, 2, 1, 1, 2, 0, 1, 0, 1, 1] -advantaged 1.4 0.91652 [1, 0, 3, 0, 1, 1, 2, 2, 2, 2] -advantageous 1.5 0.67082 [2, 0, 2, 2, 2, 1, 1, 1, 2, 2] -advantageously 1.9 0.53852 [2, 2, 2, 3, 2, 2, 2, 1, 1, 2] -advantageousness 1.6 1.28062 [-2, 2, 3, 1, 2, 2, 2, 2, 2, 2] -advantages 1.5 0.80623 [1, 0, 3, 1, 1, 1, 2, 2, 2, 2] -advantaging 1.6 0.66332 [3, 1, 1, 2, 1, 1, 2, 2, 2, 1] -adventure 1.3 0.45826 [1, 2, 1, 1, 2, 1, 1, 1, 1, 2] -adventured 1.3 0.45826 [1, 2, 1, 2, 1, 2, 1, 1, 1, 1] -adventurer 1.2 0.6 [1, 2, 0, 2, 1, 2, 1, 1, 1, 1] -adventurers 0.9 0.9434 [0, 1, 0, 1, 0, 1, 0, 1, 3, 2] -adventures 1.4 1.2 [2, 2, 1, 2, -2, 2, 2, 1, 2, 2] -adventuresome 1.7 1.1 [0, 3, 0, 1, 2, 2, 3, 1, 2, 3] -adventuresomeness 1.3 1.00499 [1, 0, 0, 2, 3, 2, 2, 0, 1, 2] -adventuress 0.8 1.72047 [3, -1, 2, 2, 0, 0, 1, 2, -3, 2] -adventuresses 1.4 1.11355 [1, 0, 0, 3, 2, 2, 3, 0, 1, 2] -adventuring 2.3 0.78102 [2, 3, 2, 3, 1, 3, 3, 1, 2, 3] -adventurism 1.5 0.67082 [1, 0, 2, 2, 2, 2, 1, 1, 2, 2] -adventurist 1.4 0.4899 [1, 1, 2, 1, 2, 2, 2, 1, 1, 1] -adventuristic 1.7 0.64031 [2, 1, 1, 2, 2, 1, 3, 2, 2, 1] -adventurists 1.2 0.9798 [3, 1, 0, 0, 1, 2, 1, 0, 2, 2] -adventurous 1.4 1.11355 [0, 1, 2, 1, 2, 0, 3, 2, 3, 0] -adventurously 1.3 0.9 [0, 1, 2, 2, 1, 2, 1, 1, 0, 3] -adventurousness 1.8 0.87178 [0, 1, 3, 2, 1, 3, 2, 2, 2, 2] -adversarial -1.5 0.92195 [-2, 0, -1, -3, -2, -2, 0, -1, -2, -2] -adversaries -1.0 0.63246 [-1, -1, -1, -1, 0, -2, -2, -1, -1, 0] -adversary -0.8 1.72047 [-3, -1, -2, -2, -2, 2, 1, -1, 2, -2] -adversative -1.2 0.74833 [-1, -1, -2, -1, -1, -1, -3, -1, 0, -1] -adversatively -0.1 1.37477 [0, -2, -1, 0, -1, -1, 1, 1, 3, -1] -adversatives -1.0 0.7746 [-1, -1, -2, -1, -2, 1, -1, -1, -1, -1] -adverse -1.5 0.80623 [-2, -2, -2, -1, -1, 0, -1, -3, -1, -2] -adversely -0.8 1.6 [-2, -2, 0, -2, -2, 2, -2, 2, -2, 0] -adverseness -0.6 1.35647 [-1, -2, -1, 2, -1, -2, -1, 2, -1, -1] -adversities -1.5 0.67082 [-2, -2, -1, -1, -2, 0, -2, -1, -2, -2] -adversity -1.8 0.6 [-3, -2, -1, -2, -2, -2, -1, -1, -2, -2] -affected -0.6 1.35647 [-1, -2, 0, -2, 0, 0, 2, -2, 1, -2] -affection 2.4 0.8 [3, 2, 2, 3, 4, 1, 3, 2, 2, 2] -affectional 1.9 1.04403 [3, 3, 2, 0, 2, 2, 2, 3, 2, 0] -affectionally 1.5 0.92195 [1, 1, 3, 1, 1, 0, 2, 2, 3, 1] -affectionate 1.9 1.13578 [1, 0, 3, 1, 3, 2, 2, 1, 2, 4] -affectionately 2.2 0.87178 [4, 1, 1, 2, 2, 2, 3, 3, 2, 2] -affectioned 1.8 0.4 [2, 2, 1, 2, 2, 1, 2, 2, 2, 2] -affectionless -2.0 0.44721 [-2, -1, -2, -2, -2, -2, -2, -2, -2, -3] -affections 1.5 1.11803 [-1, 3, 2, 2, 1, 1, 2, 1, 3, 1] -afflicted -1.5 1.0247 [-1, -2, -3, -2, 1, -1, -1, -2, -2, -2] -affronted 0.2 2.03961 [1, -2, 2, -2, -2, 4, 0, 2, 1, -2] -aggravate -2.5 0.80623 [-3, -3, -2, -3, -2, -4, -3, -2, -2, -1] -aggravated -1.9 1.04403 [-4, -3, -3, -1, -1, -1, -1, -2, -2, -1] -aggravates -1.9 0.83066 [-3, -2, -2, -2, -3, -1, -2, -2, 0, -2] -aggravating -1.2 0.9798 [-2, -2, -1, -2, -2, -1, 0, 1, -1, -2] -aggress -1.3 1.55242 [-2, -2, 2, -2, -1, -3, -3, -1, 1, -2] -aggressed -1.4 0.4899 [-1, -1, -1, -1, -2, -1, -2, -2, -2, -1] -aggresses -0.5 1.43178 [-1, -2, -1, -1, -3, 0, -1, 1, 2, 1] -aggressing -0.6 1.28062 [-1, -2, -1, 0, -1, -2, 2, -2, 1, 0] -aggression -1.2 1.77764 [-2, -2, 1, 1, -4, 2, -2, -2, -2, -2] -aggressions -1.3 1.48661 [-1, -2, -2, -2, -2, -3, 1, -2, 2, -2] -aggressive -0.6 1.28062 [-2, 1, -2, -2, 0, -2, -1, 1, 1, 0] -aggressively -1.3 1.55242 [-1, -2, 3, -2, -3, -2, -1, -1, -2, -2] -aggressiveness -1.8 0.74833 [-1, -2, -1, -2, -2, -1, -3, -1, -3, -2] -aggressivities -1.4 1.28062 [-1, -1, -1, -2, 2, -2, -2, -2, -3, -2] -aggressivity -0.6 1.35647 [-3, -1, 1, 0, 0, 0, -3, -1, 1, 0] -aggressor -0.8 1.32665 [-2, 0, -1, 2, -2, -2, -1, -1, -2, 1] -aggressors -0.9 1.13578 [-2, -2, -1, -1, -1, 1, 1, 0, -2, -2] -aghast -1.9 1.04403 [-2, -3, -1, 0, -2, -1, -4, -2, -2, -2] -agitate -1.7 0.64031 [-2, -2, -3, -1, -1, -1, -2, -1, -2, -2] -agitated -2.0 0.63246 [-2, -2, -2, -2, -1, -3, -3, -2, -2, -1] -agitatedly -1.6 0.8 [-1, -2, -1, -3, -1, -3, -1, -1, -2, -1] -agitates -1.4 0.8 [-2, 0, -1, -2, -1, -1, -3, -1, -2, -1] -agitating -1.8 0.87178 [-2, -1, -1, -1, -2, -3, -1, -3, -3, -1] -agitation -1.0 1.09545 [-2, -1, 1, -1, -2, -1, -2, -1, 1, -2] -agitational -1.2 1.66132 [-3, -3, -2, 1, -1, -2, 0, 2, -1, -3] -agitations -1.3 1.18743 [-1, -2, -1, -3, -2, -3, 0, -1, 1, -1] -agitative -1.3 1.26886 [-2, -2, -1, -2, -1, -3, 1, -2, 1, -2] -agitato -0.1 1.13578 [1, 2, 0, 0, 0, 0, -2, 0, -2, 0] -agitator -1.4 0.8 [-1, -1, -1, -2, -1, -1, -2, -3, -2, 0] -agitators -2.1 0.9434 [-2, -3, -3, -2, -2, -1, -3, -2, 0, -3] -agog 1.9 0.7 [2, 1, 3, 3, 2, 1, 2, 2, 1, 2] -agonise -2.1 0.9434 [-3, -3, -2, -3, -1, -3, -1, -3, -1, -1] -agonised -2.3 0.64031 [-2, -3, -3, -2, -2, -2, -2, -3, -1, -3] -agonises -2.4 0.91652 [-1, -4, -3, -3, -2, -2, -2, -3, -1, -3] -agonising -1.5 1.43178 [-3, -2, -3, -3, -1, 1, 0, 0, -1, -3] -agonize -2.3 0.9 [-2, -3, -1, -2, -2, -2, -4, -1, -3, -3] -agonized -2.2 1.249 [-2, -3, -3, -3, -3, -2, -1, -3, 1, -3] -agonizes -2.3 1.18743 [-1, -3, -4, -3, -3, -2, -1, -3, 0, -3] -agonizing -2.7 0.78102 [-3, -2, -2, -2, -4, -3, -3, -2, -4, -2] -agonizingly -2.3 1.48661 [-3, -1, -3, -4, -4, -2, -3, 1, -1, -3] -agony -1.8 1.16619 [-3, -1, -2, -4, -2, -1, 0, -3, -1, -1] -agree 1.5 1.11803 [1, 0, 3, 1, 2, 1, 4, 1, 1, 1] -agreeability 1.9 1.04403 [1, 1, 1, 3, 3, 2, 1, 2, 4, 1] -agreeable 1.8 0.4 [2, 1, 2, 1, 2, 2, 2, 2, 2, 2] -agreeableness 1.8 0.9798 [2, 3, 2, 1, 1, 1, 4, 1, 2, 1] -agreeablenesses 1.3 0.45826 [2, 1, 1, 2, 1, 2, 1, 1, 1, 1] -agreeably 1.6 0.4899 [1, 1, 2, 1, 1, 2, 2, 2, 2, 2] -agreed 1.1 0.53852 [1, 1, 2, 1, 1, 2, 1, 0, 1, 1] -agreeing 1.4 0.4899 [1, 1, 1, 1, 2, 1, 1, 2, 2, 2] -agreement 2.2 0.74833 [2, 1, 1, 3, 3, 3, 2, 2, 2, 3] -agreements 1.1 1.13578 [0, 1, 0, 1, 1, 2, 1, 0, 4, 1] -agrees 0.8 1.4 [1, 1, 1, 1, 3, 1, -3, 1, 1, 1] -alarm -1.4 0.91652 [-1, -1, -2, -2, -2, -2, -1, 1, -2, -2] -alarmed -1.4 0.4899 [-2, -1, -2, -2, -1, -1, -1, -2, -1, -1] -alarming -0.5 1.62788 [-1, 1, -1, 1, -3, 1, -2, -3, 1, 1] -alarmingly -2.6 0.91652 [-3, -3, -4, -3, -2, -1, -3, -3, -1, -3] -alarmism -0.3 1.26886 [-2, 0, -2, -1, 0, 1, 1, -1, 2, -1] -alarmists -1.1 1.3 [-1, -2, -3, -2, -1, -2, 1, 1, 0, -2] -alarms -1.1 1.04403 [-2, 0, -2, -1, 0, 0, 0, -1, -2, -3] -alas -1.1 1.22066 [-1, -2, -1, 0, -1, 0, 1, -3, -1, -3] -alert 1.2 0.87178 [1, 2, 0, 1, 0, 2, 2, 0, 2, 2] -alienation -1.1 1.51327 [-3, -2, -3, -1, -2, -1, 2, -1, 1, -1] -alive 1.6 0.8 [1, 1, 2, 3, 3, 2, 1, 1, 1, 1] -allergic -1.2 0.4 [-1, -2, -1, -2, -1, -1, -1, -1, -1, -1] -allow 0.9 0.83066 [0, 0, 0, 1, 2, 2, 1, 1, 2, 0] -alone -1.0 0.63246 [-2, -1, -1, -1, -2, -1, 0, -1, -1, 0] -alright 1.0 0.7746 [0, 1, 0, 3, 1, 1, 1, 1, 1, 1] -amaze 2.5 1.0247 [3, 2, 3, 4, 2, 3, 1, 4, 2, 1] -amazed 2.2 1.07703 [1, 0, 3, 2, 2, 4, 3, 3, 2, 2] -amazedly 2.1 0.53852 [2, 2, 2, 2, 3, 2, 2, 3, 1, 2] -amazement 2.5 0.80623 [3, 3, 2, 4, 1, 2, 2, 3, 2, 3] -amazements 2.2 0.87178 [3, 1, 1, 3, 3, 2, 1, 2, 3, 3] -amazes 2.2 0.9798 [1, 0, 3, 2, 2, 3, 3, 3, 2, 3] -amazing 2.8 0.87178 [1, 4, 3, 2, 4, 2, 3, 3, 3, 3] -amazon 0.7 0.64031 [0, 1, 1, 0, 1, 0, 1, 0, 1, 2] -amazonite 0.2 0.6 [0, 0, 2, 0, 0, 0, 0, 0, 0, 0] -amazons -0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 0, -1, 0] -amazonstone 1.0 1.61245 [0, 0, 0, 0, 4, 4, 2, 0, 0, 0] -amazonstones 0.2 0.6 [0, 0, 0, 0, 0, 0, 0, 0, 2, 0] -ambitious 2.1 0.53852 [2, 3, 2, 2, 2, 2, 2, 2, 3, 1] -ambivalent 0.5 0.92195 [0, 0, -1, 2, 1, 1, 1, -1, 1, 1] -amor 3.0 0.63246 [3, 3, 2, 4, 3, 2, 4, 3, 3, 3] -amoral -1.6 0.66332 [-1, -2, 0, -2, -2, -2, -2, -2, -1, -2] -amoralism -0.7 1.34536 [-2, -1, -2, 0, 0, -3, 2, 0, -1, 0] -amoralisms -0.7 1.00499 [-2, 0, 1, -1, -2, -1, -1, 1, -1, -1] -amoralities -1.2 1.6 [-3, 0, 0, -2, 1, -1, 0, -4, -3, 0] -amorality -1.5 0.92195 [0, -1, -1, -2, -1, -3, -1, -3, -2, -1] -amorally -1.0 1.61245 [-2, 0, 1, -4, -1, 1, 1, -2, -2, -2] -amoretti 0.2 0.4 [0, 0, 0, 1, 0, 0, 0, 0, 0, 1] -amoretto 0.6 0.8 [0, 1, 0, 1, 0, 0, 2, 0, 0, 2] -amorettos 0.3 0.64031 [0, 1, 0, 1, 0, 0, 0, 1, 1, -1] -amorino 1.2 0.87178 [2, 1, 1, 0, 3, 1, 1, 0, 1, 2] -amorist 1.6 1.0198 [3, 0, 0, 2, 2, 1, 3, 1, 2, 2] -amoristic 1.0 1.67332 [1, 0, 2, 3, -1, 3, 1, 3, 0, -2] -amorists 0.1 0.9434 [0, 2, 0, 0, 1, 0, -2, 0, 0, 0] -amoroso 2.3 0.78102 [3, 1, 1, 2, 3, 3, 3, 3, 2, 2] -amorous 1.8 0.9798 [3, 1, 2, 2, 1, 1, 3, 0, 2, 3] -amorously 2.3 0.78102 [1, 1, 3, 2, 3, 3, 2, 3, 2, 3] -amorousness 2.0 0.89443 [2, 3, 1, 2, 0, 2, 2, 3, 3, 2] -amorphous -0.2 0.4 [0, 0, 0, 0, 0, 0, -1, 0, 0, -1] -amorphously 0.1 0.7 [-1, 0, 0, 0, 0, 0, 2, 0, 0, 0] -amorphousness 0.3 0.45826 [0, 0, 0, 0, 0, 1, 1, 1, 0, 0] -amort -2.1 0.83066 [-3, -1, -2, -2, -2, -2, -2, -4, -1, -2] -amortise 0.5 1.43178 [0, 1, 1, 0, -3, 2, 0, 0, 2, 2] -amortised -0.2 1.16619 [-1, -3, 0, 0, 0, 2, 0, 0, 0, 0] -amortises 0.1 0.83066 [-1, -1, 0, 0, 0, 2, 1, 0, 0, 0] -amortizable 0.5 1.0247 [2, 0, 1, 0, 1, 1, -2, 1, 0, 1] -amortization 0.6 1.0198 [0, 0, 0, 0, 1, 0, 0, 0, 3, 2] -amortizations 0.2 1.07703 [-1, 1, 0, 0, 1, 0, 2, 1, -2, 0] -amortize -0.1 1.04403 [0, 0, 0, 0, 2, -2, -1, 1, -1, 0] -amortized 0.8 0.74833 [0, 2, 0, 0, 1, 1, 1, 0, 1, 2] -amortizes 0.6 0.8 [0, 2, 0, 0, 1, 1, 0, 0, 0, 2] -amortizing 0.8 1.249 [0, 3, 0, 0, 0, 0, 0, 0, 3, 2] -amusable 0.7 1.18743 [2, 1, 1, 1, 1, 1, 2, -2, -1, 1] -amuse 1.7 0.78102 [1, 2, 1, 1, 2, 1, 1, 3, 3, 2] -amused 1.8 0.6 [1, 2, 2, 2, 2, 2, 1, 2, 3, 1] -amusedly 2.2 0.74833 [3, 3, 2, 2, 3, 2, 2, 3, 1, 1] -amusement 1.5 1.11803 [3, 2, 3, 1, 2, 2, -1, 1, 1, 1] -amusements 1.5 1.0247 [2, 1, 2, 1, 2, 2, 3, -1, 2, 1] -amuser 1.1 1.7 [2, 1, -3, 2, 2, 3, -1, 1, 2, 2] -amusers 1.3 0.45826 [1, 1, 2, 1, 2, 1, 2, 1, 1, 1] -amuses 1.7 0.64031 [1, 2, 1, 2, 2, 2, 1, 2, 3, 1] -amusia 0.3 1.48661 [0, -1, 1, -1, 2, 2, -1, -1, -1, 3] -amusias -0.4 0.66332 [-1, 0, 0, 1, 0, 0, -1, -1, -1, -1] -amusing 1.6 0.91652 [2, 2, 2, -1, 2, 2, 1, 2, 2, 2] -amusingly 0.8 1.249 [1, 2, 1, 1, 1, 2, 2, -2, -1, 1] -amusingness 1.8 0.6 [1, 2, 3, 2, 1, 2, 2, 1, 2, 2] -amusive 1.7 1.1 [3, 1, 3, 1, 2, 2, 2, 2, -1, 2] -anger -2.7 1.18743 [-1, -2, -3, -2, -4, -4, -2, -1, -4, -4] -angered -2.3 0.78102 [-2, -3, -2, -4, -2, -2, -3, -2, -2, -1] -angering -2.2 0.6 [-3, -2, -1, -3, -2, -2, -3, -2, -2, -2] -angerly -1.9 0.53852 [-2, -2, -1, -1, -3, -2, -2, -2, -2, -2] -angers -2.3 0.9 [-3, -1, -2, -3, -2, -2, -4, -1, -3, -2] -angrier -2.3 0.64031 [-2, -3, -2, -3, -1, -3, -2, -3, -2, -2] -angriest -3.1 0.83066 [-4, -3, -2, -2, -2, -4, -3, -4, -4, -3] -angrily -1.8 0.4 [-2, -1, -2, -2, -2, -1, -2, -2, -2, -2] -angriness -1.7 0.64031 [-2, 0, -2, -2, -1, -2, -2, -2, -2, -2] -angry -2.3 0.9 [-2, -2, -1, -3, -1, -2, -4, -2, -3, -3] -anguish -2.9 0.83066 [-3, -3, -2, -3, -4, -1, -3, -3, -4, -3] -anguished -1.8 1.4 [-3, -4, -1, -3, -2, -1, -1, 1, -1, -3] -anguishes -2.1 1.44568 [-4, -4, -2, -3, 1, -2, -1, -1, -2, -3] -anguishing -2.7 0.9 [-2, -2, -1, -3, -2, -4, -4, -3, -3, -3] -animosity -1.9 1.75784 [-2, -3, -3, -3, -2, 2, 1, -3, -3, -3] -annoy -1.9 0.53852 [-2, -2, -1, -2, -2, -1, -2, -2, -2, -3] -annoyance -1.3 1.55242 [-2, -3, -2, -2, -1, 1, -3, -2, 2, -1] -annoyances -1.8 0.6 [-2, -2, -2, -1, -1, -2, -3, -1, -2, -2] -annoyed -1.6 1.11355 [-3, -1, 1, -3, -1, -1, -2, -2, -2, -2] -annoyer -2.2 0.87178 [-3, -2, -1, -3, -2, -4, -2, -1, -2, -2] -annoyers -1.5 1.0247 [-2, -1, -2, -3, -2, -1, -1, -2, 1, -2] -annoying -1.7 0.64031 [-1, -2, -1, -2, -1, -1, -2, -2, -3, -2] -annoys -1.8 0.6 [-1, -2, -3, -2, -2, -2, -1, -2, -1, -2] -antagonism -1.9 1.04403 [-1, -1, -3, -2, -4, -2, -2, 0, -2, -2] -antagonisms -1.2 1.53623 [0, -2, -2, -2, -2, -2, 3, -2, -1, -2] -antagonist -1.9 0.7 [-3, -1, -2, -3, -2, -2, -1, -2, -2, -1] -antagonistic -1.7 0.9 [-2, -2, -2, 1, -2, -2, -2, -2, -2, -2] -antagonistically -2.2 0.87178 [-2, -3, -4, -2, -2, -3, -2, -2, -1, -1] -antagonists -1.7 0.64031 [-2, -1, -1, -2, -1, -2, -2, -3, -1, -2] -antagonize -2.0 0.44721 [-2, -2, -2, -3, -2, -1, -2, -2, -2, -2] -antagonized -1.4 0.66332 [-2, -1, -2, -2, -1, 0, -2, -1, -1, -2] -antagonizes -0.5 1.9105 [-2, 4, -2, -2, 1, 0, -2, 1, -1, -2] -antagonizing -2.7 0.64031 [-4, -2, -2, -3, -2, -3, -3, -2, -3, -3] -anti -1.3 0.78102 [0, -2, -3, -1, -1, -2, -1, -1, -1, -1] -anticipation 0.4 1.28062 [1, 1, -1, 0, -1, 1, 1, 2, -2, 2] -anxieties -0.6 1.85472 [-2, -3, -3, -2, -1, 2, -1, 1, 1, 2] -anxiety -0.7 2.1 [-2, -2, -2, -3, 3, -1, -3, 2, 2, -1] -anxious -1.0 0.44721 [-1, -2, -1, -1, 0, -1, -1, -1, -1, -1] -anxiously -0.9 0.83066 [-1, -1, -2, -1, -1, -1, -1, 0, 1, -2] -anxiousness -1.0 1.48324 [-2, -1, -1, -1, -1, -2, 3, -3, -1, -1] -aok 2.0 0.89443 [2, 3, 2, 1, 2, 1, 1, 4, 2, 2] -apathetic -1.2 0.87178 [-1, -1, 0, -2, -2, -1, -1, 0, -3, -1] -apathetically -0.4 1.28062 [-1, -1, 0, -1, -2, 2, -1, -1, 2, -1] -apathies -0.6 1.0198 [-1, -1, -1, -2, 0, 1, -1, -2, 1, 0] -apathy -1.2 1.32665 [-2, -2, -1, 1, -1, -3, -1, 1, -1, -3] -apeshit -0.9 2.21133 [-4, -3, 2, -3, -2, -3, 1, 0, 2, 1] -apocalyptic -3.4 0.66332 [-4, -2, -3, -4, -3, -4, -4, -3, -3, -4] -apologise 1.6 0.66332 [2, 3, 2, 2, 1, 1, 2, 1, 1, 1] -apologised 0.4 0.91652 [-1, 0, 2, 0, 0, 1, 0, 2, 0, 0] -apologises 0.8 1.07703 [2, 0, 2, 0, 0, 1, 0, 3, 0, 0] -apologising 0.2 1.6 [0, -1, -1, 2, 2, 1, -2, -1, 3, -1] -apologize 0.4 0.8 [1, -1, 0, 1, 1, 1, -1, 1, 0, 1] -apologized 1.3 0.64031 [1, 1, 1, 2, 0, 2, 1, 2, 2, 1] -apologizes 1.5 0.80623 [2, 1, 1, 2, 0, 2, 1, 2, 3, 1] -apologizing -0.3 1.34536 [1, 2, -1, 1, -1, 0, -3, 0, -1, -1] -apology 0.2 1.249 [1, 1, 1, 1, -1, 1, -1, -1, -2, 2] -appall -2.4 0.66332 [-3, -2, -2, -3, -2, -3, -1, -3, -2, -3] -appalled -2.0 0.63246 [-3, -2, -3, -2, -2, -1, -1, -2, -2, -2] -appalling -1.5 1.5 [-2, -4, 1, -1, 1, -1, -2, -3, -2, -2] -appallingly -2.0 1.67332 [-3, -2, 0, -2, 2, -3, -4, -3, -2, -3] -appalls -1.9 1.37477 [0, -3, -2, -3, -3, -2, -1, -3, 1, -3] -appease 1.1 0.9434 [1, 1, 1, -1, 2, 0, 1, 2, 2, 2] -appeased 0.9 0.53852 [0, 1, 1, 1, 1, 1, 0, 1, 2, 1] -appeases 0.9 0.53852 [0, 1, 1, 1, 1, 1, 0, 1, 2, 1] -appeasing 1.0 1.09545 [1, 2, -1, 1, 2, 1, 2, 2, 1, -1] -applaud 2.0 0.63246 [3, 2, 2, 2, 1, 2, 3, 1, 2, 2] -applauded 1.5 0.5 [2, 2, 1, 2, 2, 2, 1, 1, 1, 1] -applauding 2.1 0.83066 [2, 2, 4, 1, 2, 2, 2, 1, 2, 3] -applauds 1.4 0.66332 [1, 1, 2, 1, 3, 1, 1, 1, 2, 1] -applause 1.8 0.6 [2, 1, 1, 2, 3, 2, 1, 2, 2, 2] -appreciate 1.7 0.78102 [2, 1, 2, 1, 1, 3, 1, 2, 3, 1] -appreciated 2.3 0.78102 [2, 1, 3, 2, 3, 4, 2, 2, 2, 2] -appreciates 2.3 0.9 [3, 1, 3, 1, 2, 4, 2, 3, 2, 2] -appreciating 1.9 0.7 [1, 1, 2, 2, 2, 2, 1, 3, 2, 3] -appreciation 2.3 0.9 [3, 3, 2, 1, 1, 3, 3, 1, 3, 3] -appreciations 1.7 0.78102 [3, 2, 1, 2, 2, 1, 3, 1, 1, 1] -appreciative 2.6 0.8 [3, 3, 3, 2, 1, 3, 4, 2, 2, 3] -appreciatively 1.8 0.6 [2, 2, 2, 2, 2, 1, 3, 2, 1, 1] -appreciativeness 1.6 0.8 [2, 1, 1, 2, 1, 1, 3, 3, 1, 1] -appreciator 2.6 0.8 [2, 3, 2, 3, 3, 2, 1, 3, 4, 3] -appreciators 1.5 0.80623 [1, 3, 1, 3, 1, 1, 2, 1, 1, 1] -appreciatory 1.7 0.78102 [1, 2, 1, 3, 1, 3, 2, 2, 1, 1] -apprehensible 1.1 1.04403 [2, 0, -1, 3, 1, 2, 1, 1, 1, 1] -apprehensibly -0.2 1.16619 [0, 0, -1, 2, -1, 2, -1, -1, -1, -1] -apprehension -2.1 0.83066 [-1, -2, -2, -1, -2, -3, -3, -3, -1, -3] -apprehensions -0.9 1.04403 [-1, -1, -1, -1, -2, -2, -1, -1, -1, 2] -apprehensively -0.3 1.18743 [-1, -1, -1, 0, 1, -2, -1, 1, -1, 2] -apprehensiveness -0.7 0.9 [-1, 1, -1, -1, 1, -1, -2, -1, -1, -1] -approval 2.1 0.53852 [2, 2, 2, 2, 2, 1, 3, 3, 2, 2] -approved 1.8 0.6 [1, 1, 1, 2, 3, 2, 2, 2, 2, 2] -approves 1.7 0.64031 [1, 1, 1, 2, 3, 2, 2, 2, 2, 1] -ardent 2.1 0.7 [3, 3, 2, 2, 3, 1, 2, 2, 1, 2] -arguable -1.0 0.63246 [-1, -1, -2, -1, -1, -2, 0, 0, -1, -1] -arguably -1.0 1.09545 [0, -2, 0, -2, 0, 1, -1, -2, -2, -2] -argue -1.4 0.66332 [-1, -2, -1, -3, -2, -1, -1, -1, -1, -1] -argued -1.5 0.5 [-2, -2, -1, -1, -1, -1, -2, -2, -2, -1] -arguer -1.6 0.4899 [-2, -2, -1, -2, -1, -1, -2, -2, -2, -1] -arguers -1.4 0.4899 [-2, -1, -1, -2, -1, -1, -2, -2, -1, -1] -argues -1.6 0.4899 [-2, -2, -1, -2, -1, -1, -2, -2, -2, -1] -arguing -2.0 0.63246 [-3, -3, -1, -1, -2, -2, -2, -2, -2, -2] -argument -1.5 0.80623 [-3, -1, -1, -1, -1, -2, 0, -2, -2, -2] -argumentative -1.5 0.67082 [-3, -2, -1, -1, -1, -1, -1, -2, -2, -1] -argumentatively -1.8 0.9798 [-4, -2, -1, -1, -3, -1, -2, -2, -1, -1] -argumentive -1.5 0.80623 [-3, -2, -2, -1, 0, -1, -1, -1, -2, -2] -arguments -1.7 0.64031 [-1, -1, -2, -2, -2, -3, -2, -1, -1, -2] -arrest -1.4 1.42829 [-1, 0, -1, 0, -2, -3, 0, -4, -3, 0] -arrested -2.1 1.04403 [-2, -2, -2, -1, -1, -4, -1, -4, -2, -2] -arrests -1.9 0.83066 [-4, -2, -1, -1, -1, -2, -2, -2, -2, -2] -arrogance -2.4 0.66332 [-3, -2, -2, -3, -1, -2, -3, -3, -2, -3] -arrogances -1.9 0.53852 [-1, -2, -3, -2, -2, -2, -2, -1, -2, -2] -arrogant -2.2 0.6 [-2, -2, -2, -3, -2, -3, -3, -2, -1, -2] -arrogantly -1.8 1.4 [-3, -2, 2, -3, -1, -3, -2, -2, -2, -2] -ashamed -2.1 1.3 [-3, -3, -3, -2, -2, 1, -2, -4, -1, -2] -ashamedly -1.7 0.64031 [-2, -2, -2, -1, -2, -3, -1, -2, -1, -1] -ass -2.5 1.43178 [-4, -1, -2, -1, -3, 0, -2, -4, -4, -4] -assassination -2.9 0.9434 [-2, -4, -4, -3, -3, -4, -2, -3, -3, -1] -assassinations -2.7 1.34536 [-4, -2, -3, -2, -3, -1, -4, -4, 0, -4] -assault -2.8 0.9798 [-3, -4, -2, -2, -4, -3, -1, -3, -2, -4] -assaulted -2.4 1.28062 [-3, -3, 1, -3, -3, -3, -1, -3, -3, -3] -assaulting -2.3 1.1 [-4, -3, -2, -1, -2, -1, -1, -4, -3, -2] -assaultive -2.8 0.87178 [-3, -4, -2, -4, -3, -2, -3, -1, -3, -3] -assaults -2.5 0.92195 [-1, -3, -3, -3, -4, -3, -1, -2, -2, -3] -asset 1.5 0.80623 [2, 1, 1, 3, 2, 0, 2, 2, 1, 1] -assets 0.7 1.00499 [0, 0, 1, 3, 0, 1, 0, 0, 2, 0] -assfucking -2.5 1.43178 [-3, -3, 0, -3, 0, -2, -4, -4, -4, -2] -assholes -2.8 0.74833 [-3, -3, -3, -3, -4, -3, -2, -3, -1, -3] -assurance 1.4 0.4899 [1, 1, 2, 2, 1, 1, 1, 2, 2, 1] -assurances 1.4 0.4899 [2, 2, 1, 1, 1, 2, 2, 1, 1, 1] -assure 1.4 0.4899 [1, 1, 1, 1, 2, 1, 1, 2, 2, 2] -assured 1.5 0.67082 [1, 1, 2, 1, 1, 3, 2, 1, 2, 1] -assuredly 1.6 0.66332 [1, 1, 1, 3, 2, 2, 2, 1, 2, 1] -assuredness 1.4 0.8 [2, 2, 2, 1, 1, 0, 2, 0, 2, 2] -assurer 0.9 1.13578 [2, 1, 0, 1, -2, 2, 2, 1, 1, 1] -assurers 1.1 0.9434 [2, 0, 0, 1, 3, 2, 0, 1, 1, 1] -assures 1.3 0.45826 [2, 1, 1, 1, 2, 1, 2, 1, 1, 1] -assurgent 1.3 0.9 [2, 1, 0, 0, 1, 2, 1, 2, 3, 1] -assuring 1.6 0.66332 [1, 2, 2, 3, 1, 1, 1, 1, 2, 2] -assuror 0.5 0.67082 [0, 1, 0, 1, 2, 0, 0, 1, 0, 0] -assurors 0.7 1.34536 [2, -1, 0, 2, 0, -2, 2, 1, 1, 2] -astonished 1.6 0.8 [3, 1, 0, 2, 2, 1, 2, 2, 1, 2] -astound 1.7 1.26886 [2, 2, 2, 2, 0, 3, 4, 0, 0, 2] -astounded 1.8 0.9798 [1, 3, 0, 1, 2, 2, 3, 2, 1, 3] -astounding 1.8 1.4 [3, 4, 2, 0, 1, 2, -1, 3, 2, 2] -astoundingly 2.1 1.44568 [3, 0, 4, 1, 4, 3, 1, 3, 0, 2] -astounds 2.1 1.22066 [3, 3, 1, 0, 3, 2, 3, 3, 0, 3] -attachment 1.2 0.9798 [2, 0, 1, 2, 3, 1, 1, 2, 0, 0] -attachments 1.1 0.7 [1, 1, 2, 0, 2, 1, 2, 0, 1, 1] -attack -2.1 0.83066 [-1, -3, -2, -3, -3, -1, -2, -1, -2, -3] -attacked -2.0 1.78885 [-2, 3, -2, -2, -3, -3, -3, -4, -2, -2] -attacker -2.7 0.9 [-2, -3, -2, -1, -3, -3, -4, -4, -2, -3] -attackers -2.7 0.64031 [-3, -3, -3, -2, -3, -3, -4, -2, -2, -2] -attacking -2.0 0.89443 [-3, -1, -1, -3, -3, -1, -3, -1, -2, -2] -attacks -1.9 0.9434 [-2, -2, 0, -2, -2, -2, -1, -4, -2, -2] -attract 1.5 0.92195 [1, 3, 1, 1, 3, 1, 1, 2, 0, 2] -attractancy 0.9 0.7 [1, 0, 2, 1, 0, 2, 1, 1, 0, 1] -attractant 1.3 0.9 [0, 1, 0, 1, 1, 2, 3, 2, 1, 2] -attractants 1.4 0.8 [1, 1, 0, 2, 2, 2, 3, 1, 1, 1] -attracted 1.8 0.6 [1, 3, 1, 2, 2, 2, 2, 2, 2, 1] -attracting 2.1 0.83066 [3, 1, 2, 2, 3, 1, 1, 3, 2, 3] -attraction 2.0 0.7746 [2, 2, 1, 1, 2, 3, 3, 2, 3, 1] -attractions 1.8 0.87178 [1, 3, 0, 2, 2, 2, 2, 3, 1, 2] -attractive 1.9 0.53852 [2, 2, 2, 1, 3, 2, 1, 2, 2, 2] -attractively 2.2 0.6 [3, 2, 2, 3, 2, 2, 2, 3, 1, 2] -attractiveness 1.8 1.16619 [3, 2, 2, 1, 4, 2, 0, 0, 2, 2] -attractivenesses 2.1 0.7 [2, 1, 2, 3, 2, 3, 3, 1, 2, 2] -attractor 1.2 1.16619 [1, 1, 2, 2, 2, -2, 2, 1, 2, 1] -attractors 1.2 0.87178 [1, 1, 2, 2, 0, 1, 3, 1, 0, 1] -attracts 1.7 1.00499 [2, 1, 2, 0, 2, 4, 2, 1, 1, 2] -audacious 0.9 2.02237 [3, -1, -2, 2, 1, 2, -3, 2, 2, 3] -authority 0.3 0.64031 [0, 0, 0, 1, 0, 0, 2, 0, 0, 0] -aversion -1.9 1.04403 [-3, -3, -1, -2, 0, -3, -1, -2, -1, -3] -aversions -1.1 1.13578 [-2, -1, -2, -2, -2, 1, -1, -2, 1, -1] -aversive -1.6 0.66332 [-2, -1, -1, -1, -2, -2, -1, -2, -3, -1] -aversively -0.8 1.53623 [-3, -1, -2, -1, 1, -2, 2, -2, 1, -1] -avert -0.7 0.78102 [-1, 0, -2, -1, -1, 1, -1, 0, -1, -1] -averted -0.3 1.00499 [-1, 1, 0, 0, 1, 0, -2, 0, 0, -2] -averts -0.4 1.0198 [-2, -2, -1, -1, 0, 0, 1, 0, 1, 0] -avid 1.2 0.87178 [-1, 2, 2, 1, 1, 1, 2, 2, 1, 1] -avoid -1.2 0.6 [-1, -1, -1, -1, -2, -2, -1, -2, 0, -1] -avoidance -1.7 0.45826 [-2, -2, -1, -1, -1, -2, -2, -2, -2, -2] -avoidances -1.1 0.53852 [-1, -1, -1, -1, -2, 0, -1, -2, -1, -1] -avoided -1.4 0.4899 [-2, -1, -2, -1, -1, -1, -2, -1, -2, -1] -avoider -1.8 0.6 [-2, -1, -3, -1, -2, -2, -2, -1, -2, -2] -avoiders -1.4 0.66332 [-2, -2, -1, -2, -1, -1, 0, -1, -2, -2] -avoiding -1.4 0.91652 [-2, 1, -2, -2, -1, -2, -1, -1, -2, -2] -avoids -0.7 0.45826 [-1, -1, -1, -1, -1, -1, 0, 0, 0, -1] -await 0.4 0.4899 [0, 0, 0, 1, 0, 1, 0, 1, 1, 0] -awaited -0.1 0.83066 [1, 0, 0, 0, 1, -1, 0, 0, -2, 0] -awaits 0.3 0.78102 [0, 0, 0, 1, 2, 1, 0, 0, -1, 0] -award 2.5 0.92195 [2, 1, 1, 3, 3, 2, 4, 3, 3, 3] -awardable 2.4 0.8 [3, 3, 3, 1, 3, 1, 2, 3, 2, 3] -awarded 1.7 0.78102 [2, 0, 1, 3, 2, 2, 2, 1, 2, 2] -awardee 1.8 0.6 [2, 2, 1, 3, 2, 2, 1, 1, 2, 2] -awardees 1.2 0.74833 [1, 1, 1, 1, 0, 1, 1, 1, 3, 2] -awarder 0.9 1.04403 [2, 0, 1, 3, 0, 2, 1, 0, 0, 0] -awarders 1.3 1.18743 [2, 1, 0, 2, 2, 0, 0, 4, 1, 1] -awarding 1.9 0.7 [3, 2, 1, 2, 1, 2, 3, 1, 2, 2] -awards 2.0 0.44721 [2, 2, 2, 2, 1, 2, 2, 3, 2, 2] -awesome 3.1 0.83066 [3, 4, 2, 3, 2, 2, 4, 4, 4, 3] -awful -2.0 2.04939 [-2, -2, -3, -3, -2, -3, 4, -3, -3, -3] -awkward -0.6 1.56205 [-2, -1, -1, -1, -1, -1, -1, -1, 4, -1] -awkwardly -1.3 0.45826 [-1, -1, -2, -1, -1, -1, -1, -2, -2, -1] -awkwardness -0.7 1.41774 [-1, -2, -2, -1, -2, 2, -1, -1, 2, -1] -axe -0.4 0.8 [-2, 0, 0, 0, 0, 0, -1, -1, -1, 1] -axed -1.3 0.78102 [-1, -2, 0, -3, -1, -2, -1, -1, -1, -1] -backed 0.1 0.3 [0, 0, 1, 0, 0, 0, 0, 0, 0, 0] -backing 0.1 0.83066 [1, 1, -1, 0, 0, 0, -1, 1, -1, 1] -backs -0.2 0.4 [0, 0, -1, 0, 0, 0, 0, -1, 0, 0] -bad -2.5 0.67082 [-3, -2, -4, -3, -2, -2, -3, -2, -2, -2] -badass 1.4 1.26491 [1, 3, 2, 0, -1, 1, 3, 2, 1, 2] -badly -2.1 0.7 [-2, -3, -2, -1, -3, -2, -3, -2, -1, -2] -bailout -0.4 1.35647 [-1, 0, 0, 2, -2, -1, -2, 2, -1, -1] -bamboozle -1.5 1.0247 [-3, -2, -2, -1, -2, -2, 1, -1, -1, -2] -bamboozled -1.5 1.11803 [-1, 0, -2, -4, -2, -1, -2, -1, 0, -2] -bamboozles -1.5 1.0247 [-1, 0, -2, -4, -2, -1, -2, -1, -1, -1] -ban -2.6 1.0198 [-4, -3, -4, -3, -2, -1, -3, -2, -1, -3] -banish -1.9 0.9434 [-2, -2, -2, -2, -1, -3, -1, -1, -1, -4] -bankrupt -2.6 1.0198 [-4, -4, -2, -2, -4, -3, -2, -2, -1, -2] -bankster -2.1 0.53852 [-3, -1, -2, -2, -2, -2, -2, -3, -2, -2] -banned -2.0 1.0 [-2, -1, -1, -1, -2, -2, -4, -3, -3, -1] -bargain 0.8 1.16619 [1, 1, 1, 1, 0, 1, 2, 3, -1, -1] -barrier -0.5 0.92195 [-2, 0, 0, -2, -1, -1, 1, 0, 0, 0] -bashful -0.1 1.13578 [-1, 2, -1, 0, -1, 2, 0, 0, -1, -1] -bashfully 0.2 0.9798 [0, 0, 0, -1, 1, 1, 1, 1, -2, 1] -bashfulness -0.8 0.9798 [-2, -1, 1, 1, -1, -2, -1, -1, -1, -1] -bastard -2.5 0.67082 [-2, -4, -2, -3, -2, -2, -3, -3, -2, -2] -bastardies -1.8 0.87178 [-2, -1, -3, -2, -2, -2, -1, 0, -2, -3] -bastardise -2.1 0.83066 [-2, -1, -4, -2, -2, -3, -2, -2, -2, -1] -bastardised -2.3 0.9 [-3, -2, -3, -1, -2, -3, -4, -1, -2, -2] -bastardises -2.3 1.18743 [-1, -4, -2, -3, -3, 0, -2, -4, -2, -2] -bastardising -2.6 0.8 [-3, -2, -3, -2, -2, -1, -3, -4, -3, -3] -bastardization -2.4 1.28062 [-1, -3, -4, -4, -2, -2, -2, 0, -2, -4] -bastardizations -2.1 0.7 [-2, -1, -3, -3, -2, -2, -3, -1, -2, -2] -bastardize -2.4 0.66332 [-2, -2, -3, -2, -2, -3, -4, -2, -2, -2] -bastardized -2.0 0.7746 [-2, -1, -1, -2, -3, -2, -3, -2, -1, -3] -bastardizes -1.8 0.87178 [-2, -1, -1, -2, -2, -2, -3, -3, 0, -2] -bastardizing -2.3 0.9 [-2, -2, -1, -4, -3, -2, -1, -2, -3, -3] -bastardly -2.7 0.64031 [-3, -3, -2, -2, -3, -2, -2, -4, -3, -3] -bastards -3.0 0.63246 [-4, -2, -3, -3, -4, -3, -3, -3, -3, -2] -bastardy -2.7 1.1 [-4, -3, -2, -2, -4, -3, -3, -3, -3, 0] -battle -1.6 1.28062 [-1, -3, 0, -3, -2, -3, -2, -2, 1, -1] -battled -1.2 0.87178 [0, 0, -2, 0, -2, -1, -2, -1, -2, -2] -battlefield -1.6 0.8 [-2, -2, 0, -1, -2, -1, -3, -2, -1, -2] -battlefields -0.9 1.22066 [-1, -1, 0, 0, -4, -1, 0, 0, 0, -2] -battlefront -1.2 0.87178 [-1, 0, -2, -1, 0, -3, -1, -2, -1, -1] -battlefronts -0.8 1.16619 [0, 0, -2, -1, 0, -3, -1, 1, -2, 0] -battleground -1.7 0.78102 [-2, 0, -2, -2, -1, -2, -2, -3, -1, -2] -battlegrounds -0.6 1.35647 [2, -2, 0, -1, 0, -2, -2, -2, 0, 1] -battlement -0.4 0.8 [0, -1, 0, -1, 0, -2, 0, 1, 0, -1] -battlements -0.4 0.66332 [0, 0, 0, 0, 0, -1, -2, 0, -1, 0] -battler -0.8 1.4 [2, 0, -2, 0, -2, 1, -2, -1, -2, -2] -battlers -0.2 0.9798 [-1, 0, 2, -2, 0, 0, 0, -1, 0, 0] -battles -1.6 0.4899 [-1, -1, -2, -1, -2, -2, -2, -1, -2, -2] -battleship -0.1 1.3 [2, -3, -1, -1, 0, 0, 1, 1, 0, 0] -battleships -0.5 0.80623 [-2, 0, 0, 0, 0, -1, -2, 0, 0, 0] -battlewagon -0.3 0.64031 [0, 0, -1, -2, 0, 0, 0, 0, 0, 0] -battlewagons -0.5 0.67082 [0, 0, 0, -1, -2, -1, 0, -1, 0, 0] -battling -1.1 1.04403 [0, -1, -2, -2, -1, 1, -2, 0, -2, -2] -beaten -1.8 0.6 [-1, -2, -2, -2, -3, -2, -2, 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0.64031 [3, 3, 2, 2, 3, 3, 2, 2, 4, 3] -beautifulness 2.6 0.8 [3, 3, 3, 2, 3, 4, 3, 2, 2, 1] -beautify 2.3 0.45826 [2, 3, 3, 2, 2, 3, 2, 2, 2, 2] -beautifying 2.3 0.78102 [1, 2, 1, 3, 2, 2, 3, 3, 3, 3] -beauts 1.7 0.78102 [1, 2, 0, 3, 1, 2, 2, 2, 2, 2] -beauty 2.8 0.74833 [3, 3, 2, 3, 4, 4, 2, 2, 3, 2] -belittle -1.9 0.53852 [-2, -2, -2, -1, -2, -2, -1, -2, -3, -2] -belittled -2.0 1.0 [-3, -2, -3, -3, -2, -3, -1, -1, -2, 0] -beloved 2.3 0.45826 [2, 2, 3, 2, 2, 2, 2, 3, 3, 2] -benefic 1.4 0.4899 [2, 2, 1, 1, 1, 2, 2, 1, 1, 1] -benefice 0.4 0.66332 [0, 2, 0, 1, 0, 0, 1, 0, 0, 0] -beneficed 1.1 0.7 [1, 1, 1, 0, 2, 0, 1, 1, 2, 2] -beneficence 2.8 0.87178 [1, 4, 3, 4, 2, 2, 3, 3, 3, 3] -beneficences 1.5 0.67082 [1, 1, 2, 2, 1, 1, 1, 3, 2, 1] -beneficent 2.3 0.45826 [3, 2, 3, 2, 2, 2, 2, 3, 2, 2] -beneficently 2.2 0.6 [3, 2, 3, 3, 2, 2, 1, 2, 2, 2] -benefices 1.1 0.83066 [1, 1, 1, 0, 1, 0, 1, 1, 2, 3] -beneficial 1.9 0.53852 [2, 2, 1, 2, 2, 1, 3, 2, 2, 2] -beneficially 2.4 0.8 [3, 3, 2, 2, 2, 1, 3, 4, 2, 2] -beneficialness 1.7 0.64031 [2, 1, 2, 2, 1, 1, 2, 2, 1, 3] -beneficiaries 1.8 1.16619 [0, 1, 2, 1, 3, 4, 3, 1, 2, 1] -beneficiary 2.1 0.83066 [1, 3, 2, 2, 2, 1, 3, 3, 1, 3] -beneficiate 1.0 1.18322 [0, 0, 1, 3, 1, 0, 2, 0, 3, 0] -beneficiation 0.4 1.0198 [2, 2, 0, -1, 1, 0, -1, 0, 0, 1] -benefit 2.0 0.63246 [2, 3, 1, 2, 2, 3, 2, 1, 2, 2] -benefits 1.6 0.4899 [2, 2, 2, 1, 2, 1, 2, 2, 1, 1] -benefitted 1.7 0.64031 [2, 2, 1, 2, 2, 2, 2, 2, 0, 2] -benefitting 1.9 0.7 [1, 2, 2, 3, 1, 1, 2, 3, 2, 2] -benevolence 1.7 1.1 [2, 1, 3, 2, 2, 1, 2, 2, -1, 3] -benevolences 1.9 1.64012 [3, 2, -1, -1, 3, 1, 3, 4, 2, 3] -benevolent 2.7 0.78102 [2, 2, 3, 2, 4, 2, 3, 2, 4, 3] -benevolently 1.4 1.11355 [2, 1, 2, 2, 1, -1, 2, 3, 0, 2] -benevolentness 1.2 1.249 [2, 2, 1, -1, 2, 2, 3, -1, 1, 1] -benign 1.3 0.9 [1, 3, 2, 2, 1, 1, 2, 0, 0, 1] -benignancy 0.6 1.2 [2, -1, -2, 1, 0, 1, 1, 2, 1, 1] -benignant 2.2 0.9798 [2, 2, 2, 2, 2, 2, 4, 0, 3, 3] -benignantly 1.1 1.3 [3, 2, 3, 0, 1, 1, -1, 2, 0, 0] -benignities 0.9 0.9434 [-1, 2, 1, 0, 1, 1, 2, 2, 1, 0] -benignity 1.3 1.18743 [2, -2, 2, 2, 2, 1, 2, 1, 1, 2] -benignly 0.2 1.07703 [0, -1, 1, 1, 1, 0, 2, 0, -2, 0] -bereave -2.1 1.13578 [0, -2, -2, -3, -3, -4, -3, -2, -1, -1] -bereaved -2.1 0.9434 [-2, -2, -2, -1, -2, -1, -4, -1, -3, -3] -bereaves -1.9 1.22066 [0, -3, 0, -1, -3, -2, -3, -1, -3, -3] -bereaving -1.3 1.84662 [-3, -4, -3, 1, -2, 0, -3, -1, 1, 1] -best 3.2 0.6 [2, 4, 4, 3, 4, 3, 3, 3, 3, 3] -betray -3.2 0.6 [-3, -4, -4, -3, -2, -3, -4, -3, -3, -3] -betrayal -2.8 0.74833 [-3, -4, -4, -2, -3, -2, -3, -3, -2, -2] -betrayed -3.0 0.63246 [-2, -3, -3, -3, -4, -4, -3, -3, -2, -3] -betraying -2.5 0.67082 [-2, -2, -3, -2, -3, -2, -4, -2, -2, -3] -betrays -2.5 0.67082 [-2, -3, -3, -2, -2, -2, -4, -2, -3, -2] -better 1.9 0.7 [2, 1, 2, 1, 1, 3, 2, 2, 3, 2] -bias -0.4 1.11355 [-1, -2, 0, -2, -1, 1, -1, 1, 0, 1] -biased -1.1 0.83066 [-2, -2, -1, -1, -1, -1, -1, 1, -2, -1] -bitch -2.8 0.87178 [-1, -4, -2, -4, -3, -2, -3, -3, -3, -3] -bitched -2.6 1.0198 [-1, -3, -2, -3, -2, -1, -4, -3, -3, -4] -bitcheries -2.3 0.78102 [-2, -2, -2, -4, -2, -2, -3, -1, -3, -2] -bitchery -2.7 1.18743 [-2, -2, -4, -2, -4, -4, -1, -1, -3, -4] -bitches -2.9 0.9434 [-2, -1, -3, -3, -2, -4, -4, -3, -3, -4] -bitchier -2.0 0.63246 [-2, -3, -1, -2, -3, -1, -2, -2, -2, -2] -bitchiest -3.0 0.7746 [-2, -4, -2, -3, -4, -3, -3, -4, -2, -3] -bitchily -2.6 1.11355 [-4, -4, -2, -2, -1, -4, -1, -2, -3, -3] -bitchiness -2.6 0.66332 [-3, -3, -2, -2, -3, -3, -1, -3, -3, -3] -bitching -1.1 1.64012 [-2, 2, -2, -1, 2, -1, -2, -2, -3, -2] -bitchy -2.3 1.00499 [-4, -1, -2, -3, -3, -2, -1, -1, -3, -3] -bitter -1.8 0.4 [-2, -2, -2, -1, -2, -2, -1, -2, -2, -2] -bitterbrush -0.2 0.74833 [0, 0, 0, 0, -2, 1, 0, 0, -1, 0] -bitterbrushes -0.6 0.8 [-1, 0, -2, -1, -2, 0, 0, 0, 0, 0] -bittered -1.8 1.07703 [-1, -1, -3, -1, -2, -4, -2, 0, -2, -2] -bitterer -1.9 1.04403 [-1, -2, -3, -1, -1, -4, -3, -1, -2, -1] -bitterest -2.3 1.41774 [-4, -4, -2, -1, 1, -2, -3, -3, -2, -3] -bittering -1.2 0.87178 [0, 0, -1, -2, 0, -2, -1, -2, -2, -2] -bitterish -1.6 0.8 [0, -2, -1, -1, -2, -2, -2, -1, -3, -2] -bitterly -2.0 0.63246 [-2, -2, -1, -1, -2, -2, -3, -2, -2, -3] -bittern -0.2 0.6 [0, 0, -2, 0, 0, 0, 0, 0, 0, 0] -bitterness -1.7 0.45826 [-2, -2, -1, -2, -1, -2, -1, -2, -2, -2] -bitterns -0.4 1.11355 [0, 0, 0, -3, 0, 0, 0, 1, 0, -2] -bitterroots -0.2 0.4 [0, 0, 0, -1, -1, 0, 0, 0, 0, 0] -bitters -0.4 0.4899 [-1, -1, -1, 0, 0, 0, 0, -1, 0, 0] -bittersweet -0.3 0.64031 [0, -1, 0, 0, 0, 0, 0, 0, -2, 0] -bittersweetness -0.6 0.91652 [0, 0, 0, -2, 0, -2, 0, 0, -2, 0] -bittersweets -0.2 0.9798 [-2, 1, 0, 0, 0, -2, 0, 0, 0, 1] -bitterweeds -0.5 0.67082 [0, -2, 0, -1, -1, 0, 0, -1, 0, 0] -bizarre -1.3 1.00499 [-2, 0, 0, -2, 0, -1, -3, -2, -1, -2] -blah -0.4 1.49666 [-2, -1, -1, -1, -1, -1, -1, 3, 2, -1] -blam -0.2 1.16619 [-1, 0, 0, -1, -1, -2, -1, 1, 2, 1] -blamable -1.8 0.4 [-2, -2, -2, -2, -1, -1, -2, -2, -2, -2] -blamably -1.8 0.4 [-2, -2, -2, -2, -1, -1, -2, -2, -2, -2] -blame -1.4 1.42829 [-4, -2, -2, -1, -1, -1, -2, 2, -2, -1] -blamed -2.1 0.53852 [-2, -2, -2, -2, -3, -2, -2, -2, -3, -1] -blameful -1.7 0.45826 [-2, -2, -2, -2, -2, -2, -1, -1, -2, -1] -blamefully -1.6 0.66332 [-1, -2, -1, -1, -2, -1, -1, -2, -2, -3] -blameless 0.7 1.73494 [3, 1, 2, 3, -2, 1, -1, 1, 1, -2] -blamelessly 0.9 1.37477 [2, 0, 2, 0, 1, -1, 1, 4, 0, 0] -blamelessness 0.6 1.35647 [0, 2, 1, 2, 1, 0, 1, -3, 1, 1] -blamer -2.1 0.83066 [-2, -2, -1, -2, -3, -3, -3, -1, -1, -3] -blamers -2.0 0.63246 [-3, -2, -2, -3, -1, -2, -2, -1, -2, -2] -blames -1.7 0.45826 [-2, -2, -1, -2, -2, -2, -2, -1, -1, -2] -blameworthiness -1.6 0.66332 [-2, -2, -1, -2, -2, -1, -3, -1, -1, -1] -blameworthy -2.3 0.78102 [-3, -3, -2, -2, -2, -1, -1, -3, -3, -3] -blaming -2.2 0.6 [-2, -3, -1, -3, -2, -2, -3, -2, -2, -2] -bless 1.8 0.6 [3, 2, 2, 1, 2, 2, 1, 2, 2, 1] -blessed 2.9 0.3 [2, 3, 3, 3, 3, 3, 3, 3, 3, 3] -blesseder 2.0 0.63246 [3, 3, 2, 2, 1, 1, 2, 2, 2, 2] -blessedest 2.8 0.87178 [2, 4, 1, 4, 3, 3, 2, 3, 3, 3] -blessedly 1.7 1.1 [2, 2, 1, -1, 3, 2, 3, 1, 2, 2] -blessedness 1.6 1.35647 [2, 2, 2, 2, 2, 3, 3, -1, -1, 2] -blesser 2.6 0.66332 [1, 3, 2, 3, 3, 3, 2, 3, 3, 3] -blessers 1.9 0.7 [2, 2, 1, 2, 2, 2, 3, 1, 3, 1] -blesses 2.6 0.66332 [1, 3, 3, 3, 3, 3, 2, 3, 2, 3] -blessing 2.2 1.07703 [3, 1, 0, 3, 1, 3, 2, 3, 3, 3] -blessings 2.5 0.92195 [3, 3, 3, 2, 1, 3, 2, 3, 4, 1] -blind -1.7 1.00499 [-4, -1, -1, -2, -1, -1, -3, -2, -1, -1] -bliss 2.7 0.78102 [3, 3, 3, 2, 1, 2, 4, 3, 3, 3] -blissful 2.9 0.83066 [4, 4, 2, 3, 3, 3, 1, 3, 3, 3] -blithe 1.2 1.16619 [2, 2, -1, 1, 1, 2, 2, 2, -1, 2] -block -1.9 1.13578 [-3, -2, -1, -2, 0, 0, -3, -2, -3, -3] -blockbuster 2.9 0.9434 [3, 4, 3, 2, 3, 4, 3, 2, 1, 4] -blocked -1.1 1.13578 [-1, 0, 0, -1, -2, -1, -1, -4, -1, 0] -blocking -1.6 0.91652 [-1, -1, -1, -1, -2, -2, -4, -1, -2, -1] -blocks -0.9 1.13578 [-1, 0, -1, -2, -2, -2, -1, -1, 2, -1] -bloody -1.9 0.7 [-2, -2, -2, 0, -2, -2, -3, -2, -2, -2] -blurry -0.4 1.28062 [-1, -1, -1, -1, 2, -2, -1, 2, 0, -1] -bold 1.6 0.66332 [2, 2, 2, 2, 1, 2, 0, 2, 1, 2] -bolder 1.2 0.6 [2, 1, 1, 1, 1, 2, 1, 2, 0, 1] -boldest 1.6 1.11355 [1, 3, 2, 3, 0, 0, 2, 3, 1, 1] -boldface 0.3 0.64031 [1, 0, 0, 0, 0, 0, 0, 2, 0, 0] -boldfaced -0.1 1.22066 [0, 0, 0, 2, -1, -2, 2, -1, -1, 0] -boldfaces 0.1 1.3 [0, 0, 0, 2, -2, -2, 2, 1, 0, 0] -boldfacing 0.1 0.7 [0, 0, -1, 2, 0, 0, 0, 0, 0, 0] -boldly 1.5 1.62788 [3, -2, -1, 1, 2, 3, 2, 3, 2, 2] -boldness 1.5 1.0247 [0, 1, 3, 1, 2, 0, 3, 1, 2, 2] -boldnesses 0.9 0.83066 [0, 0, 1, 0, 2, 1, 1, 2, 0, 2] -bolds 1.3 0.78102 [2, 2, 1, 1, 0, 2, 0, 2, 1, 2] -bomb -2.2 0.87178 [-2, -2, -1, -3, -4, -3, -2, -1, -2, -2] -bonus 2.5 0.67082 [2, 2, 2, 3, 4, 3, 2, 2, 3, 2] -bonuses 2.6 0.91652 [2, 2, 3, 4, 3, 4, 3, 1, 2, 2] -boost 1.7 0.64031 [1, 1, 2, 2, 2, 3, 1, 1, 2, 2] -boosted 1.5 1.5 [-1, 1, 0, 2, 1, 2, 3, 3, 4, 0] -boosting 1.4 0.91652 [1, 1, 3, 0, 2, 2, 0, 2, 1, 2] -boosts 1.3 0.9 [1, 1, 1, 1, 3, 0, 1, 1, 3, 1] -bore -1.0 0.44721 [-1, -2, 0, -1, -1, -1, -1, -1, -1, -1] -boreal -0.3 0.9 [0, 0, 0, 0, 1, -2, 0, 0, -2, 0] -borecole -0.2 0.74833 [1, 0, 0, 0, -1, -2, 0, 0, 0, 0] -borecoles -0.3 0.45826 [-1, 0, 0, 0, 0, 0, -1, 0, -1, 0] -bored -1.1 0.9434 [-2, -1, -2, -1, 0, 0, -3, 0, -1, -1] -boredom -1.3 0.45826 [-1, -1, -1, -1, -2, -1, -1, -2, -2, -1] -boredoms -1.1 0.83066 [-1, -1, -1, -2, 1, -1, -2, -1, -1, -2] -boreen 0.1 0.3 [0, 0, 0, 0, 0, 1, 0, 0, 0, 0] -boreens 0.2 0.6 [0, 0, 0, 2, 0, 0, 0, 0, 0, 0] -boreholes -0.2 0.74833 [0, 0, 0, 0, 0, 1, -1, 0, -2, 0] -borer -0.4 0.4899 [0, -1, 0, 0, -1, -1, 0, 0, 0, -1] -borers -1.2 0.9798 [-1, 0, -2, -1, -1, -3, -2, 0, -2, 0] -bores -1.3 0.78102 [-2, -1, -2, -1, -1, -1, -3, 0, -1, -1] -borescopes -0.1 0.83066 [-1, 0, -1, 2, 0, 0, 0, 0, -1, 0] -boresome -1.3 0.45826 [-2, -1, -1, -1, -1, -1, -2, -1, -2, -1] -boring -1.3 0.45826 [-1, -1, -1, -1, -1, -2, -1, -1, -2, -2] -bother -1.4 0.91652 [-1, -1, -1, -2, -3, -3, -1, -1, -1, 0] -botheration -1.7 0.64031 [-1, -1, -1, -2, -2, -1, -2, -2, -2, -3] -botherations -1.3 0.64031 [-2, -2, -2, -1, -2, 0, -1, -1, -1, -1] -bothered -1.3 0.45826 [-1, -1, -2, -1, -2, -1, -1, -1, -1, -2] -bothering -1.6 0.4899 [-2, -1, -2, -2, -1, -1, -1, -2, -2, -2] -bothers -0.8 0.9798 [-1, -2, -1, -1, 2, -1, -1, -1, -1, -1] -bothersome -1.3 0.45826 [-2, -1, -1, -1, -1, -1, -2, -2, -1, -1] -boycott -1.3 0.45826 [-2, -1, -1, -1, -1, -2, -1, -1, -2, -1] -boycotted -1.7 0.64031 [-1, -2, -2, -3, -1, -1, -2, -2, -2, -1] -boycotting -1.7 0.64031 [-2, -2, -2, 0, -2, -1, -2, -2, -2, -2] -boycotts -1.4 0.91652 [-2, -2, -2, -2, -1, -2, -1, 1, -1, -2] -brainwashing -1.5 1.28452 [-2, -2, -2, -3, -1, -2, 2, -1, -2, -2] -brave 2.4 0.8 [2, 3, 4, 3, 1, 3, 2, 2, 2, 2] -braved 1.9 0.83066 [3, 1, 3, 1, 1, 2, 3, 2, 2, 1] -bravely 2.3 0.78102 [1, 3, 2, 2, 2, 4, 2, 2, 2, 3] -braver 2.4 0.8 [3, 2, 2, 1, 4, 2, 3, 3, 2, 2] -braveries 2.0 1.0 [2, 4, 2, 3, 1, 1, 2, 3, 1, 1] -bravery 2.2 0.74833 [1, 2, 2, 2, 3, 2, 3, 3, 1, 3] -braves 1.9 0.83066 [3, 1, 3, 1, 2, 2, 3, 2, 1, 1] -bravest 2.3 0.64031 [1, 3, 3, 2, 3, 2, 3, 2, 2, 2] -breathtaking 2.0 1.26491 [3, 1, 3, 2, -1, 1, 2, 3, 3, 3] -bribe -0.8 1.98997 [-3, 0, -1, -2, -1, -2, -4, 1, 3, 1] -bright 1.9 0.7 [2, 2, 1, 2, 1, 2, 1, 3, 3, 2] -brighten 1.9 0.7 [2, 1, 1, 2, 3, 2, 1, 2, 2, 3] -brightened 2.1 0.83066 [2, 3, 1, 1, 2, 2, 3, 1, 3, 3] -brightener 1.0 1.18322 [0, 0, 0, 1, 0, 1, 2, 0, 3, 3] -brighteners 1.0 0.89443 [0, 1, 0, 1, 1, 3, 0, 1, 2, 1] -brightening 2.5 0.92195 [2, 3, 2, 1, 2, 3, 4, 4, 2, 2] -brightens 1.5 0.5 [2, 1, 1, 2, 2, 1, 2, 2, 1, 1] -brighter 1.6 0.66332 [1, 1, 1, 2, 2, 2, 1, 2, 1, 3] -brightest 3.0 0.63246 [3, 3, 2, 3, 4, 3, 2, 3, 4, 3] -brightly 1.5 0.67082 [2, 3, 1, 2, 1, 1, 2, 1, 1, 1] -brightness 1.6 0.91652 [2, 2, 1, 1, 1, 3, 3, 0, 2, 1] -brightnesses 1.4 0.91652 [2, 3, 1, 2, 1, 1, 0, 0, 2, 2] -brights 0.4 0.66332 [0, 0, 2, 0, 0, 1, 0, 0, 1, 0] -brightwork 1.1 0.83066 [1, 0, 1, 2, 1, 0, 3, 1, 1, 1] -brilliance 2.9 0.83066 [4, 3, 2, 4, 4, 3, 2, 3, 2, 2] -brilliances 2.9 0.83066 [3, 4, 3, 4, 4, 2, 3, 2, 2, 2] -brilliancies 2.3 1.18743 [1, 4, 1, 3, 3, 2, 1, 3, 4, 1] -brilliancy 2.6 1.0198 [4, 3, 2, 4, 2, 3, 1, 3, 1, 3] -brilliant 2.8 0.6 [2, 3, 3, 2, 3, 3, 4, 2, 3, 3] -brilliantine 0.8 1.16619 [-1, 3, 1, 0, 1, 0, 2, 0, 2, 0] -brilliantines 2.0 1.34164 [0, 1, 4, 2, 3, 1, 3, 0, 3, 3] -brilliantly 3.0 0.44721 [3, 2, 3, 3, 3, 3, 3, 3, 4, 3] -brilliants 1.9 0.83066 [3, 1, 2, 1, 2, 1, 3, 2, 1, 3] -brisk 0.6 0.8 [0, 0, 0, 0, 1, 1, 0, 2, 0, 2] -broke -1.8 0.4 [-2, -2, -2, -2, -1, -2, -2, -1, -2, -2] -broken -2.1 0.53852 [-2, -2, -2, -2, -3, -2, -1, -3, -2, -2] -brooding 0.1 1.3 [3, 0, -1, -1, -1, 1, 1, -1, 1, -1] -brutal -3.1 0.7 [-3, -3, -4, -2, -3, -4, -3, -4, -3, -2] -brutalise -2.7 1.1 [-4, -3, -3, -4, -3, -2, -2, -3, 0, -3] -brutalised -2.9 0.83066 [-3, -3, -2, -3, -3, -4, -4, -1, -3, -3] -brutalises -3.2 0.4 [-3, -3, -3, -3, -3, -4, -4, -3, -3, -3] -brutalising -2.8 0.74833 [-3, -3, -4, -3, -2, -3, -3, -3, -1, -3] -brutalities -2.6 1.0198 [-4, -2, -2, -4, -2, -4, -2, -3, -1, -2] -brutality -3.0 0.63246 [-2, -3, -4, -2, -3, -3, -3, -4, -3, -3] -brutalization -2.1 2.16564 [-3, -2, -4, -2, -4, -4, 2, -3, 2, -3] -brutalizations -2.3 0.64031 [-2, -2, -3, -2, -1, -3, -3, -2, -2, -3] -brutalize -2.9 0.7 [-3, -4, -3, -3, -2, -2, -3, -4, -2, -3] -brutalized -2.4 0.4899 [-3, -2, -2, -3, -2, -2, -3, -3, -2, -2] -brutalizes -3.2 0.6 [-4, -4, -3, -2, -3, -4, -3, -3, -3, -3] -brutalizing -3.4 0.66332 [-4, -3, -4, -3, -4, -4, -3, -4, -2, -3] -brutally -3.0 0.44721 [-3, -3, -3, -3, -3, -3, -3, -2, -3, -4] -bullied -3.1 0.9434 [-4, -4, -4, -2, -2, -4, -4, -3, -2, -2] -bullshit -2.8 0.6 [-3, -3, -3, -3, -3, -4, -2, -3, -2, -2] -bully -2.2 1.6 [-2, -3, -3, -4, -2, -1, 2, -3, -3, -3] -bullying -2.9 0.7 [-3, -2, -3, -2, -4, -2, -3, -3, -4, -3] -bummer -1.6 0.8 [-3, -1, -1, -1, -3, -1, -1, -2, -2, -1] -buoyant 0.9 0.83066 [0, 1, 1, 2, 1, 0, 0, 2, 0, 2] -burden -1.9 0.53852 [-2, -2, -1, -2, -3, -2, -1, -2, -2, -2] -burdened -1.7 0.45826 [-2, -2, -2, -2, -1, -2, -1, -2, -2, -1] -burdener -1.3 0.45826 [-1, -1, -2, -1, -1, -1, -2, -1, -2, -1] -burdeners -1.7 1.00499 [-2, -2, -2, -1, -3, -2, 0, 0, -2, -3] -burdening -1.4 0.66332 [-2, -1, -2, -2, -1, -1, -1, 0, -2, -2] -burdens -1.5 0.5 [-2, -2, -1, -1, -2, -1, -1, -1, -2, -2] -burdensome -1.8 0.9798 [-1, -1, -3, -2, -1, -2, -2, -1, -4, -1] -bwahaha 0.4 1.0198 [0, 1, 0, 1, 0, 2, -1, -1, 2, 0] -bwahahah 2.5 0.92195 [3, 4, 2, 2, 2, 3, 1, 2, 2, 4] -calm 1.3 0.78102 [1, 1, 0, 1, 2, 3, 2, 1, 1, 1] -calmative 1.1 0.9434 [3, 2, -1, 1, 1, 1, 1, 1, 1, 1] -calmatives 0.5 0.80623 [-1, 1, 0, 1, 0, 0, 1, 2, 0, 1] -calmed 1.6 0.4899 [2, 2, 2, 1, 1, 1, 2, 1, 2, 2] -calmer 1.5 0.67082 [1, 2, 3, 1, 1, 1, 2, 1, 2, 1] -calmest 1.6 0.8 [3, 2, 2, 2, 1, 1, 0, 2, 1, 2] -calming 1.7 0.78102 [2, 1, 3, 2, 2, 1, 3, 1, 1, 1] -calmly 1.3 0.9 [0, 0, 1, 3, 2, 2, 1, 1, 2, 1] -calmness 1.7 0.9 [1, 1, 1, 2, 2, 2, 1, 4, 1, 2] -calmnesses 1.6 0.4899 [1, 2, 1, 2, 1, 2, 2, 2, 1, 2] -calmodulin 0.2 0.4 [0, 0, 0, 0, 0, 0, 1, 0, 0, 1] -calms 1.3 0.64031 [2, 1, 1, 2, 0, 1, 1, 2, 2, 1] -can't stand -2.0 0.63246 [-2, -2, -2, -1, -1, -2, -3, -2, -2, -3] -cancel -1.0 0.63246 [-2, -1, -1, -1, -1, 0, -1, 0, -2, -1] -cancelled -1.0 0.44721 [-1, -1, -1, -1, 0, -1, -1, -2, -1, -1] -cancelling -0.8 0.74833 [0, 0, -1, 0, -1, -1, 0, -2, -1, -2] -cancels -0.9 0.53852 [0, -1, 0, -1, -1, -1, -1, -1, -2, -1] -cancer -3.4 0.8 [-2, -4, -3, -4, -4, -2, -3, -4, -4, -4] -capable 1.6 0.4899 [1, 2, 2, 2, 1, 1, 2, 2, 1, 2] -captivated 1.6 0.4899 [2, 1, 2, 2, 2, 2, 1, 2, 1, 1] -care 2.2 0.74833 [2, 1, 2, 1, 2, 2, 3, 3, 3, 3] -cared 1.8 0.74833 [1, 2, 1, 3, 1, 2, 2, 2, 3, 1] -carefree 1.7 0.64031 [1, 1, 2, 2, 2, 2, 1, 1, 2, 3] -careful 0.6 1.11355 [3, 0, 0, 0, 1, 0, -1, 2, 1, 0] -carefully 0.5 0.67082 [1, 0, 1, 1, 0, 1, 0, 1, 1, -1] -carefulness 2.0 0.44721 [3, 2, 2, 1, 2, 2, 2, 2, 2, 2] -careless -1.5 0.5 [-2, -1, -1, -2, -2, -1, -2, -2, -1, -1] -carelessly -1.0 0.44721 [-1, -1, -1, -2, -1, 0, -1, -1, -1, -1] -carelessness -1.4 0.4899 [-2, -1, -1, -2, -1, -2, -1, -1, -2, -1] -carelessnesses -1.6 1.11355 [-4, -2, -2, -3, -1, 0, -1, -1, -1, -1] -cares 2.0 0.7746 [2, 3, 1, 3, 1, 2, 2, 2, 3, 1] -caring 2.2 0.4 [2, 3, 2, 2, 2, 2, 2, 3, 2, 2] -casual 0.8 0.74833 [1, 1, 0, 1, 0, 2, 0, 1, 2, 0] -casually 0.7 1.00499 [1, 0, 0, 0, 1, 0, 0, 3, 2, 0] -casualty -2.4 0.91652 [-4, -3, -3, -2, -1, -2, -3, -1, -2, -3] -catastrophe -3.4 0.4899 [-3, -3, -3, -4, -4, -3, -3, -3, -4, -4] -catastrophic -2.2 2.22711 [-3, -2, -4, -4, -4, -3, -2, -4, 2, 2] -cautious -0.4 0.66332 [0, 1, -1, 0, 0, 0, -1, -1, -1, -1] -celebrate 2.7 1.00499 [4, 4, 3, 2, 4, 2, 2, 2, 3, 1] -celebrated 2.7 0.78102 [2, 3, 3, 2, 3, 4, 3, 3, 1, 3] -celebrates 2.7 0.64031 [2, 3, 3, 2, 2, 3, 3, 3, 4, 2] -celebrating 2.7 0.64031 [3, 3, 4, 2, 2, 2, 3, 3, 2, 3] -censor -2.0 1.34164 [0, -3, -2, -3, -3, 0, -4, -1, -1, -3] -censored -0.6 1.68523 [-1, -1, -1, 2, -3, -2, -1, -1, -1, 3] -censors -1.2 1.07703 [-1, 0, -3, 0, -1, 0, -1, -2, -1, -3] -certain 1.1 0.7 [1, 0, 2, 0, 2, 2, 1, 1, 1, 1] -certainly 1.4 1.0198 [3, 2, 0, 1, 3, 1, 0, 1, 1, 2] -certainties 0.9 1.44568 [0, -2, 4, 0, 1, 1, 1, 1, 2, 1] -certainty 1.0 0.89443 [2, 1, 0, 1, 0, 0, 2, 2, 2, 0] -chagrin -1.9 0.53852 [-1, -2, -3, -2, -1, -2, -2, -2, -2, -2] -chagrined -1.4 1.2 [-1, -2, 2, -1, -2, -2, -2, -2, -2, -2] -challenge 0.3 1.00499 [1, 0, -1, 1, 1, -1, 1, 0, 2, -1] -challenged -0.4 1.62481 [0, -2, 1, -1, -3, -1, 3, -1, 1, -1] -challenger 0.5 1.43178 [0, 0, 2, -1, -2, 1, 3, 0, 2, 0] -challengers 0.4 1.56205 [0, -2, -1, 1, 1, 2, 3, 2, -1, -1] -challenges 0.3 1.48661 [0, -1, 2, -1, -2, 0, 3, 0, 2, 0] -challenging 0.6 0.91652 [0, 0, 0, 1, 1, -1, 0, 2, 2, 1] -challengingly -0.6 1.68523 [0, -1, -2, 1, -3, 2, -2, -1, 2, -2] -champ 2.1 0.83066 [2, 2, 2, 3, 2, 3, 2, 0, 3, 2] -champac -0.2 0.6 [0, 0, -2, 0, 0, 0, 0, 0, 0, 0] -champagne 1.2 1.07703 [1, 2, 2, 3, 0, 2, 0, 0, 2, 0] -champagnes 0.5 0.92195 [0, 0, 0, 0, 0, 1, 1, 3, 0, 0] -champaign 0.2 0.6 [0, 0, 0, 0, 2, 0, 0, 0, 0, 0] -champaigns 0.5 0.67082 [1, 0, 0, 0, 0, 0, 0, 1, 2, 1] -champaks -0.2 0.6 [0, 0, 0, 0, 0, 0, -2, 0, 0, 0] -champed 1.0 0.63246 [1, 1, 2, 1, 1, 2, 1, 0, 0, 1] -champer -0.1 0.53852 [0, -1, 1, 0, 0, 0, 0, -1, 0, 0] -champers 0.5 0.67082 [1, 0, 0, 0, 0, 0, 0, 1, 1, 2] -champerties -0.1 0.83066 [0, -1, 1, 1, 0, 0, 0, 0, -2, 0] -champertous 0.3 0.78102 [0, 0, 0, 1, -1, 2, 1, 0, 0, 0] -champerty -0.2 1.32665 [-2, -1, 0, -1, 0, 0, 0, -2, 2, 2] -champignon 0.4 0.8 [0, 0, 0, 0, 0, 2, 0, 2, 0, 0] -champignons 0.2 0.6 [0, 2, 0, 0, 0, 0, 0, 0, 0, 0] -champing 0.7 1.34536 [0, 2, 0, 3, 1, 1, 2, 0, -2, 0] -champion 2.9 0.83066 [3, 2, 3, 4, 4, 3, 2, 2, 4, 2] -championed 1.2 1.53623 [2, 1, 3, 1, 1, -3, 2, 2, 1, 2] -championing 1.8 0.9798 [1, 3, 2, 0, 3, 1, 2, 2, 1, 3] -champions 2.4 1.42829 [4, 0, 0, 3, 1, 3, 4, 3, 3, 3] -championship 1.9 1.04403 [3, 1, 1, 3, 2, 1, 3, 3, 0, 2] -championships 2.2 0.74833 [2, 2, 1, 2, 3, 2, 4, 2, 2, 2] -champs 1.8 0.4 [2, 2, 2, 2, 1, 2, 1, 2, 2, 2] -champy 1.0 1.0 [3, 0, 0, 0, 0, 2, 1, 2, 1, 1] -chance 1.0 0.7746 [1, 1, 0, 0, 0, 2, 1, 2, 1, 2] -chances 0.8 0.4 [0, 1, 1, 0, 1, 1, 1, 1, 1, 1] -chaos -2.7 0.9 [-2, -2, -3, -1, -4, -3, -3, -2, -3, -4] -chaotic -2.2 1.4 [-3, -2, -1, -2, -3, 1, -2, -2, -4, -4] -charged -0.8 0.87178 [-1, -2, -2, -1, -1, 0, -1, 1, 0, -1] -charges -1.1 0.7 [-2, -2, -2, -1, -1, 0, -1, -1, 0, -1] -charitable 1.7 0.64031 [1, 2, 1, 2, 2, 1, 2, 1, 3, 2] -charitableness 1.9 0.9434 [3, 1, 1, 3, 1, 3, 3, 2, 1, 1] -charitablenesses 1.6 1.74356 [2, 2, 3, 4, 1, -1, -2, 3, 2, 2] -charitably 1.4 0.66332 [1, 2, 1, 2, 2, 1, 0, 1, 2, 2] -charities 2.2 0.6 [3, 3, 2, 2, 1, 2, 2, 3, 2, 2] -charity 1.8 0.87178 [1, 3, 2, 2, 2, 1, 2, 0, 2, 3] -charm 1.7 0.78102 [3, 1, 1, 3, 2, 2, 1, 1, 1, 2] -charmed 2.0 0.63246 [3, 1, 2, 2, 2, 3, 1, 2, 2, 2] -charmer 1.9 0.53852 [3, 2, 2, 2, 2, 2, 1, 1, 2, 2] -charmers 2.1 0.83066 [2, 1, 2, 2, 4, 3, 2, 1, 2, 2] -charmeuse 0.3 0.78102 [0, 0, 0, 1, 0, 2, 1, 0, -1, 0] -charmeuses 0.4 0.66332 [0, 0, 1, 0, 1, 0, 0, 0, 0, 2] -charming 2.8 0.4 [3, 3, 3, 3, 3, 3, 2, 3, 2, 3] -charminger 1.5 0.67082 [2, 3, 1, 2, 1, 1, 2, 1, 1, 1] -charmingest 2.4 0.66332 [2, 3, 3, 1, 3, 2, 3, 3, 2, 2] -charmingly 2.2 0.87178 [2, 2, 2, 1, 2, 2, 3, 3, 4, 1] -charmless -1.8 0.87178 [-3, -1, -3, -1, -1, -1, -2, -1, -3, -2] -charms 1.9 0.7 [1, 2, 3, 2, 1, 2, 3, 1, 2, 2] -chastise -2.5 0.92195 [-4, -3, -2, -1, -4, -3, -2, -2, -2, -2] -chastised -2.2 1.16619 [-2, -3, -2, -4, -1, -1, -3, 0, -3, -3] -chastises -1.7 1.61555 [-3, -3, -3, -1, 1, -2, 1, -1, -2, -4] -chastising -1.7 0.78102 [-2, -3, -2, -2, -2, 0, -1, -1, -2, -2] -cheat -2.0 0.7746 [-2, -3, -3, -2, -2, -1, -1, -1, -2, -3] -cheated -2.3 0.64031 [-2, -4, -2, -2, -2, -2, -3, -2, -2, -2] -cheater -2.5 0.67082 [-2, -4, -2, -3, -2, -2, -3, -2, -3, -2] -cheaters -1.9 0.83066 [-2, -2, -2, -1, -1, -4, -2, -1, -2, -2] -cheating -2.6 0.91652 [-2, -3, -3, -2, -4, -4, -3, -2, -1, -2] -cheats -1.8 0.6 [-3, -1, -2, -1, -2, -1, -2, -2, -2, -2] -cheer 2.3 0.64031 [2, 1, 2, 2, 2, 3, 3, 3, 2, 3] -cheered 2.3 0.78102 [2, 3, 3, 4, 2, 1, 2, 2, 2, 2] -cheerer 1.7 0.45826 [1, 2, 2, 2, 1, 1, 2, 2, 2, 2] -cheerers 1.8 0.87178 [2, 2, 3, 2, 1, 2, 0, 1, 3, 2] -cheerful 2.5 0.67082 [3, 2, 3, 2, 2, 2, 4, 2, 3, 2] -cheerfuller 1.9 0.83066 [3, 3, 2, 3, 2, 1, 1, 2, 1, 1] -cheerfullest 3.2 0.87178 [4, 4, 4, 4, 3, 2, 2, 3, 2, 4] -cheerfully 2.1 0.83066 [3, 2, 2, 2, 1, 3, 1, 3, 1, 3] -cheerfulness 2.1 0.9434 [3, 2, 1, 2, 3, 4, 1, 2, 1, 2] -cheerier 2.6 0.4899 [2, 2, 3, 3, 2, 3, 3, 2, 3, 3] -cheeriest 2.2 0.6 [3, 2, 3, 1, 2, 2, 3, 2, 2, 2] -cheerily 2.5 0.67082 [3, 3, 2, 3, 2, 4, 2, 2, 2, 2] -cheeriness 2.5 0.67082 [3, 2, 4, 2, 3, 2, 3, 2, 2, 2] -cheering 2.3 0.64031 [3, 3, 2, 1, 3, 2, 2, 2, 3, 2] -cheerio 1.2 0.6 [2, 1, 1, 1, 2, 1, 1, 1, 2, 0] -cheerlead 1.7 0.78102 [1, 2, 0, 2, 2, 2, 2, 3, 1, 2] -cheerleader 0.9 0.9434 [1, 1, 0, 2, 1, 0, 0, 1, 0, 3] -cheerleaders 1.2 1.07703 [2, 0, 0, 1, 1, 0, 3, 3, 1, 1] -cheerleading 1.2 1.07703 [2, 2, 0, 0, 1, 0, 3, 2, 0, 2] -cheerleads 1.2 1.07703 [2, 3, 0, 3, 1, 0, 0, 1, 1, 1] -cheerled 1.5 1.11803 [0, 2, 1, 4, 2, 2, 2, 1, 1, 0] -cheerless -1.7 1.1 [-2, -3, -2, -2, -3, -2, -1, -1, 1, -2] -cheerlessly -0.8 1.98997 [-2, 4, -1, -2, -1, -2, -2, -2, 2, -2] -cheerlessness -1.7 1.48661 [-2, -1, -2, -3, -2, -4, -1, 2, -2, -2] -cheerly 2.4 0.66332 [2, 2, 3, 2, 2, 3, 4, 2, 2, 2] -cheers 2.1 1.3 [2, 2, 1, 3, 2, 3, 3, 4, -1, 2] -cheery 2.6 0.66332 [3, 2, 2, 3, 2, 3, 4, 2, 3, 2] -cherish 1.6 1.49666 [0, 3, 3, 3, 2, 2, 2, 1, -2, 2] -cherishable 2.0 1.41421 [-2, 2, 2, 2, 3, 2, 3, 3, 2, 3] -cherished 2.3 0.64031 [3, 2, 2, 3, 2, 2, 1, 3, 2, 3] -cherisher 2.2 0.4 [2, 2, 3, 2, 2, 2, 2, 3, 2, 2] -cherishers 1.9 0.7 [3, 3, 2, 2, 1, 1, 2, 2, 2, 1] -cherishes 2.2 0.74833 [2, 2, 3, 2, 2, 2, 2, 4, 2, 1] -cherishing 2.0 0.7746 [3, 3, 2, 2, 1, 2, 1, 3, 2, 1] -chic 1.1 1.3 [1, 2, 2, -2, 2, 0, 1, 1, 3, 1] -childish -1.2 0.74833 [-1, -1, -2, -3, -1, 0, -1, -1, -1, -1] -chilling -0.1 1.92094 [3, -2, 0, 1, -2, -2, -1, -2, 1, 3] -choke -2.5 0.92195 [-1, -2, -3, -3, -2, -4, -2, -4, -2, -2] -choked -2.1 1.3 [-4, -3, 0, -2, -1, -3, -3, -2, 0, -3] -chokes -2.0 0.89443 [-4, -3, -1, -2, -1, -2, -2, -2, -1, -2] -choking -2.0 1.26491 [-4, -2, -2, -3, -2, -2, -3, -1, 1, -2] -chuckle 1.7 0.45826 [2, 1, 2, 2, 2, 2, 1, 1, 2, 2] -chuckled 1.2 0.9798 [2, 2, 1, 1, 2, 0, 1, 2, -1, 2] -chucklehead -1.9 0.53852 [-2, -2, -1, -3, -2, -2, -2, -2, -1, -2] -chuckleheaded -1.3 1.84662 [-3, -4, -2, 0, 3, -1, -2, 0, -2, -2] -chuckleheads -1.1 0.9434 [-1, -2, 0, -1, -1, -3, 0, 0, -2, -1] -chuckler 0.8 1.07703 [2, 1, -1, 0, 2, 1, 1, 2, -1, 1] -chucklers 1.2 0.87178 [1, 1, 2, 3, 1, 0, 1, 0, 2, 1] -chuckles 1.1 1.13578 [2, 2, -1, 1, 2, 1, 1, 2, -1, 2] -chucklesome 1.1 0.53852 [1, 1, 2, 1, 1, 1, 0, 2, 1, 1] -chuckling 1.4 0.4899 [1, 2, 1, 2, 1, 1, 2, 2, 1, 1] -chucklingly 1.2 0.4 [1, 1, 1, 1, 2, 1, 1, 1, 2, 1] -clarifies 0.9 1.13578 [-2, 1, 0, 2, 1, 2, 2, 1, 1, 1] -clarity 1.7 0.78102 [2, 1, 2, 3, 3, 1, 1, 2, 1, 1] -classy 1.9 0.53852 [1, 2, 2, 1, 3, 2, 2, 2, 2, 2] -clean 1.7 0.78102 [3, 1, 2, 1, 2, 1, 3, 2, 1, 1] -cleaner 0.7 0.78102 [1, 0, 1, 0, 0, 0, 2, 1, 2, 0] -clear 1.6 1.2 [2, 1, 1, 0, 3, 1, 2, 4, 2, 0] -cleared 0.4 0.4899 [0, 0, 1, 1, 0, 0, 0, 0, 1, 1] -clearly 1.7 0.78102 [2, 2, 2, 2, 1, 2, 0, 2, 1, 3] -clears 0.3 0.78102 [0, 1, 0, 0, 0, -1, 1, 2, 0, 0] -clever 2.0 0.7746 [2, 1, 2, 2, 2, 1, 3, 1, 3, 3] -cleverer 2.0 0.44721 [2, 2, 2, 3, 2, 2, 1, 2, 2, 2] -cleverest 2.6 0.91652 [4, 3, 2, 2, 4, 3, 2, 1, 2, 3] -cleverish 1.0 1.18322 [1, 1, 1, 1, 1, 1, 2, 1, -2, 3] -cleverly 2.3 0.45826 [2, 3, 2, 2, 2, 3, 2, 2, 3, 2] -cleverness 2.3 0.9 [2, 4, 2, 2, 1, 3, 3, 3, 1, 2] -clevernesses 1.4 0.66332 [1, 1, 1, 2, 2, 2, 2, 0, 2, 1] -clouded -0.2 0.9798 [-2, 0, 2, 0, 0, -1, 0, -1, 0, 0] -clueless -1.5 0.5 [-1, -2, -1, -2, -2, -1, -1, -1, -2, -2] -cock -0.6 1.49666 [0, 0, -4, 0, 0, 1, 0, -3, 0, 0] -cocksucker -3.1 0.83066 [-3, -4, -2, -2, -4, -4, -4, -2, -3, -3] -cocksuckers -2.6 1.42829 [-4, -3, -4, -3, -3, 1, -3, -1, -3, -3] -cocky -0.5 1.0247 [2, 0, -1, 0, -1, -2, 0, -1, -1, -1] -coerced -1.5 0.67082 [-1, -2, -2, -2, -1, 0, -1, -2, -2, -2] -collapse -2.2 0.87178 [-3, -1, -2, -4, -3, -2, -2, -2, -1, -2] -collapsed -1.1 1.64012 [-1, -2, -2, -1, -2, -2, 2, 2, -3, -2] -collapses -1.2 0.87178 [-2, -1, -2, 0, -2, 0, 0, -2, -1, -2] -collapsing -1.2 0.6 [-1, -1, -2, -2, -2, -1, 0, -1, -1, -1] -collide -0.3 1.61555 [-3, 0, -1, 3, 0, -1, -1, 2, -1, -1] -collides -1.1 1.22066 [-2, -2, -1, -1, 0, -2, 2, -2, -1, -2] -colliding -0.5 1.36015 [-2, 2, -1, -1, 0, -1, -2, 2, -1, -1] -collision -1.5 0.67082 [-1, -1, -2, -1, -2, -1, -1, -3, -2, -1] -collisions -1.1 0.7 [0, -2, -1, 0, -1, -1, -2, -2, -1, -1] -colluding -1.2 1.32665 [-1, -1, -2, -2, 0, -3, 2, -2, -1, -2] -combat -1.4 1.0198 [0, -2, 0, -2, -2, -2, -1, -3, 0, -2] -combats -0.8 1.16619 [0, -2, -3, -1, 0, 0, 0, -1, 1, -2] -comedian 1.6 1.0198 [1, 0, 2, 3, 2, 0, 3, 1, 2, 2] -comedians 1.2 1.16619 [0, 0, 0, 2, 3, 1, 3, 2, 0, 1] -comedic 1.7 0.64031 [2, 1, 1, 3, 1, 2, 2, 2, 1, 2] -comedically 2.1 0.7 [3, 2, 2, 1, 2, 3, 3, 2, 1, 2] -comedienne 0.6 0.66332 [0, 2, 1, 0, 1, 1, 0, 1, 0, 0] -comediennes 1.6 1.11355 [2, 1, 3, 0, 0, 3, 1, 1, 2, 3] -comedies 1.7 1.00499 [0, 2, 1, 3, 3, 3, 1, 1, 2, 1] -comedo 0.3 0.9 [0, 0, 0, 0, -1, 0, 2, 0, 2, 0] -comedones -0.8 0.9798 [0, 0, 0, -1, 0, -3, 0, -1, -1, -2] -comedown -0.8 1.07703 [-1, -1, -1, 0, -2, -1, 2, -1, -2, -1] -comedowns -0.9 0.53852 [-1, -1, -1, -1, 0, -2, 0, -1, -1, -1] -comedy 1.5 0.67082 [1, 1, 2, 1, 3, 2, 1, 1, 2, 1] -comfort 1.5 0.67082 [1, 3, 1, 2, 1, 1, 2, 1, 1, 2] -comfortable 2.3 0.64031 [1, 2, 3, 2, 2, 3, 3, 3, 2, 2] -comfortableness 1.3 1.48661 [4, 2, 2, 3, 1, 1, 1, -1, -1, 1] -comfortably 1.8 0.74833 [1, 2, 2, 1, 3, 3, 1, 2, 1, 2] -comforted 1.8 0.6 [2, 2, 2, 0, 2, 2, 2, 2, 2, 2] -comforter 1.9 0.53852 [2, 3, 2, 2, 2, 1, 2, 2, 2, 1] -comforters 1.2 0.6 [2, 1, 0, 2, 1, 1, 2, 1, 1, 1] -comforting 1.7 0.64031 [1, 2, 1, 1, 2, 2, 2, 3, 2, 1] -comfortingly 1.7 0.45826 [1, 2, 1, 2, 2, 1, 2, 2, 2, 2] -comfortless -1.8 0.6 [-3, -2, -1, -2, -1, -2, -1, -2, -2, -2] -comforts 2.1 0.7 [3, 1, 3, 1, 2, 2, 3, 2, 2, 2] -commend 1.9 0.7 [1, 2, 2, 1, 2, 1, 2, 3, 2, 3] -commended 1.9 0.9434 [1, 3, 2, 3, 2, 2, 0, 1, 3, 2] -commit 1.2 0.87178 [1, 0, 2, 2, 0, 0, 2, 2, 1, 2] -commitment 1.6 0.91652 [3, 1, 2, 0, 3, 1, 2, 1, 2, 1] -commitments 0.5 0.92195 [1, 3, 0, 0, 0, 0, 0, 0, 0, 1] -commits 0.1 1.13578 [0, -1, 0, 2, 1, -1, 1, 1, -2, 0] -committed 1.1 0.7 [0, 1, 1, 2, 0, 2, 1, 1, 2, 1] -committing 0.3 1.18743 [0, 1, 0, 3, 0, -2, 1, 0, 0, 0] -compassion 2.0 0.7746 [3, 2, 1, 1, 2, 1, 3, 2, 2, 3] -compassionate 2.2 0.87178 [0, 3, 3, 2, 2, 3, 3, 2, 2, 2] -compassionated 1.6 0.66332 [3, 1, 2, 2, 1, 2, 2, 1, 1, 1] -compassionately 1.7 1.41774 [1, 3, 3, 2, 1, 2, 3, 2, -2, 2] -compassionateness 0.9 1.37477 [-3, 2, 2, 1, 1, 1, 2, 1, 1, 1] -compassionates 1.6 0.4899 [2, 1, 2, 2, 1, 2, 2, 1, 1, 2] -compassionating 1.6 0.91652 [3, 0, 2, 1, 3, 1, 2, 1, 2, 1] -compassionless -2.6 0.8 [-3, -2, -2, -3, -4, -3, -1, -2, -3, -3] -compelled 0.2 1.07703 [-1, 0, 0, 0, 1, 2, -1, -1, 2, 0] -compelling 0.9 0.94339 [1, 1, 1, 0, 1, 2, 2, -1, 2, 0] -competent 1.3 0.78102 [1, 3, 1, 1, 2, 1, 1, 0, 2, 1] -competitive 0.7 0.9 [0, 2, 0, 2, 0, 1, 0, 0, 0, 2] -complacent -0.3 1.1 [2, -1, -1, 1, -1, -1, -1, 1, -1, -1] -complain -1.5 0.67082 [-1, -1, -1, -2, -1, -2, -3, -2, -1, -1] -complainant -0.7 0.78102 [0, 0, -1, 0, 0, -2, 0, -1, -2, -1] -complainants -1.1 1.3 [-2, -1, 0, -2, -3, -2, -1, 1, -2, 1] -complained -1.7 0.64031 [-1, -3, -2, -2, -1, -1, -2, -2, -1, -2] -complainer -1.8 0.4 [-2, -2, -2, -2, -1, -2, -2, -2, -1, -2] -complainers -1.3 1.00499 [-2, -1, -1, -2, -3, 1, -1, -1, -2, -1] -complaining -0.8 1.249 [-2, -1, -1, -1, -2, -1, -1, 2, 1, -2] -complainingly -1.7 0.64031 [-1, -2, -1, -2, -1, -2, -1, -2, -3, -2] -complains -1.6 0.66332 [-1, -2, -1, -2, -2, -3, -1, -1, -1, -2] -complaint -1.2 1.249 [-1, -1, -2, -2, -1, -3, -1, -1, 2, -2] -complaints -1.7 0.45826 [-2, -2, -2, -1, -2, -2, -2, -1, -1, -2] -compliment 2.1 0.7 [2, 2, 3, 1, 2, 3, 3, 1, 2, 2] -complimentarily 1.7 0.45826 [2, 2, 2, 2, 1, 1, 2, 1, 2, 2] -complimentary 1.9 0.7 [1, 2, 2, 1, 2, 1, 2, 3, 3, 2] -complimented 1.8 1.4 [3, 2, 2, 2, 3, 2, -2, 3, 1, 2] -complimenting 2.3 0.64031 [2, 2, 1, 3, 3, 2, 2, 3, 3, 2] -compliments 1.7 0.45826 [2, 1, 2, 2, 1, 2, 2, 1, 2, 2] -comprehensive 1.0 0.63246 [1, 1, 1, 0, 2, 2, 1, 0, 1, 1] -conciliate 1.0 1.18322 [2, 1, 1, 0, 2, 2, -2, 2, 1, 1] -conciliated 1.1 0.9434 [1, 3, 0, 0, 2, 0, 2, 1, 1, 1] -conciliates 1.1 0.9434 [1, 3, 0, 0, 2, 0, 2, 1, 1, 1] -conciliating 1.3 0.78102 [2, 2, 1, 1, 2, 0, 2, 1, 2, 0] -condemn -1.6 1.0198 [-2, -2, -1, -2, -2, 1, -2, -3, -1, -2] -condemnation -2.8 0.9798 [-3, -4, -2, -4, -2, -4, -2, -1, -3, -3] -condemned -1.9 1.81384 [2, -2, -2, -3, -2, -3, -3, -4, 1, -3] -condemns -2.3 0.64031 [-2, -2, -3, -3, -3, -2, -2, -3, -1, -2] -confidence 2.3 0.64031 [3, 3, 3, 3, 1, 2, 2, 2, 2, 2] -confident 2.2 0.87178 [1, 3, 3, 2, 3, 1, 3, 2, 1, 3] -confidently 2.1 0.53852 [2, 2, 3, 1, 2, 2, 2, 2, 3, 2] -conflict -1.3 0.45826 [-2, -2, -1, -2, -1, -1, -1, -1, -1, -1] -conflicting -1.7 0.64031 [-1, -2, -3, -1, -2, -1, -2, -1, -2, -2] -conflictive -1.8 0.6 [-2, -2, -2, -2, -1, -1, -3, -2, -1, -2] -conflicts -1.6 0.8 [-1, -1, -1, -2, -1, -1, -3, -2, -1, -3] -confront -0.7 0.78102 [0, -1, -1, 0, 1, -1, -1, -2, -1, -1] -confrontation -1.3 1.55242 [-3, -2, -3, -2, -1, -2, 1, 2, -1, -2] -confrontational -1.6 0.66332 [-1, -2, -1, -2, -1, -2, -1, -2, -3, -1] -confrontationist -1.0 1.34164 [-1, -2, -2, 2, 1, -1, -2, -1, -2, -2] -confrontationists -1.2 1.46969 [-2, -3, -1, -2, 2, 1, -1, -2, -2, -2] -confrontations -1.5 1.0247 [-1, -3, -2, -1, -3, 0, -2, -2, 0, -1] -confronted -0.8 0.74833 [-1, -2, -1, -1, -1, -1, -1, -1, 1, 0] -confronter -0.3 1.1 [0, -2, 1, -2, 0, -1, -1, 0, 1, 1] -confronters -1.3 1.26886 [-3, -2, -2, -2, -1, -2, 1, 1, -1, -2] -confronting -0.6 1.11355 [-2, -1, -1, 0, -2, 2, -1, 0, 0, -1] -confronts -0.9 0.53852 [-1, -1, -1, -1, 0, -1, 0, -1, -2, -1] -confuse -0.9 0.3 [-1, -1, -1, -1, -1, -1, -1, -1, 0, -1] -confused -1.3 0.45826 [-1, -2, -1, -1, -1, -1, -1, -1, -2, -2] -confusedly -0.6 1.42829 [-3, -1, -1, 1, -1, -1, -2, 2, 1, -1] -confusedness -1.5 0.67082 [-3, -1, -1, -2, -1, -2, -2, -1, -1, -1] -confuses -1.3 0.45826 [-1, -2, -1, -1, -1, -1, -1, -1, -2, -2] -confusing -0.9 0.7 [-1, -1, -1, -2, -1, -1, 1, -1, -1, -1] -confusingly -1.4 0.66332 [-1, -1, -1, -1, -3, -1, -2, -1, -1, -2] -confusion -1.2 0.6 [-1, -1, -1, -1, -1, -2, 0, -1, -2, -2] -confusional -1.2 0.6 [-2, -2, 0, -1, -2, -1, -1, -1, -1, -1] -confusions -0.9 1.04403 [-1, -2, -1, -1, -1, 2, -2, -1, -1, -1] -congrats 2.4 0.91652 [1, 3, 3, 3, 2, 2, 4, 1, 2, 3] -congratulate 2.2 1.249 [3, 3, 2, 3, -1, 2, 1, 3, 3, 3] -congratulation 2.9 0.9434 [3, 3, 3, 2, 4, 2, 4, 3, 4, 1] -congratulations 2.9 0.53852 [2, 3, 3, 3, 3, 3, 3, 3, 4, 2] -consent 0.9 0.7 [0, 0, 1, 1, 1, 2, 1, 2, 0, 1] -consents 1.0 0.63246 [0, 2, 1, 0, 1, 1, 1, 2, 1, 1] -considerate 1.9 1.22066 [2, -1, 3, 2, 2, 2, 4, 1, 2, 2] -consolable 1.1 0.53852 [1, 1, 2, 1, 0, 1, 1, 1, 2, 1] -conspiracy -2.4 0.66332 [-2, -2, -3, -3, -2, -2, -4, -2, -2, -2] -constrained -0.4 1.0198 [-1, 0, -1, -1, -1, -1, 2, -1, 1, -1] -contagion -2.0 1.18322 [-1, 0, -2, -1, -2, -4, -2, -4, -2, -2] -contagions -1.5 0.92195 [-2, -2, -2, -2, 1, -2, -1, -1, -2, -2] -contagious -1.4 0.91652 [-2, -2, -2, 0, -1, -1, -2, 0, -1, -3] -contempt -2.8 0.6 [-3, -3, -4, -2, -3, -2, -3, -3, -2, -3] -contemptibilities -2.0 1.09545 [-2, 1, -2, -2, -3, -3, -3, -2, -2, -2] -contemptibility -0.9 1.51327 [-2, -1, -3, -1, 0, -3, -1, 1, 2, -1] -contemptible -1.6 1.68523 [-2, -2, -3, -3, -2, -3, -1, -3, 1, 2] -contemptibleness -1.9 0.7 [-2, -2, -1, -2, -2, -1, -1, -2, -3, -3] -contemptibly -1.4 1.49666 [-3, 0, -2, -3, -2, -2, -1, -3, 1, 1] -contempts -1.0 1.48324 [-2, -2, -1, 0, 1, -1, -2, -3, 2, -2] -contemptuous -2.2 1.83303 [-2, -3, -4, -2, -3, -3, 3, -2, -3, -3] -contemptuously -2.4 0.8 [-1, -3, -2, -3, -3, -2, -1, -3, -3, -3] -contemptuousness -1.1 1.57797 [-3, -1, -2, 3, -2, 0, -1, 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1.16619 [1, 2, -2, 2, 1, 2, 2, 1, 2, 1] -cool 1.3 0.64031 [1, 1, 2, 1, 1, 1, 2, 2, 2, 0] -cornered -1.1 0.83066 [-1, -1, -3, -1, 0, -1, 0, -1, -2, -1] -corpse -2.7 1.18743 [-3, -4, 0, -4, -3, -3, -3, -1, -3, -3] -costly -0.4 1.0198 [-1, 0, -1, -1, 2, -1, -1, 1, -1, -1] -courage 2.2 0.74833 [2, 3, 1, 2, 3, 2, 3, 3, 1, 2] -courageous 2.4 0.4899 [2, 3, 3, 3, 3, 2, 2, 2, 2, 2] -courageously 2.3 0.78102 [3, 3, 3, 1, 3, 3, 2, 2, 2, 1] -courageousness 2.1 0.7 [3, 3, 1, 2, 1, 2, 2, 2, 3, 2] -courteous 2.3 0.45826 [2, 2, 2, 3, 3, 2, 3, 2, 2, 2] -courtesy 1.5 0.67082 [1, 1, 2, 3, 1, 2, 1, 1, 2, 1] -cover-up -1.2 1.16619 [-1, -1, -4, -1, 0, 0, -2, 0, -1, -2] -coward -2.0 0.63246 [-3, -3, -1, -2, -2, -1, -2, -2, -2, -2] -cowardly -1.6 0.8 [-1, -1, -1, -3, -1, -2, -3, -2, -1, -1] -coziness 1.5 1.11803 [2, 3, 1, 3, 1, 2, 2, -1, 1, 1] -cramp -0.8 1.66132 [0, -1, -1, -3, -3, 1, -2, 1, -2, 2] -crap -1.6 0.66332 [-1, -1, -2, -2, -1, -2, -3, -1, -1, -2] -crappy -2.6 0.8 [-1, -3, -3, -2, -3, -4, -2, -2, -3, -3] -crash -1.7 1.18743 [-2, -3, -2, -1, -2, 0, 0, -1, -4, -2] -craze -0.6 1.49666 [0, -3, -1, -1, -2, 0, 0, -1, 3, -1] -crazed -0.5 2.24722 [-2, -1, 3, -3, -3, 1, 1, -1, 3, -3] -crazes 0.2 1.6 [-2, -1, 3, -1, -1, 1, 2, 0, 2, -1] -crazier -0.1 1.7 [2, -2, -2, 0, -1, 1, 3, 1, -1, -2] -craziest -0.2 2.13542 [2, -2, -3, 3, -2, 0, 2, 2, -2, -2] -crazily -1.5 0.67082 [-2, -1, -1, -2, -1, -3, -2, -1, -1, -1] -craziness -1.6 0.66332 [-2, 0, -2, -1, -2, -1, -2, -2, -2, -2] -crazinesses -1.0 1.48324 [1, -2, -2, 2, -1, 0, -2, -1, -3, -2] -crazing -0.5 0.80623 [0, 0, 0, 0, -2, -1, -2, 0, 0, 0] -crazy -1.4 1.35647 [-2, -1, -1, -2, -3, -2, -3, -1, 2, -1] -crazyweed 0.8 0.9798 [2, 0, 0, 0, 0, 2, 2, 0, 2, 0] -create 1.1 1.13578 [1, 1, 1, 2, 3, 0, 0, 0, 3, 0] -created 1.0 0.7746 [2, 0, 0, 1, 1, 2, 0, 1, 1, 2] -creates 1.1 0.83066 [2, 0, 0, 1, 1, 2, 0, 1, 2, 2] -creatin 0.1 0.53852 [0, 0, 0, 1, 0, 0, 0, 1, -1, 0] -creatine 0.2 0.6 [0, 0, 0, 0, 0, 0, 0, 0, 0, 2] -creating 1.2 1.249 [0, 0, 0, 0, 4, 1, 1, 2, 2, 2] -creatinine 0.4 1.2 [0, 0, 0, 4, 0, 0, 0, 0, 0, 0] -creation 1.1 0.83066 [2, 1, 1, 2, 0, 0, 0, 1, 2, 2] -creationism 0.7 0.9 [2, 0, 0, 0, 0, 0, 2, 0, 2, 1] -creationisms 1.1 1.37477 [2, 4, 0, 3, 0, 0, 1, 1, 0, 0] -creationist 0.8 0.9798 [2, 0, 0, 0, 0, 0, 2, 0, 2, 2] -creationists 0.5 0.67082 [0, 0, 0, 1, 1, 0, 2, 0, 1, 0] -creations 1.6 0.91652 [3, 2, 1, 1, 1, 3, 1, 2, 2, 0] -creative 1.9 0.53852 [2, 1, 2, 2, 2, 1, 3, 2, 2, 2] -creatively 1.5 0.80623 [2, 2, 1, 0, 2, 2, 2, 0, 2, 2] -creativeness 1.8 1.07703 [3, 2, 1, 0, 2, 2, 2, 0, 3, 3] -creativities 1.7 1.00499 [2, 2, 1, 0, 3, 2, 2, 0, 2, 3] -creativity 1.6 0.8 [2, 1, 2, 2, 3, 2, 0, 2, 1, 1] -credit 1.6 0.91652 [1, 1, 0, 2, 3, 3, 2, 2, 1, 1] -creditabilities 1.4 1.28062 [0, 3, -1, 2, 2, 2, 1, 2, 0, 3] -creditability 1.9 1.3 [3, 0, 4, 0, 1, 1, 3, 2, 2, 3] -creditable 1.8 0.6 [2, 1, 1, 1, 2, 2, 3, 2, 2, 2] -creditableness 1.2 0.74833 [1, 1, 1, 3, 2, 1, 0, 1, 1, 1] -creditably 1.7 0.78102 [3, 1, 1, 0, 2, 2, 2, 2, 2, 2] 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-2, -2, -3, 2, -3] -cry -2.1 0.53852 [-2, -2, -2, -1, -2, -2, -3, -3, -2, -2] -crying -2.1 0.7 [-3, -1, -2, -2, -3, -2, -3, -2, -1, -2] -cunt -2.2 2.08806 [-4, -1, -4, -2, 2, -4, -4, -3, 1, -3] -cunts -2.9 1.44568 [-3, -4, -3, -4, -4, -4, -3, 1, -3, -2] -curious 1.3 0.78102 [0, 1, 0, 2, 2, 2, 1, 1, 2, 2] -curse -2.5 0.67082 [-3, -3, -4, -2, -2, -3, -2, -2, -2, -2] -cut -1.1 0.53852 [-2, -1, -1, -1, 0, -1, -1, -1, -2, -1] -cute 2.0 0.63246 [1, 3, 1, 2, 2, 2, 2, 3, 2, 2] -cutely 1.3 1.00499 [3, 1, 1, 2, 2, 1, 1, 2, -1, 1] -cuteness 2.3 0.45826 [2, 2, 2, 3, 2, 3, 3, 2, 2, 2] -cutenesses 1.9 0.53852 [1, 2, 2, 1, 3, 2, 2, 2, 2, 2] -cuter 2.3 0.9 [1, 2, 3, 4, 1, 2, 2, 3, 3, 2] -cutes 1.8 0.87178 [1, 2, 3, 0, 1, 2, 2, 2, 3, 2] -cutesie 1.0 1.18322 [2, 2, 1, 1, 0, 2, 2, -1, 2, -1] -cutesier 1.5 1.20416 [3, -1, 2, 1, 1, 2, 2, 3, 0, 2] -cutesiest 2.2 1.4 [3, 3, 4, 2, 2, 4, 2, -1, 2, 1] -cutest 2.8 0.87178 [2, 3, 3, 4, 4, 3, 1, 3, 2, 3] -cutesy 2.1 0.83066 [2, 1, 2, 2, 4, 3, 1, 2, 2, 2] -cutey 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0.53852 [-2, -2, -2, -2, -2, -1, -2, -2, -3, -1] -damagers -2.0 0.63246 [-2, -3, -1, -2, -2, -1, -3, -2, -2, -2] -damages -1.9 1.04403 [-1, 0, -2, -2, -2, -4, -2, -1, -3, -2] -damaging -2.3 0.9 [-4, -1, -2, -4, -2, -2, -2, -2, -2, -2] -damagingly -2.0 0.7746 [-2, -2, -2, -2, -1, -3, -3, -1, -3, -1] -damn -1.7 0.64031 [-2, -1, -2, -1, -1, -3, -1, -2, -2, -2] -damnable -1.7 0.45826 [-2, -1, -2, -2, -1, -2, -1, -2, -2, -2] -damnableness -1.8 0.74833 [-2, -2, -2, -2, -1, -2, -2, 0, -3, -2] -damnably -1.7 0.45826 [-2, -1, -2, -2, -1, -2, -1, -2, -2, -2] -damnation -2.6 1.0198 [-3, -2, -3, -4, -4, -3, -1, -2, -1, -3] -damnations -1.4 1.11355 [-2, -1, -2, -3, -2, 0, -1, 1, -2, -2] -damnatory -2.6 1.42829 [-4, -1, -4, -2, -1, -3, -3, 0, -4, -4] -damned -1.6 0.66332 [-1, -1, -3, -1, -2, -2, -1, -2, -1, -2] -damnedest -0.5 1.5 [1, 0, 0, 0, -1, -1, 0, 2, -3, -3] -damnified -2.8 0.9798 [-1, -3, -3, -2, -2, -3, -4, -4, -2, -4] -damnifies -1.8 0.87178 [-2, -2, -1, -2, -3, -2, -2, 0, -1, -3] -damnify -2.2 0.74833 [-2, -2, -4, -2, -3, -2, -1, -2, -2, -2] -damnifying -2.4 0.66332 [-3, -1, -2, -2, -2, -2, -3, -3, -3, -3] -damning -1.4 0.8 [-1, -3, -1, -1, -1, -1, -3, -1, -1, -1] -damningly -2.0 1.61245 [-3, -2, -1, -4, -3, -3, -3, -2, 2, -1] -damnit -2.4 1.0198 [-3, -3, -2, -2, -3, -2, -4, -2, 0, -3] -damns -2.2 0.74833 [-2, -3, -2, -1, -3, -2, -1, -2, -3, -3] -danger -2.4 0.91652 [-3, -1, -2, -3, -3, -3, -2, -1, -2, -4] -dangered -2.4 0.66332 [-3, -3, -2, -3, -3, -2, -1, -2, -3, -2] -dangering -2.5 0.80623 [-1, -2, -2, -3, -4, -3, -3, -2, -2, -3] -dangerous -2.1 0.3 [-2, -3, -2, -2, -2, -2, -2, -2, -2, -2] -dangerously -2.0 0.44721 [-2, -2, -2, -1, -2, -3, -2, -2, -2, -2] -dangerousness -2.0 0.44721 [-2, -3, -2, -1, -2, -2, -2, -2, -2, -2] -dangers -2.2 0.87178 [-1, -1, -2, -4, -2, -3, -3, -2, -2, -2] -daredevil 0.5 0.92195 [0, 1, -1, 2, 0, 0, 1, 0, 0, 2] -daring 1.5 1.5 [3, 0, 1, 1, 2, -2, 3, 2, 2, 3] -daringly 2.1 0.7 [3, 1, 2, 1, 3, 2, 2, 3, 2, 2] -daringness 1.4 0.8 [0, 2, 1, 3, 1, 2, 2, 1, 1, 1] -darings 0.4 0.91652 [0, 1, 1, 1, 0, 1, 0, 1, -2, 1] -darkest -2.2 0.6 [-3, -3, -2, -2, -3, -2, -1, -2, -2, -2] -darkness -1.0 0.44721 [-2, -1, -1, -1, -1, 0, -1, -1, -1, -1] -darling 2.8 0.6 [3, 3, 2, 2, 3, 3, 4, 2, 3, 3] -darlingly 1.6 0.66332 [1, 1, 2, 3, 1, 1, 2, 2, 2, 1] -darlingness 2.3 0.45826 [3, 3, 2, 2, 2, 2, 2, 2, 3, 2] -darlings 2.2 0.4 [3, 2, 2, 2, 2, 2, 2, 2, 3, 2] -dauntless 2.3 0.78102 [3, 3, 2, 1, 3, 3, 2, 1, 2, 3] -daze -0.7 0.78102 [-1, 0, -1, -1, 1, -1, -1, 0, -1, -2] -dazed -0.7 0.64031 [0, -1, -1, 0, -1, -1, 0, -1, 0, -2] -dazedly -0.4 1.0198 [-1, -1, -1, -1, -1, 2, -1, 1, 0, -1] -dazedness -0.5 1.11803 [-1, 2, 0, -1, -1, -1, 1, -2, -1, -1] -dazes -0.3 0.78102 [0, -1, 0, 0, 0, -1, 0, 1, 0, -2] -dead -3.3 1.00499 [-4, -4, -1, -4, -4, -3, -4, -2, -3, -4] -deadlock -1.4 0.8 [-2, -2, -1, -3, -1, 0, -2, -1, -1, -1] -deafening -1.2 1.6 [-4, -2, 0, -3, 1, -2, 1, -2, -1, 0] -dear 1.6 1.35647 [3, 3, 2, 2, 2, 2, 1, -2, 1, 2] -dearer 1.9 0.7 [2, 2, 1, 2, 1, 1, 2, 3, 2, 3] -dearest 2.6 0.8 [1, 2, 3, 3, 2, 2, 3, 3, 4, 3] -dearie 2.2 0.6 [2, 2, 2, 3, 2, 1, 3, 2, 3, 2] -dearies 1.0 1.0 [0, 1, 2, -1, 1, 1, 1, 1, 1, 3] -dearly 1.8 1.07703 [3, 4, 2, 1, 1, 0, 1, 2, 2, 2] -dearness 2.0 0.7746 [1, 1, 2, 3, 2, 2, 2, 3, 1, 3] -dears 1.9 0.83066 [3, 2, 2, 2, 1, 2, 2, 2, 0, 3] -dearth -2.3 1.00499 [-2, -2, -1, -4, -2, -1, -2, -4, -3, -2] -dearths -0.9 0.7 [0, -1, 0, -1, -2, -1, -2, 0, -1, -1] -deary 1.9 0.83066 [3, 2, 2, 1, 2, 2, 3, 2, 0, 2] -death -2.9 1.04403 [-3, -4, -4, -3, -3, -1, -1, -4, -3, -3] -debonair 0.8 1.72047 [1, -1, -1, -3, 2, 2, 2, 2, 2, 2] -debt -1.5 1.0247 [-2, -1, -2, -3, 1, -2, -2, -1, -1, -2] -decay -1.7 0.45826 [-2, -2, -2, -1, -2, -1, -1, -2, -2, -2] -decayed -1.6 0.91652 [-2, -2, -2, -2, -2, 1, -1, -2, -2, -2] -decayer -1.6 0.4899 [-2, -2, -2, -1, -2, -1, -1, -1, -2, -2] -decayers -1.6 0.4899 [-2, -1, -1, -2, -1, -2, -2, -2, -1, -2] -decaying -1.7 0.64031 [-1, -1, -2, -2, -1, -2, -3, -2, -2, -1] -decays -1.7 0.45826 [-2, -1, -2, -2, -1, -2, -1, -2, -2, -2] -deceit -2.0 1.34164 [-3, -2, -2, -3, -3, 0, 1, -2, -3, -3] -deceitful -1.9 1.22066 [-3, -2, -2, -3, -1, -3, -1, -3, -2, 1] -deceive -1.7 0.64031 [-1, -2, -2, -1, -2, -1, -1, -3, -2, -2] -deceived -1.9 1.3 [1, -3, -3, -1, -1, -2, -2, -2, -4, -2] -deceives -1.6 1.56205 [-1, 2, -2, -2, -3, -2, 0, -2, -4, -2] -deceiving -1.4 1.68523 [-3, -2, -2, -2, -1, -1, 1, -4, 2, -2] -deception -1.9 1.04403 [-1, -2, -2, -4, -2, 0, -2, -1, -3, -2] -decisive 0.9 0.83066 [2, 2, 0, 1, -1, 1, 1, 1, 1, 1] -dedicated 2.0 0.44721 [2, 2, 2, 2, 2, 2, 2, 1, 3, 2] -defeat -2.0 1.67332 [0, -4, -3, -4, -2, -1, -2, -1, 1, -4] -defeated -2.1 0.83066 [-1, -2, -1, -2, -3, -2, -2, -2, -2, -4] -defeater -1.4 0.8 [-2, -1, -1, -3, -2, -1, -2, -1, 0, -1] -defeaters -0.9 0.9434 [-2, 0, -1, -2, -2, -1, 0, -1, 1, -1] -defeating -1.6 0.66332 [-2, -2, -1, -1, -1, -1, -2, -2, -3, -1] -defeatism -1.3 1.00499 [-1, -2, -2, -1, -1, -3, 1, -2, -1, -1] -defeatist -1.7 0.9 [0, -1, -2, -3, -1, -2, -1, -3, -2, -2] -defeatists -2.1 0.9434 [-3, -2, -1, -2, -2, -1, -3, -4, -1, -2] -defeats -1.3 1.1 [-1, 0, -1, -2, -1, -2, -3, 1, -2, -2] -defeature -1.9 1.22066 [1, -2, -2, -2, -2, -1, -2, -3, -4, -2] -defeatures -1.5 1.20416 [-3, -2, -3, 0, -1, -1, -2, 0, -3, 0] -defect -1.4 0.8 [-2, -1, -2, -1, 0, -2, -3, -1, -1, -1] -defected -1.7 0.64031 [-3, -2, -2, -2, -1, -1, -1, -2, -1, -2] -defecting -1.8 0.6 [-2, -1, -2, -2, -2, -1, -3, -1, -2, -2] -defection -1.4 0.66332 [-1, -2, -1, -2, 0, -1, -2, -2, -2, -1] -defections -1.5 0.67082 [-2, -2, -2, -1, 0, -1, -2, -2, -1, -2] -defective -1.9 0.53852 [-2, -1, -2, -3, -2, -2, -2, -2, -1, -2] -defectively -2.1 0.83066 [-1, -3, -2, -1, -3, -2, -1, -3, -2, -3] -defectiveness -1.8 0.74833 [-1, -1, -2, -2, -2, -3, -1, -1, -2, -3] -defectives -1.8 0.74833 [-3, -3, -1, -2, -2, -1, -2, -1, -1, -2] -defector -1.9 0.53852 [-2, -3, -2, -2, -1, -2, -1, -2, -2, -2] -defectors -1.3 1.26886 [-2, -1, -2, 0, -1, -1, -2, -4, 1, -1] -defects -1.7 0.9 [-1, -2, -1, 0, -2, -3, -2, -2, -1, -3] -defence 0.4 0.91652 [0, 0, 0, 1, 0, 0, 0, 2, 2, -1] -defenceman 0.4 1.11355 [3, 0, 0, 0, 0, -1, 2, 0, 0, 0] -defencemen 0.6 0.91652 [0, 0, 0, 2, 0, 2, 0, 2, 0, 0] -defences -0.2 1.16619 [0, 0, 0, 1, -2, -1, 0, -2, 0, 2] -defender 0.4 1.0198 [0, 0, 2, 1, -1, 2, 0, 1, -1, 0] -defenders 0.3 0.78102 [0, 1, 1, 0, 0, 0, 0, -1, 2, 0] -defense 0.5 0.67082 [0, 1, 0, 1, 2, 1, 0, 0, 0, 0] -defenseless -1.4 0.8 [0, -1, -1, -2, -1, -1, -3, -1, -2, -2] -defenselessly -1.1 0.9434 [-2, -2, -2, -1, 0, -1, 1, -1, -1, -2] -defenselessness -1.3 1.18743 [-3, -1, -3, 0, -2, -1, -1, -2, 1, -1] -defenseman 0.1 1.13578 [2, 0, 0, 0, 0, 0, -1, 0, 2, -2] -defensemen -0.4 0.66332 [0, 0, -2, 0, -1, -1, 0, 0, 0, 0] -defenses 0.7 1.41774 [3, 0, 2, 0, -1, 1, -2, 1, 1, 2] -defensibility 0.4 1.56205 [1, -2, 1, 0, 4, 0, -1, 1, -1, 1] -defensible 0.8 0.87178 [0, 2, 0, 0, 1, 0, 2, 0, 2, 1] -defensibly 0.1 1.13578 [0, -1, 0, 0, -1, 0, 3, 0, -1, 1] -defensive 0.1 1.13578 [2, -1, 0, -1, 2, 0, -1, 1, 0, -1] -defensively -0.6 0.91652 [1, 1, -1, -1, -1, -1, -2, -1, 0, -1] -defensiveness -0.4 1.11355 [2, -1, -1, -1, -1, 0, 0, 1, -2, -1] -defensives -0.3 1.00499 [-1, 0, 0, -1, 0, -1, 0, -2, 2, 0] -defer -1.2 0.6 [-1, -2, -1, 0, -1, -2, -2, -1, -1, -1] -deferring -0.7 0.64031 [0, 0, -2, -1, -1, -1, -1, 0, -1, 0] -defiant -0.9 1.44568 [-1, -2, -1, 2, 1, -2, 0, -1, -3, -2] -deficit -1.7 0.78102 [-3, -3, -2, -1, -2, -2, -1, -1, -1, -1] -definite 1.1 0.7 [2, 1, 0, 1, 0, 1, 1, 2, 2, 1] -definitely 1.7 0.64031 [2, 2, 2, 2, 2, 1, 2, 2, 0, 2] -degradable -1.0 1.26491 [-1, -2, 0, -2, 0, -1, -2, -2, 2, -2] -degradation -2.4 1.0198 [-4, -3, -3, -3, -3, -2, -2, -2, 0, -2] -degradations -1.5 0.67082 [-2, -1, -3, -1, -2, -2, -1, -1, -1, -1] -degradative -2.0 0.63246 [-2, -1, -3, -2, -2, -2, -1, -2, -3, -2] -degrade -1.9 0.7 [-3, -2, -1, -3, -1, -2, -2, -2, -1, -2] -degraded -1.8 0.87178 [-2, -3, -1, 0, -2, -1, -2, -2, -3, -2] -degrader -2.0 0.63246 [-2, -3, -1, -1, -2, -2, -3, -2, -2, -2] -degraders -2.0 0.63246 [-2, -3, -1, -2, -2, -2, -3, -2, -1, -2] -degrades -2.1 0.83066 [-3, -1, -3, -3, -2, -3, -1, -1, -2, -2] -degrading -2.8 0.87178 [-3, -3, -2, -3, -4, -2, -3, -4, -3, -1] -degradingly -2.7 0.64031 [-3, -2, -3, -4, -2, -3, -3, -2, -3, -2] -dehumanize -1.8 2.18174 [-2, -4, -1, -3, 2, -4, -3, 2, -1, -4] -dehumanized -1.9 0.7 [-2, -2, -2, -2, -1, -3, -2, -1, -3, -1] -dehumanizes -1.5 0.67082 [-1, -1, -1, -2, -1, -3, -2, -1, -2, -1] -dehumanizing -2.4 0.91652 [-2, -3, -4, -2, -3, -2, -3, -1, -1, -3] -deject -2.2 0.6 [-2, -3, -2, -3, -2, -2, -3, -2, -1, -2] -dejected -2.2 0.74833 [-2, -1, -2, -3, -2, -2, -2, -2, -2, -4] -dejecting -2.3 0.64031 [-2, -2, -3, -2, -3, -2, -1, -2, -3, -3] -dejects -2.0 0.63246 [-2, -2, -3, -1, -2, -1, -3, -2, -2, -2] -delay -1.3 0.45826 [-1, -1, -1, -2, -1, -1, -2, -1, -2, -1] -delayed -0.9 0.3 [-1, -1, 0, -1, -1, -1, -1, -1, -1, -1] -delectable 2.9 0.83066 [3, 4, 3, 2, 3, 4, 3, 1, 3, 3] -delectables 1.4 1.35647 [1, 2, 0, 4, 2, 1, 3, -1, 1, 1] -delectably 2.8 0.74833 [3, 4, 3, 2, 3, 3, 3, 1, 3, 3] -delicate 0.2 0.74833 [2, 0, 0, 0, 0, 0, 1, 0, -1, 0] -delicately 1.0 1.26491 [1, 1, 2, 0, 1, 3, -1, 2, -1, 2] -delicates 0.6 1.35647 [3, 0, 2, 1, -1, -1, 2, 0, 1, -1] -delicatessen 0.4 0.8 [0, 0, 0, 0, 0, 0, 0, 2, 2, 0] -delicatessens 0.4 0.8 [0, 0, 2, 0, 0, 2, 0, 0, 0, 0] -delicious 2.7 0.64031 [3, 2, 3, 4, 2, 3, 3, 3, 2, 2] -deliciously 1.9 0.83066 [2, 2, 1, 3, 1, 3, 2, 3, 1, 1] -deliciousness 1.8 0.87178 [1, 2, 3, 3, 2, 2, 1, 2, 2, 0] -delight 2.9 0.7 [2, 3, 4, 4, 3, 2, 3, 3, 2, 3] -delighted 2.3 0.64031 [3, 3, 2, 3, 2, 1, 3, 2, 2, 2] -delightedly 2.4 0.4899 [2, 3, 3, 3, 2, 2, 3, 2, 2, 2] -delightedness 2.1 0.53852 [2, 2, 2, 2, 3, 2, 3, 2, 1, 2] -delighter 2.0 0.63246 [3, 2, 2, 3, 1, 2, 2, 1, 2, 2] -delighters 2.6 0.66332 [3, 2, 2, 2, 3, 2, 3, 2, 4, 3] -delightful 2.8 0.6 [4, 3, 2, 3, 3, 3, 2, 2, 3, 3] -delightfully 2.7 0.45826 [3, 2, 2, 2, 3, 3, 3, 3, 3, 3] -delightfulness 2.1 0.7 [3, 2, 3, 1, 2, 3, 2, 2, 2, 1] -delighting 1.6 1.90788 [3, 3, 3, 2, 3, 2, 3, -2, -2, 1] -delights 2.0 1.54919 [2, 3, 1, -2, 2, 4, 2, 3, 3, 2] -delightsome 2.3 0.45826 [3, 3, 2, 2, 2, 3, 2, 2, 2, 2] -demand -0.5 0.67082 [0, 0, 0, 0, 0, -1, -1, -1, 0, -2] -demanded -0.9 0.7 [-2, 0, 0, 0, -2, -1, -1, -1, -1, -1] -demanding -0.9 0.53852 [-1, -2, 0, -1, -1, -1, -1, -1, 0, -1] -demonstration 0.4 0.91652 [0, 0, 0, 0, 0, 0, 3, 1, 0, 0] -demoralized -1.6 1.62481 [-2, -2, -2, -2, -3, 2, -2, -3, 1, -3] -denied -1.9 0.53852 [-2, -3, -1, -2, -2, -1, -2, -2, -2, -2] -denier -1.5 0.67082 [-1, -1, -1, -1, -2, -3, -2, -2, -1, -1] -deniers -1.1 1.13578 [-2, 0, -2, -1, -3, 1, 0, -1, -2, -1] -denies -1.8 0.6 [-1, -2, -1, -1, -2, -3, -2, -2, -2, -2] -denounce -1.4 0.91652 [-2, -1, -2, -1, 1, -2, -2, -1, -2, -2] -denounces -1.9 0.7 [-1, -3, -2, -3, -2, -1, -2, -2, -2, -1] -deny -1.4 0.4899 [-1, -1, -1, -1, -2, -1, -2, -2, -1, -2] -denying -1.4 0.4899 [-1, -1, -1, -2, -2, -2, -1, -2, -1, -1] -depress -2.2 0.74833 [-2, -1, -3, -3, -2, -2, -3, -3, -1, -2] -depressant -1.6 1.11355 [-3, -1, 0, -1, 0, -2, -3, -1, -3, -2] -depressants -1.6 0.91652 [-1, -1, -3, -3, -2, 0, -1, -2, -2, -1] -depressed -2.3 0.45826 [-2, -2, -2, -2, -2, -3, -3, -3, -2, -2] -depresses -2.2 0.6 [-2, -2, -2, -2, -3, -3, -1, -2, -3, -2] -depressible -1.7 0.78102 [-2, -1, 0, -3, -2, -2, -2, -1, -2, -2] -depressing -1.6 1.28062 [-2, -2, -2, 2, -3, -1, -2, -2, -2, -2] -depressingly -2.3 0.45826 [-2, -3, -2, -2, -2, -3, -3, -2, -2, -2] -depression -2.7 0.64031 [-3, -2, -2, -2, -2, -3, -4, -3, -3, -3] -depressions -2.2 0.6 [-2, -3, -3, -2, -2, -2, -3, -2, -2, -1] -depressive -1.6 1.11355 [-2, -1, -1, -2, -1, -2, -3, 1, -3, -2] -depressively -2.1 0.53852 [-3, -2, -3, -2, -2, -2, -2, -1, -2, -2] -depressives -1.5 0.5 [-2, -1, -1, -2, -1, -1, -1, -2, -2, -2] -depressor -1.8 1.16619 [-2, -4, -3, 0, 0, -2, -2, -2, -1, -2] -depressors -1.7 0.9 [-1, -1, -1, -2, -1, -2, -4, -2, -2, -1] -depressurization -0.3 0.78102 [1, 0, 0, -1, -1, 0, -2, 0, 0, 0] -depressurizations -0.4 0.91652 [0, 0, 0, 0, 1, -2, -1, 0, -2, 0] -depressurize -0.5 0.80623 [0, 0, -2, 0, -2, 0, 0, 0, 0, -1] -depressurized -0.3 0.64031 [0, 0, 0, 0, 0, 0, -1, 0, -2, 0] -depressurizes -0.3 0.64031 [0, 0, 0, 0, 0, 0, -1, 0, -2, 0] -depressurizing -0.7 1.34536 [2, 0, -1, -1, -2, -2, 1, -2, 0, -2] -deprival -2.1 0.7 [-1, -2, -2, -2, -1, -3, -3, -3, -2, -2] -deprivals -1.2 0.87178 [0, -1, -2, -1, 0, -2, -1, -1, -3, -1] -deprivation -1.8 1.4 [-3, -2, -3, -2, -1, -2, -2, 2, -2, -3] -deprivations -1.8 0.74833 [-1, -2, -3, -1, -2, -1, -2, -2, -3, -1] -deprive -2.1 0.7 [-3, -2, -1, -3, -1, -2, -2, -3, -2, -2] -deprived -2.1 0.7 [-2, -2, -2, -2, -2, -4, -2, -2, -1, -2] -depriver -1.6 0.91652 [-1, -2, -1, -2, -1, -4, -2, -1, -1, -1] -deprivers -1.4 0.66332 [-2, -1, -1, -3, -1, -1, -1, -1, -2, -1] -deprives -1.7 0.64031 [-2, -2, -1, -2, -1, -3, -2, -1, -1, -2] -depriving -2.0 0.0 [-2, -2, -2, -2, -2, -2, -2, -2, -2, -2] -derail -1.2 1.07703 [-1, 1, -1, -2, -1, -2, -1, -3, -2, 0] -derailed -1.4 0.66332 [-1, -2, -2, 0, -1, -1, -2, -1, -2, -2] -derails -1.3 0.78102 [-2, -3, -1, -2, -1, -1, 0, -1, -1, -1] -deride -1.1 1.22066 [-3, -2, -2, -1, -1, -1, 1, -2, -1, 1] -derided -0.8 0.87178 [-2, -1, -2, 0, 0, -1, -1, -1, 1, -1] -derides -1.0 1.0 [-1, -2, -2, 0, 0, 1, -1, -2, -1, -2] -deriding -1.5 0.80623 [-2, -2, 0, 0, -2, -1, -2, -2, -2, -2] -derision -1.2 1.249 [-1, -2, -2, -2, -1, -1, 1, 1, -3, -2] -desirable 1.3 0.45826 [2, 1, 1, 1, 1, 1, 1, 2, 2, 1] -desire 1.7 0.78102 [1, 1, 2, 1, 3, 3, 1, 2, 2, 1] -desired 1.1 1.04403 [1, 1, 0, 3, 1, 0, 1, 1, 3, 0] -desirous 1.3 0.64031 [1, 2, 1, 2, 2, 1, 2, 1, 0, 1] -despair -1.3 1.9 [2, -1, -3, -1, -3, 1, -3, 1, -3, -3] -despaired -2.7 0.45826 [-2, -2, -3, -3, -3, -3, -3, -2, -3, -3] -despairer -1.3 1.1 [-2, -2, -1, -3, -2, 1, -1, -1, 0, -2] -despairers -1.3 1.00499 [-2, -1, -1, 1, -2, -1, -2, -1, -1, -3] -despairing -2.3 0.64031 [-2, -1, -3, -2, -3, -2, -2, -2, -3, -3] -despairingly -2.2 0.74833 [-2, -2, -2, -2, -4, -2, -3, -1, -2, -2] -despairs -2.7 1.00499 [-3, -4, -1, -3, -4, -2, -1, -3, -3, -3] -desperate -1.3 1.34536 [-2, -1, -2, 1, -1, -2, -3, -3, -1, 1] -desperately -1.6 1.11355 [-3, -3, -2, -1, -2, -1, -2, -2, -1, 1] -desperateness -1.5 1.36015 [-1, -2, -2, -2, -3, -3, 1, -2, 1, -2] -desperation -2.0 1.0 [-2, -1, -1, -2, -3, -3, -1, -4, -1, -2] -desperations -2.2 1.66132 [-1, -4, -2, -4, -4, -1, -1, -2, 1, -4] -despise -1.4 1.35647 [-2, -3, -1, -2, -1, 1, -3, 1, -2, -2] -despised -1.7 1.48661 [-2, -1, -3, -2, -3, 1, -3, 1, -2, -3] -despisement -2.4 0.91652 [-3, -3, -2, -1, -3, -1, -4, -2, -2, -3] -despisements -2.5 1.0247 [-2, -2, -3, -2, 0, -3, -4, -3, -3, -3] -despiser -1.8 1.07703 [-2, -1, -3, 1, -2, -2, -3, -2, -2, -2] -despisers -1.6 1.35647 [-3, -3, -1, -3, -2, -1, -1, 1, 0, -3] -despises -2.0 1.26491 [-3, -1, -3, 1, -2, -1, -3, -2, -3, -3] -despising -2.7 0.9 [-4, -3, -3, -4, -1, -2, -3, -2, -2, -3] -despondent -2.1 0.53852 [-2, -2, -2, -3, -2, -2, -1, -3, -2, -2] -destroy -2.5 0.67082 [-2, -3, -3, -1, -3, -3, -3, -2, -2, -3] -destroyed -2.2 0.87178 [-1, -3, -3, -2, -1, -2, -1, -3, -3, -3] -destroyer -2.0 0.89443 [-2, -3, -3, -3, -1, -2, -2, -2, 0, -2] -destroyers -2.3 0.78102 [-1, -3, -3, -3, -2, -2, -3, -3, -1, -2] -destroying -2.6 0.91652 [-2, -4, -4, -2, -1, -3, -2, -3, -2, -3] -destroys -2.6 0.4899 [-3, -3, -3, -2, -2, -2, -3, -3, -2, -3] -destruct -2.4 0.4899 [-3, -3, -3, -2, -2, -2, -3, -2, -2, -2] -destructed -1.9 1.04403 [-4, -1, -2, -2, -2, -1, -3, -2, 0, -2] -destructibility -1.8 1.07703 [-1, -2, -1, -1, -2, -3, -2, 0, -4, -2] -destructible -1.5 1.11803 [-2, -2, -2, -1, 1, -1, -3, -1, -3, -1] -destructing -2.5 0.67082 [-2, -3, -2, -3, -2, -2, -2, -3, -2, -4] -destruction -2.7 0.9 [-4, -3, -4, -3, -2, -2, -3, -1, -2, -3] -destructionist -2.6 0.8 [-3, -4, -2, -2, -2, -3, -3, -1, -3, -3] -destructionists -2.1 0.53852 [-3, -1, -2, -2, -3, -2, -2, -2, -2, -2] -destructions -2.3 0.78102 [-3, -2, -2, -2, -1, -3, -4, -2, -2, -2] -destructive -3.0 0.63246 [-3, -4, -3, -2, -3, -3, -3, -2, -4, -3] -destructively -2.4 0.91652 [-2, -3, -1, -4, -2, -3, -3, -3, -1, -2] -destructiveness -2.4 0.91652 [-3, -3, -2, -4, -1, -2, -3, -2, -1, -3] -destructivity -2.2 1.53623 [2, -3, -3, -4, -3, -2, -2, -2, -2, -3] -destructs -2.4 0.91652 [-2, -1, -2, -4, -4, -2, -3, -2, -2, -2] -detached -0.5 1.20416 [-1, 2, -1, -1, -2, 0, 1, -2, -1, 0] -detain -1.8 0.9798 [-3, -1, -2, -2, -4, -2, -1, -1, -1, -1] -detained -1.7 0.9 [-1, -1, -1, -1, -1, -2, -2, -2, -2, -4] -detention -1.5 0.67082 [-1, -2, -1, -2, -1, -1, -3, -2, -1, -1] -determinable 0.9 0.7 [2, 1, 1, 1, 0, 1, 2, 0, 0, 1] -determinableness 0.2 1.07703 [0, 0, 0, 1, 0, 1, -1, 2, -2, 1] -determinably 0.9 0.83066 [2, 0, 1, 1, 0, 1, 2, 2, 0, 0] -determinacy 1.0 1.0 [0, 0, 0, 3, 1, 1, 2, 1, 0, 2] -determinant 0.2 0.6 [0, 1, -1, 0, 1, 1, 0, 0, 0, 0] -determinantal -0.3 1.41774 [0, 0, 0, -4, 0, -1, 0, 0, 2, 0] -determinate 0.8 0.87178 [2, 1, 0, 0, 0, 2, 2, 0, 1, 0] -determinately 1.2 0.6 [1, 2, 0, 1, 1, 1, 2, 1, 2, 1] -determinateness 1.1 0.9434 [1, 1, 1, 0, 0, 2, 3, 1, 0, 2] -determination 1.7 0.78102 [2, 3, 1, 1, 1, 2, 1, 1, 2, 3] -determinations 0.8 1.16619 [0, 3, 1, 0, 1, 3, 0, 0, 0, 0] -determinative 1.1 1.04403 [2, 0, 3, 2, 1, 1, 0, 0, 2, 0] -determinatives 0.9 1.3 [2, 0, -2, 1, 2, 2, 2, 0, 0, 2] -determinator 1.1 1.04403 [3, 0, 1, 0, 1, 0, 2, 2, 0, 2] -determined 1.4 1.35647 [-2, 1, 3, 2, 2, 2, 3, 1, 1, 1] -devastate -3.1 0.9434 [-4, -4, -1, -4, -4, -3, -3, -3, -2, -3] -devastated -3.0 0.89443 [-4, -3, -3, -4, -3, -1, -3, -4, -3, -2] -devastates -2.8 0.9798 [-4, -3, -2, -4, -2, -1, -3, -4, -3, -2] -devastating -3.3 0.9 [-4, -3, -4, -4, -1, -4, -3, -3, -3, -4] -devastatingly -2.4 1.28062 [-3, -4, -3, 0, -3, 0, -2, -3, -3, -3] -devastation -1.8 2.13542 [-1, -1, -3, -3, -4, -3, -4, 2, 2, -3] -devastations -1.9 1.92094 [-3, -3, -2, -2, 1, -1, 2, -4, -4, -3] -devastative -3.2 1.16619 [-4, -3, 0, -4, -4, -3, -3, -4, -3, -4] -devastator -2.8 0.74833 [-3, -3, -2, -2, -3, -2, -3, -4, -2, -4] -devastators -2.9 1.22066 [-3, -2, -3, -4, -4, -4, 0, -3, -2, -4] -devil -3.4 0.8 [-4, -3, -4, -4, -4, -4, -2, -3, -2, -4] -deviled -1.6 1.0198 [-1, -2, 0, -4, -1, -2, -2, -2, -1, -1] -devilfish -0.8 1.07703 [-2, -3, -1, 0, 0, 0, 0, -2, 0, 0] -devilfishes -0.6 1.0198 [-3, 0, -2, 0, 0, 0, 0, -1, 0, 0] -deviling -2.2 0.87178 [-1, -3, -1, -2, -3, -2, -2, -4, -2, -2] -devilish -2.1 1.04403 [-1, -2, -4, -1, -1, -2, -2, -4, -2, -2] -devilishly -1.6 0.8 [-2, -2, -3, -1, -2, -2, 0, -2, -1, -1] -devilishness -2.3 0.9 [-4, -1, -4, -2, -2, -2, -2, -2, -2, -2] -devilkin -2.4 0.91652 [-3, -1, -2, -3, -2, -4, -2, -3, -3, -1] -devilled -2.3 1.1 [-3, -1, -2, -3, 0, -4, -2, -3, -2, -3] -devilling -1.8 1.249 [-3, -1, -1, -2, -2, -3, -4, -2, 0, 0] -devilment -1.9 0.9434 [-2, -1, -2, -1, -3, -2, -2, -1, -1, -4] -devilments -1.1 0.7 [-2, -1, -2, -2, -1, 0, 0, -1, -1, -1] -devilries -1.6 1.35647 [-1, -1, -2, -4, -3, 0, -2, 0, 0, -3] -devilry -2.8 1.249 [-4, -3, 0, -2, -2, -2, -3, -4, -4, -4] -devils -2.7 0.9 [-3, -1, -3, -2, -2, -3, -4, -3, -2, -4] -deviltries -1.5 1.11803 [-1, -2, 1, -2, 0, -2, -2, -3, -2, -2] -deviltry -2.8 1.32665 [-4, -4, -3, -3, -3, -3, 1, -3, -3, -3] -devilwood -0.8 1.07703 [0, -1, -2, 0, 0, 0, 0, -3, -2, 0] -devilwoods -1.0 0.7746 [-2, 0, -2, -1, -1, 0, -1, -2, 0, -1] -devote 1.4 1.28062 [3, 0, 2, -1, 0, 3, 2, 2, 1, 2] -devoted 1.7 1.34536 [2, -1, 3, 2, 1, 0, 1, 3, 3, 3] -devotedly 1.6 1.35647 [1, 1, 2, 2, 3, 2, 2, -2, 2, 3] -devotedness 2.0 1.0 [0, 3, 2, 1, 3, 2, 2, 3, 1, 3] -devotee 1.6 1.11355 [1, 3, 0, 2, 1, 2, 1, 1, 4, 1] -devotees 0.5 1.0247 [0, 0, 3, 0, 0, 0, 2, 0, 0, 0] -devotement 1.5 1.36015 [2, -1, 3, 2, -1, 1, 2, 3, 2, 2] -devotements 1.1 1.04403 [0, 1, 0, 0, 0, 2, 2, 2, 3, 1] -devotes 1.6 0.91652 [2, 3, 0, 2, 2, 3, 1, 1, 1, 1] -devoting 2.1 0.7 [2, 2, 3, 1, 2, 3, 2, 3, 1, 2] -devotion 2.0 1.0 [2, 0, 1, 2, 4, 3, 2, 2, 2, 2] -devotional 1.2 1.16619 [0, 1, 0, 2, 2, 1, 0, 0, 3, 3] -devotionally 2.2 0.4 [2, 2, 2, 3, 2, 3, 2, 2, 2, 2] -devotionals 1.2 1.07703 [3, 1, 1, 0, -1, 2, 2, 2, 1, 1] -devotions 1.8 0.74833 [2, 3, 1, 2, 1, 3, 1, 2, 1, 2] -diamond 1.4 1.42829 [0, 0, 2, 0, 1, 3, 1, 3, 0, 4] -dick -2.3 1.18743 [-2, -3, -4, -2, 0, -4, -2, -1, -3, -2] -dickhead -3.1 0.53852 [-4, -3, -3, -3, -4, -2, -3, -3, -3, -3] -die -2.9 0.9434 [-4, -3, -1, -2, -4, -3, -3, -3, -2, -4] -died -2.6 1.28062 [-3, -1, -3, -4, -2, -4, -3, -4, -2, 0] -difficult -1.5 0.5 [-2, -2, -1, -1, -2, -1, -1, -2, -1, -2] -difficulties -1.2 0.4 [-1, -2, -1, -1, -1, -2, -1, -1, -1, -1] -difficultly -1.7 0.45826 [-1, -2, -1, -2, -2, -1, -2, -2, -2, -2] -difficulty -1.4 0.66332 [-2, -2, -2, -2, 0, -1, -1, -2, -1, -1] -diffident -1.0 0.44721 [-1, -1, -1, -1, -1, 0, -2, -1, -1, -1] -dignified 2.2 0.6 [1, 2, 2, 2, 3, 3, 3, 2, 2, 2] -dignifies 2.0 0.7746 [1, 3, 2, 2, 3, 3, 2, 2, 1, 1] -dignify 1.8 0.74833 [1, 2, 2, 1, 3, 3, 1, 2, 2, 1] -dignifying 2.1 1.04403 [1, 1, 1, 3, 1, 4, 2, 3, 2, 3] -dignitaries 0.6 0.91652 [0, 0, 1, 0, 0, 0, 3, 0, 1, 1] -dignitary 1.9 1.3 [0, 3, 4, 2, 3, 1, 1, 3, 0, 2] -dignities 1.4 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-2, -1, -1] -discouragers -1.9 0.53852 [-2, -2, -2, -2, -1, -1, -3, -2, -2, -2] -discourages -1.9 0.53852 [-2, -1, -2, -2, -2, -2, -1, -3, -2, -2] -discouraging -1.9 0.7 [-2, -2, -2, -3, -1, -1, -2, -1, -2, -3] -discouragingly -1.8 0.87178 [-2, -1, -3, -1, -1, -3, -2, -1, -3, -1] -discredited -1.9 0.53852 [-2, -2, -2, -2, -1, -3, -1, -2, -2, -2] -disdain -2.1 0.3 [-3, -2, -2, -2, -2, -2, -2, -2, -2, -2] -disgrace -2.2 0.74833 [-2, -4, -1, -2, -2, -2, -2, -3, -2, -2] -disgraced -2.0 0.44721 [-3, -2, -2, -2, -1, -2, -2, -2, -2, -2] -disguise -1.0 1.09545 [-2, -1, 0, 0, 0, 0, -3, -2, -2, 0] -disguised -1.1 1.04403 [-3, 0, 0, -1, -1, 0, -3, -1, -1, -1] -disguises -1.0 0.63246 [-2, 0, 0, -1, -1, -1, -2, -1, -1, -1] -disguising -1.3 0.78102 [0, -2, -1, -1, -1, -2, -1, -1, -3, -1] -disgust -2.9 0.7 [-3, -3, -4, -2, -3, -3, -4, -2, -3, -2] -disgusted -2.4 0.91652 [-4, -3, -3, -1, -3, -1, -2, -2, -2, -3] -disgustedly -3.0 0.89443 [-2, -3, -4, -4, -2, -4, -4, -2, -3, -2] -disgustful -2.6 0.4899 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0.8 [-1, -2, -2, -3, -3, -4, -3, -2, -2, -2] -distressed -1.8 0.6 [-2, -2, -2, -3, -2, -2, -1, -1, -2, -1] -distresses -1.6 0.66332 [-2, -1, -1, -2, -2, -2, -1, -1, -3, -1] -distressful -2.2 0.6 [-1, -3, -3, -2, -2, -3, -2, -2, -2, -2] -distressfully -1.7 1.1 [-1, -3, -2, 1, -3, -1, -2, -2, -2, -2] -distressfulness -2.4 0.66332 [-2, -3, -2, -3, -3, -3, -2, -1, -3, -2] -distressing -1.7 1.18743 [-3, -3, -1, -1, -2, -2, -3, -2, 1, -1] -distressingly -2.2 0.74833 [-3, -1, -2, -3, -3, -3, -2, -2, -2, -1] -distrust -1.8 0.87178 [-1, -2, -2, -2, -1, -1, -2, -4, -1, -2] -distrusted -2.4 0.66332 [-1, -3, -3, -3, -2, -2, -3, -2, -2, -3] -distrustful -2.1 0.83066 [-1, -3, -2, -2, -3, -1, -1, -3, -2, -3] -distrustfully -1.8 0.6 [-2, -1, -1, -2, -1, -2, -3, -2, -2, -2] -distrustfulness -1.6 0.66332 [-2, -1, -2, -1, -2, -1, -1, -3, -1, -2] -distrusting -2.1 0.83066 [-1, -2, -2, -2, -3, -3, -1, -3, -1, -3] -distrusts -1.3 0.45826 [-1, -1, -2, -1, -2, -1, -2, -1, -1, -1] -disturb -1.7 0.45826 [-2, -1, -1, -2, -2, -2, -1, -2, -2, -2] -disturbance -1.6 0.8 [-1, -2, -1, -2, -2, -3, -1, -2, 0, -2] -disturbances -1.4 0.66332 [-1, -1, -1, -2, -1, -1, -1, -1, -3, -2] -disturbed -1.6 0.4899 [-2, -2, -1, -1, -2, -2, -1, -2, -1, -2] -disturber -1.4 0.4899 [-2, -1, -1, -2, -2, -1, -1, -2, -1, -1] -disturbers -2.1 0.53852 [-2, -2, -2, -2, -2, -3, -3, -2, -1, -2] -disturbing -2.3 0.45826 [-2, -2, -3, -3, -2, -2, -3, -2, -2, -2] -disturbingly -2.3 0.78102 [-2, -2, -1, -3, -4, -3, -2, -2, -2, -2] -disturbs -1.9 0.53852 [-2, -2, -1, -2, -3, -2, -1, -2, -2, -2] -dithering -0.5 0.92195 [0, 0, 0, 0, 1, -1, -2, -2, -1, 0] -divination 1.7 1.1 [2, 3, 0, 1, 2, 1, 3, 3, 2, 0] -divinations 1.1 1.04403 [1, 0, 1, 2, 2, 0, 3, 2, 0, 0] -divinatory 1.6 1.42829 [4, 1, 0, 0, 1, 3, 3, 0, 1, 3] -divine 2.6 0.8 [3, 3, 3, 2, 1, 2, 3, 4, 2, 3] -divined 0.8 1.16619 [1, 0, 3, 0, 0, 1, 0, 3, 0, 0] -divinely 2.9 0.7 [3, 2, 3, 3, 2, 4, 3, 2, 4, 3] -diviner 0.3 0.9 [0, 0, 3, 0, 0, 0, 0, 0, 0, 0] -diviners 1.2 1.16619 [0, 1, 0, 2, 2, 0, 3, 1, 3, 0] -divines 0.8 1.249 [0, 0, 3, 0, 0, 0, 3, 2, 0, 0] -divinest 2.7 0.78102 [3, 4, 2, 4, 2, 2, 2, 3, 2, 3] -diving 0.3 0.45826 [1, 0, 0, 0, 0, 1, 0, 1, 0, 0] -divining 0.9 1.37477 [0, -1, 2, 0, 1, 0, 2, 4, 1, 0] -divinise 0.5 1.36015 [0, 2, 0, 0, 0, 0, 0, -2, 2, 3] -divinities 1.8 1.46969 [1, 3, 3, 4, 0, 0, 1, 0, 3, 3] -divinity 2.7 1.00499 [4, 4, 2, 3, 3, 1, 2, 4, 2, 2] -divinize 2.3 1.00499 [4, 2, 2, 3, 4, 1, 1, 2, 2, 2] -dizzy -0.9 0.3 [-1, -1, -1, -1, -1, -1, -1, -1, 0, -1] -dodging -0.4 0.8 [-1, -1, 0, 1, 0, -1, 0, 0, -2, 0] -dodgy -0.9 0.9434 [-1, -1, -1, -3, -1, 1, -1, -1, -1, 0] -dolorous -2.2 0.6 [-2, -2, -2, -3, -3, -3, -2, -2, -1, -2] -dominance 0.8 0.87178 [2, 0, 0, 2, 1, 0, 0, 1, 2, 0] -dominances -0.1 0.9434 [-1, 0, 1, 1, 0, -1, 0, 1, 0, -2] -dominantly 0.2 1.16619 [-2, 0, 0, -1, 2, 1, 2, 0, 0, 0] -dominants 0.2 1.16619 [0, 2, -1, 0, -1, -1, -1, 1, 1, 2] -dominate -0.5 0.92195 [0, -1, 1, -1, 1, -1, -2, 0, -1, -1] -dominates 0.2 1.249 [1, 0, -2, -1, 1, -1, 2, 0, 0, 2] -dominating -1.2 1.98997 [-4, -1, -4, -1, -3, -1, -1, 2, 2, -1] -domination -0.2 0.9798 [0, 1, 0, -1, -1, -1, 0, 2, -1, -1] -dominations -0.3 0.45826 [0, 0, 0, 0, 0, -1, 0, -1, -1, 0] -dominative -0.7 1.18743 [-1, -1, -2, -2, -1, -1, -1, 2, 1, -1] -dominators -0.4 1.8 [-1, -2, -2, -2, 0, 2, 2, -3, 2, 0] -dominatrices -0.2 1.6 [-3, 0, 2, 0, -2, -2, 0, 1, 2, 0] -dominatrix -0.5 0.92195 [0, 0, -1, 0, 0, 1, 0, -1, -2, -2] -dominatrixes 0.6 1.35647 [0, 4, 0, -1, 0, 2, 1, 0, 0, 0] -doom -1.7 1.26886 [-2, -1, -1, -4, -2, -2, 1, -3, -1, -2] -doomed -3.2 0.74833 [-3, -3, -4, -4, -4, -2, -4, -3, -3, -2] -doomful -2.1 0.7 [-3, -2, -3, -1, -2, -3, -2, -1, -2, -2] -dooming -2.8 0.4 [-2, -3, -2, -3, -3, -3, -3, -3, -3, -3] -dooms -1.1 1.57797 [1, -3, -1, -3, -2, -1, -3, 1, 1, -1] -doomsayer -0.7 1.41774 [2, -1, -2, -1, 1, -2, -2, -1, 1, -2] -doomsayers -1.7 0.78102 [-1, -2, -3, 0, -2, -2, -2, -1, -2, -2] -doomsaying -1.5 1.28452 [-3, -2, -2, 0, 1, 0, -3, -2, -2, -2] -doomsayings -1.5 0.92195 [-2, -1, -1, -2, -2, 0, 0, -2, -3, -2] -doomsday -2.8 1.249 [-3, -1, -3, -4, -3, -4, 0, -4, -3, -3] -doomsdayer -2.2 1.249 [-3, -1, -4, -3, -4, -3, -1, -1, -1, -1] -doomsdays -2.4 1.85472 [-3, -2, -4, 1, -4, -3, -2, -4, 1, -4] -doomster -2.2 0.87178 [-2, -1, -2, -3, -1, -3, -1, -3, -3, -3] -doomsters -1.6 0.8 [-3, -1, -2, -2, 0, -2, -2, -1, -1, -2] -doomy -1.1 1.37477 [2, -2, -1, -2, -2, -2, -2, 1, -1, -2] -dork -1.4 0.66332 [-1, -2, -2, -1, -1, -1, -3, -1, -1, -1] -dorkier -1.1 0.53852 [-1, -1, -1, -1, -2, 0, -1, -2, -1, -1] -dorkiest -1.2 0.74833 [-1, -2, -1, -3, -1, 0, -1, -1, -1, -1] -dorks -0.5 0.67082 [-1, 1, -1, -1, -1, -1, 0, 0, -1, 0] -dorky -1.1 1.04403 [-1, 0, -1, 1, -1, -1, -3, -2, -2, -1] -doubt -1.5 0.5 [-1, -1, -2, -2, -1, -1, -2, -1, -2, -2] -doubtable -1.5 0.5 [-1, -1, -2, -1, -2, -1, -2, -2, -1, -2] -doubted -1.1 1.22066 [-1, -2, -2, 2, -1, -1, -2, -2, -2, 0] -doubter -1.6 0.91652 [-1, -3, -2, -1, -1, -1, -2, -2, -3, 0] -doubters -1.3 0.45826 [-1, -1, -1, -1, -1, -2, -1, -2, -2, -1] -doubtful -1.4 0.4899 [-1, -1, -2, -1, -2, -2, -1, -1, -2, -1] -doubtfully -1.2 0.4 [-1, -1, -1, -1, -1, -1, -2, -1, -1, -2] -doubtfulness -1.2 0.4 [-2, -1, -1, -1, -1, -1, -1, -1, -1, -2] -doubting -1.4 0.4899 [-1, -1, -1, -2, -2, -1, -1, -1, -2, -2] -doubtingly -1.4 0.4899 [-2, -2, -1, -1, -1, -1, -1, -2, -2, -1] -doubtless 0.9 1.51327 [2, 2, 1, 2, -2, 2, -2, 1, 1, 2] -doubtlessly 1.2 0.9798 [2, 1, 1, 2, 0, -1, 2, 1, 2, 2] -doubtlessness 0.8 0.9798 [2, 1, 2, 0, 0, 0, 2, -1, 1, 1] -doubts -1.2 0.6 [-2, -1, -1, -1, -2, -2, -1, 0, -1, -1] -douche -1.5 1.68819 [-3, -2, -3, 1, 1, -2, -3, -2, 1, -3] -douchebag -3.0 0.44721 [-3, -3, -3, -3, -3, -3, -2, -3, -4, -3] -downcast -1.8 0.74833 [-1, -1, -1, -2, -2, -2, -1, -3, -3, -2] -downhearted -2.3 0.78102 [-1, -2, -2, -4, -2, -2, -2, -3, -3, -2] -downside -1.0 0.7746 [-1, -1, -1, -1, -1, -1, -2, 1, -2, -1] -drag -0.9 0.83066 [-1, -2, -1, -1, -2, -1, -1, 1, 0, -1] -dragged -0.2 1.07703 [-2, -1, 0, 0, -1, 0, 0, 1, 2, -1] -drags -0.7 0.64031 [0, -1, 0, -1, -1, -2, -1, 0, 0, -1] -drained -1.5 0.5 [-1, -1, -2, -2, -1, -2, -1, -2, -1, -2] -dread -2.0 0.63246 [-2, -3, -2, -2, -2, -2, -3, -1, -1, -2] -dreaded -2.7 0.64031 [-2, -3, -3, -3, -4, -3, -2, -2, -2, -3] -dreadful -1.9 1.86815 [-4, -2, -2, 2, -1, -4, -1, 0, -3, -4] -dreadfully -2.7 1.26886 [-4, -4, -3, -4, -3, -1, -2, -1, -1, -4] -dreadfulness -3.2 0.87178 [-3, -4, -2, -3, -4, -4, -2, -2, -4, -4] -dreadfuls -2.4 1.2 [-4, -3, -3, -2, -3, -2, -4, 0, -1, -2] -dreading -2.4 0.8 [-3, -2, -2, -2, -2, -2, -3, -4, -3, -1] -dreadlock -0.4 0.66332 [0, 0, 0, 0, 0, -1, -2, 0, -1, 0] -dreadlocks -0.2 0.9798 [0, 0, 0, 0, 0, -1, -2, 2, 0, -1] -dreadnought -0.6 1.35647 [-2, 0, 0, 0, -3, 0, -1, -2, 0, 2] -dreadnoughts -0.4 0.66332 [0, -1, -1, 0, 0, 0, 0, 0, -2, 0] -dreads -1.4 1.42829 [0, -1, 0, 0, -3, -3, 0, -4, -2, -1] -dream 1.0 1.18322 [0, 1, 2, 0, 0, 3, 0, 3, 1, 0] -dreams 1.7 1.1 [2, 2, 3, 0, 1, 1, 1, 4, 1, 2] -dreary -1.4 0.4899 [-1, -1, -2, -1, -1, -2, -2, -1, -2, -1] -droopy -0.8 0.74833 [-1, -1, 0, -1, -2, 0, 0, -1, 0, -2] -drop -1.1 0.53852 [0, -1, -1, -1, -2, -1, -2, -1, -1, -1] -drown -2.7 1.00499 [-4, -2, -2, -4, -4, -2, -3, -1, -3, -2] -drowned -2.9 0.7 [-2, -3, -3, -3, -2, -4, -4, -2, -3, -3] -drowns -2.2 1.6 [-3, -3, -3, -4, -2, -3, -1, -2, 2, -3] -drunk -1.4 0.91652 [-3, -1, 0, -2, 0, -1, -1, -2, -2, -2] -dubious -1.5 0.5 [-1, -2, -2, -1, -1, -2, -1, -1, -2, -2] -dud -1.0 0.89443 [-1, -1, -1, 0, -3, 0, -1, 0, -1, -2] -dull -1.7 0.45826 [-2, -2, -2, -1, -2, -2, -2, -1, -1, -2] -dullard -1.6 0.66332 [-2, -1, -1, -2, -2, -1, -1, -2, -1, -3] -dullards -1.8 0.87178 [-1, -3, -1, -1, -3, -1, -1, -2, -3, -2] -dulled -1.5 0.5 [-2, -1, -2, -1, -1, -1, -2, -2, -1, -2] -duller -1.7 0.64031 [-3, -1, -2, -2, -2, -1, -2, -1, -1, -2] -dullest -1.7 1.00499 [-1, -4, -1, -1, -2, -3, -2, -1, -1, -1] -dulling -1.1 0.7 [-1, -2, 0, -1, -2, -2, 0, -1, -1, -1] -dullish -1.1 0.53852 [-2, -1, -1, -1, -1, -1, -1, -1, 0, -2] -dullness -1.4 0.8 [-1, -1, -1, -1, -1, -1, -3, -1, -3, -1] -dullnesses -1.9 1.04403 [-3, -2, -1, -1, -3, -1, -4, -1, -2, -1] -dulls -1.0 0.44721 [-1, -1, -1, -1, -1, -1, 0, -1, -1, -2] -dullsville -2.4 0.8 [-2, -2, -4, -3, -2, -2, -3, -2, -3, -1] -dully -1.1 0.3 [-1, -1, -1, -1, -1, -1, -1, -1, -1, -2] -dumb -2.3 0.9 [-4, -2, -2, -2, -2, -2, -4, -2, -2, -1] -dumbass -2.6 1.0198 [-3, -3, -4, -4, -1, -2, -3, -3, -1, -2] -dumbbell -0.8 0.9798 [0, -1, -3, -2, 0, -1, 0, 0, -1, 0] -dumbbells -0.2 0.4 [0, -1, 0, 0, 0, 0, 0, -1, 0, 0] -dumbcane -0.3 0.45826 [0, 0, 0, 0, 0, -1, -1, 0, -1, 0] -dumbcanes -0.6 1.2 [0, 0, -1, -1, -1, 2, 0, -1, -3, -1] -dumbed -1.4 0.4899 [-2, -1, -2, -2, -2, -1, -1, -1, -1, -1] -dumber -1.5 0.5 [-2, -1, -2, -1, -2, -1, -1, -2, -2, -1] -dumbest -2.3 1.00499 [-3, -1, -3, -4, -2, -1, -2, -3, -1, -3] -dumbfound -0.1 1.92094 [3, -2, -1, -1, 1, 1, -3, 3, -1, -1] -dumbfounded -1.6 1.11355 [-2, 0, -2, 0, -2, -1, -4, -1, -2, -2] -dumbfounder -1.0 0.89443 [-2, 0, 0, 0, -2, -1, -2, 0, -2, -1] -dumbfounders -1.0 0.89443 [-1, -3, -1, 0, -2, 0, -1, 0, -1, -1] -dumbfounding -0.8 0.74833 [-1, -2, 0, -1, -1, 0, 0, -1, 0, -2] -dumbfounds -0.3 1.26886 [0, -1, -1, 0, 0, -1, -1, -2, 0, 3] -dumbhead -2.6 0.66332 [-3, -4, -3, -2, -2, -3, -3, -2, -2, -2] -dumbheads -1.9 0.83066 [-2, -2, -2, -1, -2, -1, -2, -4, -1, -2] -dumbing -0.5 1.0247 [-1, 2, -1, 0, -1, -2, -1, 0, 0, -1] -dumbly -1.3 1.00499 [-2, -1, -2, -3, 1, -2, -1, -1, -1, -1] -dumbness -1.9 0.53852 [-2, -2, -2, -2, -2, -3, -2, -2, -1, -1] -dumbs -1.5 0.67082 [-1, -1, -1, -3, -2, -1, -2, -1, -2, -1] -dumbstruck -1.0 1.34164 [-1, -2, 0, 0, -2, 1, -3, 1, -2, -2] -dumbwaiter 0.2 1.07703 [0, 0, 0, 0, 2, 0, 2, 0, -2, 0] -dumbwaiters -0.1 0.3 [0, 0, 0, 0, 0, 0, -1, 0, 0, 0] -dump -1.6 0.91652 [-3, -2, -1, -2, -1, -3, -2, -1, -1, 0] -dumpcart -0.6 0.8 [0, -2, -1, 0, 0, 0, -1, 0, -2, 0] -dumped -1.7 0.78102 [-2, -3, -2, -1, -1, -1, -3, -2, -1, -1] -dumper -1.2 0.87178 [-2, -3, -1, -1, -1, -2, 0, -1, 0, -1] -dumpers -0.8 0.6 [0, 0, -2, -1, -1, 0, -1, -1, -1, -1] -dumpier -1.4 0.66332 [-2, -1, -2, -1, -1, -2, 0, -2, -1, -2] -dumpiest -1.6 1.35647 [-1, -2, -2, -3, -2, -4, 1, 0, -1, -2] -dumpiness -1.2 0.6 [-2, -1, 0, -1, -1, -2, -1, -2, -1, -1] -dumping -1.3 1.1 [-3, -2, -2, 0, -2, -1, -1, 1, -1, -2] -dumpings -1.1 0.83066 [-2, 0, -1, -1, 0, -1, -2, -2, 0, -2] -dumpish -1.8 0.6 [-2, -1, -2, -3, -2, -2, -1, -2, -2, -1] -dumpling 0.4 0.91652 [0, 0, 1, 0, -1, 2, 2, 0, 0, 0] -dumplings -0.3 1.26886 [0, 0, 0, 0, 2, 0, 0, 0, -2, -3] -dumps -1.7 0.9 [-3, -2, -3, -1, -1, -3, -1, -1, -1, -1] -dumpster -0.6 0.91652 [0, -2, 0, -2, 0, 0, 0, -2, 0, 0] -dumpsters -1.0 0.89443 [0, -1, 0, -2, -2, -2, 0, 0, -1, -2] -dumpy -1.7 0.78102 [-3, -2, -3, -1, -1, -2, -2, -1, -1, -1] -dupe -1.5 0.5 [-2, -2, -1, -1, -2, -1, -2, -1, -2, -1] -duped -1.8 0.4 [-2, -2, -1, -2, -2, -2, -2, -1, -2, -2] -dwell 0.5 0.92195 [2, 1, -1, 0, -1, 1, 1, 1, 1, 0] -dwelled 0.4 0.66332 [2, 0, 0, 0, 0, 1, 1, 0, 0, 0] -dweller 0.3 0.64031 [2, 0, 0, 0, 0, 0, 1, 0, 0, 0] -dwellers -0.3 0.9 [-3, 0, 0, 0, 0, 0, 0, 0, 0, 0] -dwelling 0.1 0.53852 [0, 1, 0, 1, 0, 0, 0, -1, 0, 0] -dwells -0.1 0.53852 [0, 0, 0, 0, -1, 1, -1, 0, 0, 0] -dynamic 1.6 0.8 [1, 1, 1, 3, 1, 1, 2, 3, 2, 1] -dynamical 1.2 0.87178 [1, 2, 0, 1, 0, 2, 2, 2, 2, 0] -dynamically 1.5 1.0247 [2, 0, 3, 2, 0, 0, 2, 2, 2, 2] -dynamics 1.1 1.13578 [2, 3, 0, 0, 0, 2, 2, 0, 2, 0] -dynamism 1.6 1.11355 [0, 2, 0, 2, 0, 2, 3, 3, 2, 2] -dynamisms 1.2 0.9798 [2, 0, 2, 0, 0, 2, 2, 2, 0, 2] -dynamist 1.4 1.0198 [0, 2, 0, 2, 0, 1, 3, 2, 2, 2] -dynamistic 1.5 1.0247 [3, 1, 1, 2, 1, 3, 2, 0, 2, 0] -dynamists 0.9 0.83066 [1, 0, 0, 0, 0, 2, 2, 1, 2, 1] -dynamite 0.7 2.2383 [-3, 2, 3, 1, 2, 0, 2, 2, 2, -4] -dynamited -0.9 1.04403 [0, 0, 0, -1, -1, 0, -2, 0, -2, -3] -dynamiter -1.2 0.87178 [-1, 0, -1, -1, -2, 0, -1, -1, -2, -3] -dynamiters 0.4 1.42829 [0, 0, 0, -3, 1, 0, 2, 2, 2, 0] -dynamites -0.3 1.73494 [0, 0, 4, -1, -1, 0, 0, 0, -2, -3] -dynamitic 0.9 1.3 [2, 0, 1, -2, 2, 1, 1, 3, 0, 1] -dynamiting 0.2 1.32665 [-2, 0, 0, 2, -1, -1, 0, 2, 2, 0] -dynamometer 0.3 0.64031 [0, 0, 0, 0, 1, 0, 0, 2, 0, 0] -dynamometers 0.3 0.45826 [0, 0, 0, 0, 0, 1, 0, 1, 1, 0] -dynamometric 0.3 0.9 [0, 0, 0, 0, 0, 2, 0, 0, 2, -1] -dynamometry 0.6 1.28062 [-2, 0, 0, 0, 0, 2, 2, 2, 0, 2] -dynamos 0.3 0.64031 [1, 0, 0, 0, 0, 0, 0, 0, 2, 0] -dynamotor 0.6 0.91652 [0, 2, 0, 0, 0, 0, 2, 0, 2, 0] -dysfunction -1.8 0.6 [-2, -3, -2, -1, -2, -1, -2, -1, -2, -2] -eager 1.5 0.67082 [1, 3, 1, 2, 2, 2, 1, 1, 1, 1] -eagerly 1.6 0.66332 [0, 1, 2, 2, 2, 2, 2, 1, 2, 2] -eagerness 1.7 0.45826 [2, 2, 2, 2, 1, 1, 2, 2, 2, 1] -eagers 1.6 0.66332 [2, 2, 3, 1, 2, 1, 1, 1, 2, 1] -earnest 2.3 0.64031 [3, 2, 3, 1, 2, 2, 2, 3, 3, 2] -ease 1.5 0.92195 [1, 1, 1, 0, 2, 1, 2, 3, 3, 1] -eased 1.2 0.74833 [2, 0, 1, 0, 2, 2, 1, 1, 1, 2] -easeful 1.5 1.0247 [2, 1, 1, 2, 1, 0, 3, 2, 0, 3] -easefully 1.4 0.4899 [2, 2, 1, 1, 1, 1, 2, 2, 1, 1] -easel 0.3 0.45826 [0, 0, 0, 0, 1, 1, 0, 0, 0, 1] -easement 1.6 0.91652 [0, 1, 2, 3, 2, 1, 2, 1, 3, 1] -easements 0.4 1.11355 [0, 0, 0, 1, 2, -2, 1, 0, 2, 0] -eases 1.3 0.78102 [2, 0, 1, 0, 2, 2, 2, 1, 1, 2] -easier 1.8 0.9798 [1, 1, 2, 2, 4, 3, 2, 1, 1, 1] -easiest 1.8 1.07703 [2, 4, 1, 3, 2, 0, 2, 2, 1, 1] -easily 1.4 0.4899 [2, 1, 1, 2, 1, 2, 1, 2, 1, 1] -easiness 1.6 0.66332 [2, 1, 1, 2, 3, 2, 1, 1, 2, 1] -easing 1.0 0.63246 [0, 0, 2, 1, 1, 2, 1, 1, 1, 1] -easy 1.9 1.04403 [1, 4, 2, 1, 1, 3, 1, 3, 2, 1] -easygoing 1.3 0.45826 [1, 1, 1, 1, 1, 1, 2, 2, 2, 1] -easygoingness 1.5 0.67082 [1, 2, 1, 2, 1, 3, 1, 2, 1, 1] -ecstacy 3.3 1.18743 [4, 4, 3, 4, 4, 0, 3, 3, 4, 4] -ecstasies 2.3 1.34536 [3, 3, 2, 4, 3, 1, 3, -1, 2, 3] -ecstasy 2.9 1.75784 [4, 3, 3, 4, 4, 2, -2, 3, 4, 4] -ecstatic 2.3 1.34536 [3, 4, 3, 4, 1, 1, 1, 4, 1, 1] -ecstatically 2.8 1.93907 [3, 4, -1, 4, 4, 4, -1, 3, 4, 4] -ecstatics 2.9 0.83066 [1, 3, 4, 4, 3, 3, 3, 2, 3, 3] -eerie -1.5 0.67082 [-1, -1, -2, -2, -1, -1, -2, -1, -3, -1] -eery -0.9 1.04403 [-3, -1, -2, -1, -2, 0, 0, 0, 0, 0] -effective 2.1 0.83066 [2, 2, 2, 1, 3, 4, 2, 1, 2, 2] -effectively 1.9 0.7 [1, 2, 1, 2, 2, 1, 3, 3, 2, 2] -efficiencies 1.6 0.4899 [2, 1, 1, 2, 2, 2, 1, 2, 2, 1] -efficiency 1.5 0.5 [2, 1, 2, 2, 1, 2, 1, 1, 2, 1] -efficient 1.8 0.9798 [1, 2, 1, 1, 2, 3, 3, 0, 2, 3] -efficiently 1.7 0.78102 [1, 3, 2, 1, 3, 1, 1, 2, 2, 1] -effin -2.3 1.18743 [0, -3, -3, -3, -2, -1, -4, -1, -3, -3] -egotism -1.4 0.91652 [-2, -3, -1, -2, -2, 0, 0, -1, -2, -1] -egotisms -1.0 0.7746 [-1, -1, -1, -1, -1, 0, 0, -1, -3, -1] -egotist -2.3 0.9 [-2, -1, -2, -3, -4, -2, -3, -3, -1, -2] -egotistic -1.4 1.0198 [-2, -1, -1, -1, -2, 1, -3, -2, -1, -2] -egotistical -0.9 1.57797 [-1, -2, -2, -1, -2, 1, -3, 2, 1, -2] -egotistically -1.8 0.87178 [-2, -1, -1, -2, -1, -3, -3, -1, -1, -3] -egotists -1.7 0.78102 [-1, -2, 0, -2, -2, -2, -3, -1, -2, -2] -elated 3.2 0.74833 [2, 4, 4, 3, 4, 3, 3, 2, 3, 4] -elation 1.5 1.43178 [1, 2, -2, 2, 2, 3, 0, 3, 2, 2] -elegance 2.1 0.53852 [3, 2, 2, 1, 2, 2, 3, 2, 2, 2] -elegances 1.8 0.6 [2, 2, 1, 1, 2, 2, 2, 3, 2, 1] -elegancies 1.6 1.0198 [2, 1, 2, 1, 1, 0, 4, 1, 2, 2] -elegancy 2.1 0.53852 [3, 2, 2, 1, 2, 2, 3, 2, 2, 2] -elegant 2.1 0.83066 [2, 2, 2, 1, 4, 1, 2, 3, 2, 2] -elegantly 1.9 0.83066 [2, 1, 1, 3, 2, 2, 1, 3, 3, 1] -embarrass -1.2 1.66132 [-2, -2, -3, -1, -2, -2, 2, 2, -2, -2] -embarrassable -1.6 0.8 [-3, -2, -1, -3, -1, -1, -1, -2, -1, -1] -embarrassed -1.5 0.67082 [-2, -2, -1, -2, -1, -3, -1, -1, -1, -1] -embarrassedly -1.1 1.44568 [-2, -1, -2, -3, 1, -1, -1, -2, -2, 2] -embarrasses -1.7 0.78102 [-2, -3, -1, -2, -1, -3, -2, -1, -1, -1] -embarrassing -1.6 0.8 [-3, -1, -1, -1, -1, -2, -1, -2, -3, -1] -embarrassingly -1.7 0.64031 [-2, -1, -1, -2, -1, -2, -1, -3, -2, -2] -embarrassment -1.9 0.53852 [-2, -2, -1, -2, -2, -2, -2, -1, -3, -2] -embarrassments -1.7 0.64031 [-2, -1, -2, -1, -1, -2, -2, -1, -2, -3] -embittered -0.4 1.35647 [1, -2, -1, 1, -2, 2, 0, -1, 0, -2] -embrace 1.3 1.34536 [3, 2, 1, 3, 2, -1, 2, 1, -1, 1] -emergency -1.6 2.05913 [-3, -3, -3, -3, -4, 2, 1, -1, 1, -3] -emotional 0.6 1.0198 [1, -1, 0, 0, 0, 2, 0, 2, 2, 0] -empathetic 1.7 1.1 [-1, 3, 2, 2, 2, 1, 3, 1, 2, 2] -emptied -0.7 0.64031 [-1, 0, 0, 0, -1, -1, -1, -2, 0, -1] -emptier -0.7 0.64031 [-1, 0, 0, 0, -1, -1, -1, -2, 0, -1] -emptiers -0.7 0.78102 [0, 0, -1, 0, -1, -1, -2, 0, -2, 0] -empties -0.7 0.64031 [-1, 0, 0, 0, -1, -1, -1, -2, 0, -1] -emptiest -1.8 1.07703 [-1, -2, -2, -1, -1, -2, -3, 0, -4, -2] -emptily -1.0 1.41421 [-2, 2, -1, -1, -1, 0, -4, -1, -1, -1] -emptiness -1.9 0.7 [-2, -2, -3, -2, -2, -1, -1, -3, -1, -2] -emptinesses -1.5 1.11803 [-1, -1, -3, -1, -1, -1, -2, 0, -4, -1] -emptins -0.3 0.45826 [0, 0, 0, -1, 0, 0, 0, -1, -1, 0] -empty -0.8 0.74833 [-1, -1, -1, -1, -1, -1, -2, 0, -1, 1] -emptying -0.6 1.0198 [2, -1, -1, 0, -1, 0, -1, -1, -2, -1] -enchanted 1.6 0.8 [1, 3, 1, 2, 1, 3, 1, 2, 1, 1] -encourage 2.3 0.78102 [2, 1, 3, 2, 3, 4, 2, 2, 2, 2] -encouraged 1.5 0.5 [1, 2, 2, 2, 2, 2, 1, 1, 1, 1] -encouragement 1.8 0.9798 [2, 1, 2, 1, 1, 3, 1, 2, 4, 1] -encouragements 2.1 0.7 [3, 2, 3, 2, 1, 2, 3, 2, 2, 1] -encourager 1.5 0.5 [2, 1, 2, 1, 1, 2, 1, 1, 2, 2] -encouragers 1.5 0.5 [2, 2, 1, 1, 2, 2, 1, 1, 2, 1] -encourages 1.9 0.53852 [2, 2, 1, 2, 2, 1, 2, 2, 2, 3] -encouraging 2.4 0.66332 [2, 3, 2, 3, 3, 2, 3, 2, 1, 3] -encouragingly 2.0 0.7746 [1, 1, 1, 3, 2, 2, 2, 3, 2, 3] -endorse 1.3 0.9 [0, 1, 0, 1, 3, 2, 2, 2, 1, 1] -endorsed 1.0 0.89443 [1, 2, 0, 1, 1, 0, 1, 0, 3, 1] -endorsement 1.3 0.9 [0, 1, 2, 2, 1, 2, 0, 1, 3, 1] -endorses 1.4 0.4899 [1, 2, 1, 2, 1, 1, 1, 2, 2, 1] -enemies -2.2 0.6 [-2, -3, -1, -2, -2, -3, -2, -3, -2, -2] -enemy -2.5 0.92195 [-3, -2, -3, -3, -3, -4, -1, -3, -1, -2] -energetic 1.9 0.53852 [2, 1, 3, 2, 2, 2, 1, 2, 2, 2] -energetically 1.8 0.6 [2, 2, 1, 1, 2, 2, 3, 1, 2, 2] -energetics 0.3 0.64031 [1, 0, 0, 0, 0, 0, 2, 0, 0, 0] -energies 0.9 1.04403 [1, 0, 0, 2, 0, 1, 3, 2, 0, 0] -energise 2.2 0.4 [2, 2, 2, 2, 2, 2, 3, 2, 3, 2] -energised 2.1 0.53852 [2, 3, 1, 2, 2, 2, 3, 2, 2, 2] -energises 2.2 0.6 [3, 3, 2, 2, 1, 3, 2, 2, 2, 2] -energising 1.9 0.7 [2, 3, 1, 2, 2, 3, 2, 1, 1, 2] -energization 1.6 0.66332 [1, 2, 1, 3, 1, 1, 2, 2, 2, 1] -energizations 1.5 1.11803 [1, 0, 3, 1, 3, 0, 1, 1, 2, 3] -energize 2.1 0.7 [2, 2, 2, 1, 3, 2, 3, 2, 3, 1] -energized 2.3 0.64031 [3, 2, 3, 3, 3, 2, 2, 2, 1, 2] -energizer 2.1 0.53852 [3, 2, 2, 2, 2, 2, 2, 3, 1, 2] -energizers 1.7 0.9 [2, 0, 2, 3, 3, 1, 1, 2, 2, 1] -energizes 2.1 0.53852 [3, 2, 3, 2, 2, 2, 2, 2, 1, 2] -energizing 2.0 0.63246 [3, 3, 2, 1, 2, 2, 1, 2, 2, 2] -energy 1.1 0.83066 [0, 2, 0, 2, 1, 1, 2, 1, 2, 0] -engage 1.4 0.8 [1, 2, 3, 2, 1, 1, 0, 1, 2, 1] -engaged 1.7 1.1 [1, 1, 2, 2, 1, 0, 2, 3, 4, 1] -engagement 2.0 1.34164 [0, 0, 3, 4, 4, 2, 1, 2, 2, 2] -engagements 0.6 0.8 [1, 0, 0, 2, 0, 2, 0, 0, 1, 0] -engager 1.1 0.7 [1, 1, 0, 2, 1, 0, 2, 1, 2, 1] -engagers 1.0 0.7746 [1, 1, 1, 0, 2, 1, 0, 2, 2, 0] -engages 1.0 0.7746 [1, 1, 0, 2, 1, 0, 1, 2, 2, 0] -engaging 1.4 0.4899 [2, 2, 1, 1, 2, 1, 1, 1, 1, 2] -engagingly 1.5 0.67082 [1, 2, 3, 1, 1, 1, 1, 1, 2, 2] -engrossed 0.6 1.49666 [0, 2, 0, 2, -2, 2, 3, -1, 0, 0] -enjoy 2.2 0.6 [3, 2, 2, 2, 3, 2, 2, 3, 2, 1] -enjoyable 1.9 0.53852 [3, 2, 2, 1, 2, 1, 2, 2, 2, 2] -enjoyableness 1.9 1.13578 [2, 2, 2, 2, 1, 3, 3, 3, -1, 2] -enjoyably 1.8 0.4 [2, 2, 2, 1, 2, 1, 2, 2, 2, 2] -enjoyed 2.3 0.64031 [2, 2, 1, 3, 3, 3, 2, 2, 2, 3] -enjoyer 2.2 0.6 [2, 2, 1, 3, 3, 2, 2, 2, 2, 3] -enjoyers 2.2 0.74833 [2, 4, 2, 2, 2, 2, 2, 3, 2, 1] -enjoying 2.4 0.66332 [2, 2, 2, 3, 3, 3, 1, 3, 2, 3] -enjoyment 2.6 0.4899 [2, 3, 2, 3, 2, 3, 2, 3, 3, 3] -enjoyments 2.0 0.7746 [3, 1, 1, 3, 2, 1, 2, 2, 2, 3] -enjoys 2.3 0.45826 [2, 3, 2, 2, 2, 3, 2, 3, 2, 2] -enlighten 2.3 1.1 [2, 2, 1, 3, 2, 1, 1, 4, 3, 4] -enlightened 2.2 0.87178 [4, 2, 3, 1, 2, 2, 1, 3, 2, 2] -enlightening 2.3 0.64031 [3, 2, 2, 2, 2, 2, 2, 4, 2, 2] -enlightens 1.7 1.00499 [2, 1, 1, 1, 1, 2, 4, 1, 3, 1] -ennui -1.2 0.6 [-1, -1, -1, -2, -1, -1, -2, -1, 0, -2] -enrage -2.6 0.91652 [-3, -3, -3, -4, -1, -1, -3, -2, -3, -3] -enraged -1.7 1.79165 [-3, -3, -3, -3, 2, -1, -3, -1, 1, -3] -enrages -1.8 1.6 [-3, -3, -3, -3, 1, -1, -3, -1, 1, -3] -enraging -2.8 0.74833 [-4, -2, -3, -2, -2, -3, -3, -2, -4, -3] -enrapture 3.0 0.63246 [2, 4, 3, 3, 4, 3, 3, 2, 3, 3] -enslave -3.1 0.9434 [-3, -4, -2, -4, -4, -2, -4, -2, -4, -2] -enslaved -1.7 2.41039 [3, -3, -3, -3, -4, -4, -4, 1, -1, 1] -enslaves -1.6 2.15407 [2, -2, -3, -2, -4, -4, -4, 1, -1, 1] -ensure 1.6 0.91652 [2, 1, 3, 1, 1, 2, 3, 2, 0, 1] -ensuring 1.1 0.9434 [0, 1, 3, 1, 1, 2, 1, 0, 2, 0] -enterprising 2.3 0.78102 [3, 2, 1, 3, 3, 2, 1, 2, 3, 3] -entertain 1.3 0.64031 [1, 2, 1, 1, 2, 1, 2, 0, 1, 2] -entertained 1.7 0.64031 [1, 2, 2, 1, 2, 1, 1, 3, 2, 2] -entertainer 1.6 1.2 [1, 4, 2, 2, 0, 0, 1, 3, 1, 2] -entertainers 1.0 0.7746 [0, 1, 2, 2, 0, 0, 1, 1, 2, 1] -entertaining 1.9 0.83066 [1, 2, 1, 1, 3, 2, 3, 2, 3, 1] -entertainingly 1.9 0.53852 [2, 1, 2, 3, 2, 2, 1, 2, 2, 2] -entertainment 1.8 0.9798 [2, 0, 4, 2, 2, 1, 2, 2, 1, 2] -entertainments 2.3 1.18743 [3, 3, 3, 2, 1, 0, 3, 4, 1, 3] -entertains 2.4 0.66332 [2, 2, 2, 2, 2, 3, 4, 3, 2, 2] -enthral 0.4 1.42829 [2, 2, 0, 2, 0, -1, -2, 2, 0, -1] -enthuse 1.6 0.66332 [1, 2, 1, 1, 3, 1, 2, 2, 2, 1] -enthused 2.0 0.63246 [3, 3, 1, 2, 2, 2, 2, 1, 2, 2] -enthuses 1.7 0.78102 [2, 3, 1, 2, 1, 3, 1, 1, 1, 2] -enthusiasm 1.9 0.9434 [3, 3, 3, 2, 1, 0, 2, 1, 2, 2] -enthusiasms 2.0 0.89443 [1, 3, 2, 2, 3, 2, 0, 2, 3, 2] -enthusiast 1.5 0.67082 [1, 2, 2, 2, 0, 1, 1, 2, 2, 2] -enthusiastic 2.2 0.9798 [1, 2, 3, 4, 2, 3, 2, 1, 1, 3] -enthusiastically 2.6 0.66332 [3, 3, 3, 2, 3, 3, 3, 3, 2, 1] -enthusiasts 1.4 0.91652 [1, 1, 0, 3, 3, 2, 1, 1, 1, 1] -enthusing 1.9 0.7 [2, 1, 2, 1, 2, 3, 2, 1, 2, 3] -entitled 1.1 0.83066 [2, 2, 1, 1, 2, 1, 1, -1, 1, 1] -entrusted 0.8 1.46969 [3, 0, 2, 2, 1, 1, -1, 0, -2, 2] -envied -1.1 0.83066 [-1, -2, -2, 1, -2, -1, -1, -1, -1, -1] -envier -1.0 0.7746 [-1, -2, -2, -1, -1, 1, -1, -1, -1, -1] -enviers -1.1 1.13578 [-3, -1, 0, -3, -1, -1, -1, -1, 1, -1] -envies -0.8 0.9798 [-1, -2, -2, 1, -1, 1, -1, -1, -1, -1] -envious -1.1 0.83066 [-2, -1, -1, -1, -2, -1, -1, 1, -2, -1] -envy -1.1 0.83066 [-2, -1, -1, -2, -1, -1, -1, 1, -1, -2] -envying -0.8 1.32665 [-1, -1, -1, -1, -3, 2, -2, -1, 1, -1] -envyingly -1.3 1.55242 [-2, 3, -2, -2, -1, -3, -1, -1, -2, -2] -erroneous -1.8 0.6 [-2, -3, -2, -2, -2, -2, -1, -1, -1, -2] -error -1.7 0.64031 [-2, -1, -2, -1, -2, -1, -1, -2, -3, -2] -errors -1.4 0.66332 [-2, -1, -2, 0, -2, -2, -1, -1, -1, -2] -escape 0.7 1.00499 [2, 0, 0, 1, 0, 1, 0, 3, 0, 0] -escapes 0.5 1.36015 [4, 1, 1, 0, -1, 0, -1, 0, 1, 0] -escaping 0.2 1.46969 [-2, 2, -1, 0, 1, 0, 2, 2, -2, 0] -esteemed 1.9 0.83066 [3, 2, 1, 2, 3, 1, 1, 2, 3, 1] -ethical 2.3 0.78102 [3, 3, 3, 3, 2, 2, 1, 3, 2, 1] -euphoria 3.3 0.9 [4, 4, 3, 3, 3, 4, 4, 4, 1, 3] -euphoric 3.2 0.87178 [3, 4, 3, 3, 3, 4, 4, 4, 1, 3] -eviction -2.0 0.63246 [-2, -2, -3, -2, -3, -2, -1, -2, -1, -2] -evil -3.4 0.91652 [-4, -4, -4, -3, -3, -4, -1, -4, -3, -4] -evildoer -3.1 0.7 [-2, -3, -3, -3, -4, -4, -3, -2, -3, -4] -evildoers -2.4 0.4899 [-3, -3, -2, -2, -2, -2, -2, -2, -3, -3] -evildoing -3.1 0.7 [-4, -4, -3, -3, -3, -4, -2, -3, -2, -3] -evildoings -2.5 1.0247 [-3, -1, -1, -3, -4, -2, -4, -2, -2, -3] -eviler -2.1 1.13578 [-2, -1, -3, -2, -4, -3, -1, -2, 0, -3] -evilest -2.5 1.0247 [-3, -4, -1, -3, -2, -3, -1, -4, -2, -2] -eviller -2.9 0.83066 [-3, -3, -4, -2, -2, -3, -2, -4, -2, -4] -evillest -3.3 0.78102 [-3, -4, -2, -3, -4, -2, -4, -4, -3, -4] -evilly -3.4 0.8 [-2, -4, -4, -4, -3, -4, -4, -4, -3, -2] -evilness -3.1 1.04403 [-3, -4, -4, -4, -4, -2, -3, -2, -1, -4] -evils -2.7 0.78102 [-3, -2, -2, -4, -4, -2, -3, -2, -3, -2] -exaggerate -0.6 0.66332 [-1, -1, -1, 0, -1, 0, 1, -1, -1, -1] -exaggerated -0.4 1.2 [-1, -1, -1, -1, -1, 2, 1, 1, -2, -1] -exaggerates -0.6 1.28062 [-1, -1, -1, -1, -1, 1, 0, 2, -3, -1] -exaggerating -0.7 0.9 [-1, -2, 0, -1, 0, 0, -2, -1, 1, -1] -exasperated -1.8 1.53623 [-4, -3, -3, -1, -1, -1, 1, -1, -4, -1] -excel 2.0 1.0 [3, 0, 2, 3, 1, 1, 3, 3, 2, 2] -excelled 2.2 0.87178 [1, 2, 2, 2, 3, 2, 4, 3, 2, 1] -excellence 3.1 0.9434 [4, 3, 4, 3, 2, 3, 1, 4, 3, 4] -excellences 2.5 0.92195 [4, 2, 2, 2, 4, 3, 2, 2, 3, 1] -excellencies 2.4 0.4899 [3, 2, 3, 3, 2, 2, 2, 2, 3, 2] -excellency 2.5 0.80623 [4, 2, 3, 3, 2, 3, 1, 3, 2, 2] -excellent 2.7 0.64031 [2, 3, 3, 3, 3, 2, 3, 2, 2, 4] -excellently 3.1 0.7 [4, 3, 3, 3, 2, 3, 3, 4, 4, 2] -excelling 2.5 0.67082 [2, 2, 3, 3, 3, 2, 2, 4, 2, 2] -excels 2.5 0.92195 [4, 2, 4, 2, 2, 1, 2, 3, 3, 2] -excelsior 0.7 0.64031 [1, 0, 0, 2, 0, 1, 1, 1, 1, 0] -excitabilities 1.5 1.0247 [2, 0, 1, 1, 3, 1, 2, 3, 2, 0] -excitability 1.2 0.87178 [0, 1, 1, 0, 1, 2, 3, 1, 2, 1] -excitable 1.5 0.92195 [2, 3, 1, 0, 1, 2, 2, 0, 2, 2] -excitableness 1.0 1.09545 [0, 0, 2, 0, 2, 0, 2, 0, 1, 3] -excitant 1.8 1.16619 [1, 0, 1, 3, 2, 0, 3, 3, 2, 3] -excitants 1.2 0.9798 [1, 0, 1, 2, 2, 2, 1, -1, 2, 2] -excitation 1.8 0.87178 [2, 0, 3, 1, 3, 2, 2, 2, 1, 2] -excitations 1.8 1.16619 [3, 3, -1, 2, 2, 2, 1, 1, 3, 2] -excitative 0.3 0.78102 [0, 1, 1, 0, 0, 0, 2, 0, -1, 0] -excitatory 1.1 1.7 [-1, 2, 2, 1, 2, 2, 2, 3, -3, 1] -excite 2.1 1.22066 [1, 2, 2, 1, 2, 0, 4, 4, 3, 2] -excited 1.4 0.4899 [1, 1, 2, 1, 2, 1, 2, 1, 1, 2] -excitedly 2.3 0.9 [3, 3, 2, 3, 1, 3, 1, 3, 1, 3] -excitement 2.2 0.4 [2, 2, 2, 3, 3, 2, 2, 2, 2, 2] -excitements 1.9 0.53852 [2, 1, 2, 3, 2, 2, 2, 2, 2, 1] -exciter 1.9 0.9434 [3, 2, 3, 1, 0, 1, 2, 3, 2, 2] -exciters 1.4 1.42829 [1, 2, 0, 1, 2, 4, 0, -1, 3, 2] -excites 2.1 0.83066 [2, 3, 3, 2, 0, 2, 2, 3, 2, 2] -exciting 2.2 0.87178 [3, 2, 1, 1, 1, 3, 3, 3, 2, 3] -excitingly 1.9 0.9434 [3, 2, 3, 0, 1, 2, 1, 2, 2, 3] -exciton 0.3 0.64031 [2, 0, 0, 0, 0, 0, 1, 0, 0, 0] -excitonic 0.2 0.6 [0, 0, 0, 0, 2, 0, 0, 0, 0, 0] -excitons 0.8 0.6 [1, 2, 0, 1, 1, 0, 0, 1, 1, 1] -excitor 0.5 0.67082 [2, 0, 0, 0, 1, 1, 1, 0, 0, 0] -exclude -0.9 1.13578 [-1, -2, -1, -3, -1, 1, -1, -1, 1, -1] -excluded -1.4 1.62481 [-2, -1, -3, -3, -2, -3, -2, 1, -1, 2] -exclusion -1.2 1.249 [-2, -2, -3, -1, -2, -1, -1, -1, 2, -1] -exclusive 0.5 0.92195 [0, 0, 0, -1, 2, 0, 1, 2, 1, 0] -excruciate -2.7 0.64031 [-2, -3, -2, -3, -3, -2, -4, -3, -2, -3] -excruciated -1.3 1.9 [-4, -1, -4, 0, 2, -2, -1, -1, -3, 1] -excruciates -1.0 2.19089 [-4, 1, -4, 0, 1, -3, -1, 1, -3, 2] -excruciating -3.3 0.9 [-3, -4, -4, -4, -4, -4, -4, -2, -2, -2] -excruciatingly -2.9 1.04403 [-2, -4, -3, -2, -4, -1, -2, -3, -4, -4] -excruciation -3.4 0.66332 [-4, -3, -2, -4, -4, -3, -4, -3, -3, -4] -excruciations -1.9 1.51327 [-3, -3, -2, -4, -1, -1, 1, -4, -1, -1] -excuse 0.3 1.73494 [0, 0, 3, -1, 0, -1, -2, 0, 4, 0] -exempt 0.4 0.91652 [1, 0, 0, 0, 2, -1, 0, 0, 2, 0] -exhaust -1.2 0.87178 [0, -1, 0, -1, -1, -3, -2, -2, -1, -1] -exhausted -1.5 1.28452 [-2, -1, 2, -2, -3, -2, -2, -1, -2, -2] -exhauster -1.3 0.64031 [-1, -1, 0, -1, -2, -1, -1, -2, -2, -2] -exhausters -1.3 0.45826 [-2, -1, -2, -1, -1, -2, -1, -1, -1, -1] -exhaustibility -0.8 1.07703 [0, -2, -3, 0, 1, -1, -1, -1, 0, -1] -exhaustible -1.0 0.63246 [-1, -1, 0, -1, -2, -2, -1, 0, -1, -1] -exhausting -1.5 0.5 [-1, -2, -1, -1, -2, -1, -2, -2, -1, -2] -exhaustion -1.5 0.92195 [-2, -1, 1, -2, -2, -2, -2, -1, -2, -2] -exhaustions -1.1 0.9434 [-1, -3, -2, -1, -1, -1, -1, 1, -1, -1] -exhaustive -0.5 0.67082 [-1, -1, 0, -1, -2, 0, 0, 0, 0, 0] -exhaustively -0.7 0.78102 [-2, 0, -1, -1, -1, -2, 0, 0, 0, 0] -exhaustiveness -1.1 1.3 [-2, -2, 0, -1, -1, 1, -4, -1, 0, -1] -exhaustless 0.2 1.8868 [1, 1, 0, 2, 3, 0, -2, 2, -2, -3] -exhaustlessness 0.9 1.75784 [2, 2, 1, 1, -4, 2, 1, 2, 0, 2] -exhausts -1.1 0.53852 [-2, -1, 0, -1, -1, -2, -1, -1, -1, -1] -exhilarated 3.0 0.63246 [3, 3, 3, 3, 2, 2, 4, 4, 3, 3] -exhilarates 2.8 1.07703 [4, 3, 3, 3, 0, 2, 3, 4, 3, 3] -exhilarating 1.7 1.61555 [3, 4, 3, 2, -1, 1, 1, 3, -1, 2] -exonerate 1.8 0.74833 [2, 2, 2, 2, 3, 2, 1, 0, 2, 2] -exonerated 1.8 1.83303 [3, -2, 2, 3, 2, 4, 3, 1, -1, 3] -exonerates 1.6 1.90788 [3, -2, 1, 2, 3, 4, 0, 3, -1, 3] -exonerating 1.0 1.41421 [2, -2, 3, 0, 0, 2, 0, 2, 2, 1] -expand 1.3 0.64031 [0, 2, 2, 1, 1, 1, 2, 1, 2, 1] -expands 0.4 0.66332 [0, 1, 0, 0, 0, 0, 0, 0, 2, 1] -expel -1.9 1.44568 [0, -4, -3, -1, -3, -1, 0, -2, -4, -1] -expelled -1.0 1.94936 [-1, -2, 2, -2, -4, -3, -2, 1, 2, -1] -expelling -1.6 1.49666 [-2, -2, -2, -2, -2, -3, -4, -1, 1, 1] -expels -1.6 1.11355 [-4, -2, 0, -3, -1, -1, -1, -2, -1, -1] -exploit -0.4 1.62481 [-2, -1, -1, 2, -2, -2, 2, -1, 2, -1] -exploited -2.0 1.0 [-3, -3, -1, -1, -1, -4, -2, -2, -1, -2] -exploiting -1.9 1.22066 [0, -3, -3, 0, -2, -3, -1, -1, -3, -3] -exploits -1.4 0.8 [-2, -2, -2, -1, -1, 0, -2, 0, -2, -2] -exploration 0.9 0.7 [2, 2, 0, 1, 1, 0, 1, 0, 1, 1] -explorations 0.3 1.1 [1, 1, 0, 0, 1, 2, 1, -2, -1, 0] -expose -0.6 0.8 [-1, -1, 0, 0, -2, 1, -1, 0, -1, -1] -exposed -0.3 1.18743 [-2, -1, 0, 2, 0, 0, -1, 1, -2, 0] -exposes -0.5 0.92195 [-1, -1, 0, 2, -1, 0, -1, -1, -1, -1] -exposing -1.1 0.7 [-2, -2, -1, -1, 0, -2, -1, -1, 0, -1] -extend 0.7 0.78102 [2, 0, 0, 0, 1, 2, 1, 1, 0, 0] -extends 0.5 0.80623 [2, 0, 2, 0, 0, 0, 1, 0, 0, 0] -exuberant 2.8 0.6 [2, 3, 2, 3, 2, 4, 3, 3, 3, 3] -exultant 3.0 1.18322 [4, 4, 3, 0, 3, 4, 3, 3, 2, 4] -exultantly 1.4 1.49666 [3, 2, 4, 1, 1, 2, -2, 1, 1, 1] -fab 2.0 1.0 [2, 1, 1, 3, 1, 2, 2, 4, 3, 1] -fabulous 2.4 0.8 [2, 2, 3, 4, 3, 3, 1, 2, 2, 2] -fabulousness 2.8 1.07703 [4, 1, 4, 3, 1, 3, 3, 2, 4, 3] -fad 0.9 0.83066 [2, 0, 1, 1, 1, 0, 0, 2, 2, 0] -fag -2.1 0.83066 [-3, -1, -2, -4, -2, -2, -2, -1, -2, -2] -faggot -3.4 0.8 [-2, -4, -4, -3, -2, -4, -4, -4, -3, -4] -faggots -3.2 0.9798 [-2, -4, -4, -4, -3, -4, -4, -3, -1, -3] -fail -2.5 0.67082 [-2, -3, -3, -3, -4, -2, -2, -2, -2, -2] -failed -2.3 0.9 [-2, -3, -1, -2, -2, -1, -3, -3, -4, -2] -failing -2.3 1.1 [-2, -3, -3, -3, -4, -1, -2, -2, 0, -3] -failingly -1.4 0.8 [-1, -3, -2, -1, 0, -1, -2, -1, -2, -1] -failings -2.2 1.07703 [-2, -2, -3, -4, -1, -2, -1, -1, -4, -2] -faille 0.1 0.3 [0, 0, 0, 0, 0, 0, 1, 0, 0, 0] -fails -1.8 0.74833 [-2, -3, -2, -3, -2, -2, -1, -1, -1, -1] -failure -2.3 1.00499 [-3, -1, -3, -2, -1, -2, -3, -1, -4, -3] -failures -2.0 0.63246 [-1, -2, -1, -2, -3, -2, -2, -3, -2, -2] -fainthearted -0.3 1.34536 [3, -1, -1, -1, -2, -1, 0, 1, -1, 0] -fair 1.3 1.00499 [0, 1, 1, 2, 4, 1, 1, 1, 1, 1] -faith 1.8 0.6 [1, 3, 2, 2, 1, 2, 2, 2, 1, 2] -faithed 1.3 1.00499 [3, 2, 1, 2, 1, 2, -1, 1, 1, 1] -faithful 1.9 0.83066 [1, 3, 2, 2, 1, 1, 3, 3, 2, 1] -faithfully 1.8 1.07703 [3, 1, 2, 2, 4, 1, 0, 1, 2, 2] -faithfulness 1.9 0.53852 [1, 2, 2, 3, 2, 2, 2, 1, 2, 2] -faithless -1.0 0.89443 [-1, -1, -1, -2, -2, -1, -1, 0, 1, -2] -faithlessly -0.9 1.51327 [-1, -2, -1, -3, -2, -1, 3, 0, -1, -1] -faithlessness -1.8 1.249 [-3, -2, 1, -2, -2, -1, -2, -1, -4, -2] -faiths 1.8 0.9798 [2, 3, 1, 1, 3, 3, 0, 2, 2, 1] -fake -2.1 0.9434 [-2, -2, -1, -1, -1, -3, -3, -4, -2, -2] -fakes -1.8 1.07703 [-2, -3, -2, -2, -3, 1, -2, -2, -1, -2] -faking -1.8 0.87178 [-3, -1, -2, -1, -2, -2, -3, -2, 0, -2] -fallen -1.5 0.80623 [-1, -1, -2, -2, -1, -3, 0, -1, -2, -2] -falling -0.6 1.8 [-2, -2, -1, 0, -1, 3, -3, 2, 0, -2] -falsified -1.6 0.91652 [-4, -1, -1, -2, -1, -1, -2, -2, -1, -1] -falsify -2.0 0.7746 [-2, -1, -3, -3, -1, -2, -2, -2, -1, -3] -fame 1.9 1.13578 [0, 2, 1, 2, 2, 4, 1, 3, 3, 1] -fan 1.3 0.78102 [2, 0, 1, 1, 2, 1, 1, 3, 1, 1] -fantastic 2.6 0.91652 [1, 3, 3, 3, 2, 4, 4, 2, 2, 2] -fantastical 2.0 1.18322 [-1, 3, 2, 2, 2, 2, 3, 1, 3, 3] -fantasticalities 2.1 1.04403 [2, 4, 2, 2, 1, 1, 2, 4, 1, 2] -fantasticality 1.7 1.26886 [4, 1, 0, 2, 2, 1, 4, 1, 1, 1] -fantasticalness 1.3 1.9 [2, 3, -3, 0, 3, 2, 2, 3, -1, 2] -fantasticate 1.5 1.96214 [1, 2, -3, 1, 4, 1, 3, 4, 0, 2] -fantastico 0.4 1.49666 [0, 0, 2, 0, 2, -2, 1, -1, -1, 3] -farce -1.7 0.45826 [-2, -2, -1, -2, -2, -1, -1, -2, -2, -2] -fascinate 2.4 1.0198 [4, 2, 2, 3, 1, 2, 3, 4, 1, 2] -fascinated 2.1 0.83066 [2, 2, 2, 3, 1, 2, 4, 2, 1, 2] -fascinates 2.0 0.44721 [2, 3, 1, 2, 2, 2, 2, 2, 2, 2] -fascination 2.2 0.74833 [2, 1, 3, 3, 2, 3, 2, 2, 1, 3] -fascinating 2.5 0.92195 [3, 3, 3, 4, 2, 3, 2, 3, 1, 1] -fascist -2.6 0.8 [-3, -3, -2, -2, -2, -3, -1, -3, -4, -3] -fascists -0.8 1.6 [-2, -3, -1, 1, -1, 2, -3, 1, -1, -1] -fatal -2.5 1.62788 [-2, -3, -3, -4, -3, -3, 2, -4, -2, -3] -fatalism -0.6 1.8 [0, 0, -3, -4, -1, 1, 0, 2, -2, 1] -fatalisms -1.7 0.9 [-2, -4, -2, -2, -2, -1, -1, -1, -1, -1] -fatalist -0.5 1.56525 [0, 0, -1, -4, -1, 2, 0, 1, -2, 0] -fatalistic -1.0 1.34164 [-3, -1, -3, -1, 1, 0, 1, -2, -1, -1] -fatalists -1.2 0.87178 [0, -2, -1, -2, -1, 0, -1, -1, -3, -1] -fatalities -2.9 0.7 [-2, -3, -3, -4, -2, -2, -3, -4, -3, -3] -fatality -3.5 0.67082 [-2, -4, -4, -4, -3, -4, -4, -4, -3, -3] -fatally -3.2 0.74833 [-3, -2, -4, -2, -3, -4, -4, -3, -3, -4] -fatigue -1.0 0.7746 [-2, -1, -1, -1, 1, -1, -2, -1, -1, -1] -fatigued -1.4 0.4899 [-2, -1, -1, -2, -1, -1, -2, -2, -1, -1] -fatigues -1.3 1.00499 [-2, -1, -1, -2, -1, 1, -3, -2, -1, -1] -fatiguing -1.2 0.6 [-1, -2, -2, -1, 0, -2, -1, -1, -1, -1] -fatiguingly -1.5 0.80623 [-1, 0, -3, -2, -1, -1, -2, -1, -2, -2] -fault -1.7 0.64031 [-1, -2, -2, -2, -1, -1, -2, -2, -1, -3] -faulted -1.4 0.4899 [-2, -2, -1, -2, -1, -1, -1, -1, -2, -1] -faultfinder -0.8 1.32665 [-3, -2, -2, -1, 1, 1, 1, -1, -1, -1] -faultfinders -1.5 0.80623 [-2, -2, -1, -3, -2, -1, 0, -1, -1, -2] -faultfinding -2.1 0.83066 [-3, -2, -1, -2, -1, -3, -1, -3, -2, -3] -faultier -2.1 0.7 [-3, -3, -3, -1, -2, -2, -2, -1, -2, -2] -faultiest -2.1 0.53852 [-3, -1, -2, -2, -2, -2, -2, -2, -3, -2] -faultily -2.0 0.89443 [-2, -2, -2, -3, -2, -1, 0, -3, -2, -3] -faultiness -1.5 0.92195 [-1, -1, -3, -1, 0, -2, -3, -1, -2, -1] -faulting -1.4 0.4899 [-1, -2, -1, -1, -2, -1, -1, -2, -1, -2] -faultless 2.0 1.41421 [3, 2, 0, 1, 3, 1, 4, 0, 2, 4] -faultlessly 2.0 1.09545 [3, 3, 2, 2, 0, 3, 2, 3, 2, 0] -faultlessness 1.1 2.02237 [3, 2, 4, 2, 1, -1, -2, 1, -2, 3] -faults -2.1 0.3 [-2, -2, -2, -2, -2, -2, -3, -2, -2, -2] -faulty -1.3 0.45826 [-1, -1, -1, -1, -2, -2, -2, -1, -1, -1] -fav 2.0 0.63246 [2, 1, 2, 2, 2, 1, 3, 2, 3, 2] -fave 1.9 1.51327 [1, 3, -2, 3, 2, 3, 1, 3, 2, 3] -favor 1.7 0.64031 [2, 2, 2, 2, 2, 2, 0, 1, 2, 2] -favorable 2.1 0.7 [2, 1, 2, 3, 1, 2, 2, 3, 3, 2] -favorableness 2.2 0.87178 [1, 2, 1, 3, 2, 2, 2, 4, 2, 3] -favorably 1.6 0.66332 [2, 1, 1, 1, 1, 2, 2, 2, 3, 1] -favored 1.8 0.6 [2, 2, 1, 1, 3, 1, 2, 2, 2, 2] -favorer 1.3 1.18743 [2, 2, 1, 1, -2, 1, 2, 2, 2, 2] -favorers 1.4 0.4899 [2, 2, 1, 2, 1, 2, 1, 1, 1, 1] -favoring 1.8 0.6 [2, 1, 1, 3, 2, 2, 1, 2, 2, 2] -favorite 2.0 0.63246 [2, 1, 3, 1, 2, 2, 2, 3, 2, 2] -favorited 1.7 0.45826 [1, 2, 2, 1, 2, 2, 2, 1, 2, 2] -favorites 1.8 0.6 [1, 2, 1, 3, 2, 2, 1, 2, 2, 2] -favoritism 0.7 1.79165 [-1, 3, -1, -1, 2, -2, 2, 2, 3, 0] -favoritisms 0.7 0.9 [0, 2, -1, 1, 0, 0, 1, 1, 2, 1] -favors 1.0 0.7746 [2, 1, 1, 1, 2, 1, -1, 1, 1, 1] -favour 1.9 0.53852 [2, 1, 2, 3, 2, 2, 2, 1, 2, 2] -favoured 1.8 0.4 [1, 2, 2, 2, 1, 2, 2, 2, 2, 2] -favourer 1.6 0.4899 [1, 2, 2, 1, 1, 2, 2, 2, 1, 2] -favourers 1.6 0.66332 [2, 2, 1, 0, 2, 2, 1, 2, 2, 2] -favouring 1.3 0.45826 [1, 2, 1, 1, 2, 1, 1, 1, 1, 2] -favours 1.8 0.6 [3, 2, 1, 2, 1, 2, 2, 1, 2, 2] -fear -2.2 0.6 [-2, -3, -2, -3, -2, -1, -2, -3, -2, -2] -feared -2.2 0.6 [-2, -3, -2, -1, -3, -2, -3, -2, -2, -2] -fearful -2.2 0.87178 [-2, -2, -3, -1, -2, -3, -2, -2, -4, -1] -fearfuller -2.2 0.87178 [-1, -4, -2, -2, -1, -2, -3, -2, -3, -2] -fearfullest -2.5 1.0247 [-3, -3, -4, -4, -3, -2, -1, -2, -2, -1] -fearfully -2.2 0.87178 [-2, -2, -2, -1, -1, -3, -4, -2, -3, -2] -fearfulness -1.8 0.87178 [-1, -1, -1, -2, -2, -1, -4, -2, -2, -2] -fearing -2.7 0.9 [-3, -3, -3, -2, -4, -2, -1, -3, -2, -4] -fearless 1.9 0.83066 [3, 3, 3, 2, 2, 2, 1, 1, 1, 1] -fearlessly 1.1 1.22066 [2, -2, 1, 1, 2, 1, 3, 1, 1, 1] -fearlessness 1.1 1.13578 [3, 2, -1, 2, 0, 2, 1, 1, 1, 0] -fears -1.8 0.6 [-2, -2, -3, -2, -2, -1, -1, -2, -1, -2] -fearsome -1.7 0.64031 [-3, -1, -1, -2, -1, -2, -2, -2, -1, -2] -fed up -1.8 1.249 [-2, -2, -3, -4, -2, -2, -1, -2, -1, 1] -feeble -1.2 1.249 [-2, -2, -3, -1, -1, -2, -1, -1, 2, -1] -feeling 0.5 1.0247 [0, 0, 0, 3, 0, 2, 0, 0, 0, 0] -felonies -2.5 0.5 [-3, -3, -3, -2, -2, -2, -2, -3, -2, -3] -felony -2.5 1.36015 [-4, -3, -4, -2, -3, -3, -2, -3, -2, 1] -ferocious -0.4 1.56205 [1, 1, -2, -3, -1, 2, 1, -2, -1, 0] -ferociously -1.1 1.86815 [-3, -4, 2, -2, 0, -2, -1, -1, 2, -2] -ferociousness -1.0 1.89737 [2, -4, -2, 0, -2, -3, -1, 0, 2, -2] -ferocities -1.0 1.54919 [1, 0, -2, 0, 0, -3, 0, 0, -2, -4] -ferocity -0.7 1.67631 [-2, -1, -4, 0, 0, -3, 1, 1, 0, 1] -fervent 1.1 1.44568 [3, 0, 0, 1, -2, 2, 2, 3, 1, 1] -fervid 0.5 2.20227 [4, -2, 1, -2, 4, 0, -1, 2, 1, -2] -festival 2.2 0.6 [2, 2, 3, 2, 3, 2, 2, 2, 3, 1] -festivalgoer 1.3 1.1 [1, 3, 2, 3, 0, 0, 1, 2, 0, 1] -festivalgoers 1.2 0.9798 [2, 2, 0, 0, 0, 2, 2, 0, 2, 2] -festivals 1.5 1.11803 [2, 0, 2, 3, 0, 3, 2, 1, 2, 0] -festive 2.0 0.63246 [2, 3, 2, 3, 1, 2, 2, 2, 1, 2] -festively 2.2 0.6 [2, 2, 3, 1, 3, 2, 3, 2, 2, 2] -festiveness 2.4 0.8 [1, 3, 2, 1, 3, 3, 3, 3, 2, 3] -festivities 2.1 0.7 [1, 2, 1, 2, 3, 2, 3, 3, 2, 2] -festivity 2.2 1.07703 [3, 3, 3, 0, 2, 1, 3, 3, 1, 3] -feud -1.4 0.66332 [-3, -2, -1, -2, -1, -1, -1, -1, -1, -1] -feudal -0.8 0.87178 [-1, -2, -2, 0, 0, 0, -2, -1, 0, 0] -feudalism -0.9 1.37477 [-2, -3, -2, -3, 0, 0, 1, 0, 0, 0] -feudalisms -0.2 0.74833 [0, 0, 0, 0, 0, 0, -1, 0, -2, 1] -feudalist -0.9 1.13578 [-2, -2, -2, -2, 0, 0, 1, 0, 0, -2] -feudalistic -1.1 0.7 [0, -1, -1, 0, -2, -1, -2, -1, -2, -1] -feudalities -0.4 1.0198 [-1, 0, -1, -2, -1, 0, -1, 0, 0, 2] -feudality -0.5 1.28452 [1, -1, 0, -1, 1, 0, -3, -2, 1, -1] -feudalization -0.3 1.18743 [-2, -2, 0, 0, 2, 0, -1, -1, 1, 0] -feudalize -0.5 0.92195 [-1, 0, -1, 0, -2, 0, 1, 0, 0, -2] -feudalized -0.8 1.07703 [-1, -1, -3, 0, 0, 0, 1, -1, -2, -1] -feudalizes -0.1 0.53852 [0, 0, -1, 0, -1, 0, 0, 0, 1, 0] -feudalizing -0.7 1.34536 [2, -2, -1, 0, 0, -2, -1, -2, 1, -2] -feudally -0.6 0.66332 [0, 0, -1, -1, 0, -1, 0, -1, -2, 0] -feudaries -0.3 0.9 [0, 0, 0, -2, -2, 0, 0, 0, 0, 1] -feudary -0.8 0.74833 [0, 0, -1, -1, -2, 0, -1, 0, -2, -1] -feudatories -0.5 0.92195 [-3, 0, -1, 0, 0, 0, 0, -1, 0, 0] -feudatory -0.1 0.83066 [-2, 0, 0, 0, 1, 0, 1, -1, 0, 0] -feuded -2.2 0.6 [-2, -2, -2, -1, -3, -3, -2, -3, -2, -2] -feuding -1.6 0.66332 [-2, -1, -2, -2, -1, -1, -3, -1, -2, -1] -feudist -1.1 0.83066 [-2, 0, -3, -1, -1, -1, 0, -1, -1, -1] -feudists -0.7 0.9 [0, 0, -1, 0, 0, -2, -2, 0, -2, 0] -feuds -1.4 1.0198 [-2, -2, -2, -1, -1, -1, -3, -2, 1, -1] -fiasco -2.3 0.64031 [-2, -2, -3, -3, -2, -3, -1, -3, -2, -2] -fidgety -1.4 0.66332 [-1, -2, -2, 0, -1, -1, -2, -1, -2, -2] -fiery -1.4 0.91652 [0, -1, -1, -2, -2, 0, -3, -1, -2, -2] -fiesta 2.1 0.7 [3, 2, 1, 2, 2, 1, 3, 3, 2, 2] -fiestas 1.5 1.0247 [3, 0, 3, 1, 0, 2, 2, 1, 2, 1] -fight -1.6 1.56205 [-1, -2, -3, -3, -1, 2, -4, -1, -2, -1] -fighter 0.6 1.11355 [3, 0, 0, -1, 1, 0, 1, 0, 2, 0] -fighters -0.2 1.46969 [-1, 2, -2, 0, 2, 0, -2, -2, 0, 1] -fighting -1.5 1.11803 [-1, -2, -3, -2, -2, -2, 0, -3, 0, 0] -fightings -1.9 0.53852 [-2, -3, -1, -2, -2, -2, -2, -1, -2, -2] -fights -1.7 0.64031 [-2, -2, -1, -2, -2, -1, -3, -1, -1, -2] -fine 0.8 0.6 [1, 0, 1, 2, 1, 1, 1, 1, 0, 0] -fire -1.4 1.49666 [-2, 0, -4, 0, -2, -1, -1, 0, -4, 0] -fired -2.6 0.91652 [-2, -3, -4, -3, -3, -1, -3, -3, -1, -3] -firing -1.4 0.8 [0, -1, -1, -1, -1, -2, -2, -3, -2, -1] -fit 1.5 1.0247 [2, 1, 2, 0, 4, 2, 1, 1, 1, 1] -fitness 1.1 0.9434 [0, 2, 1, 0, 1, 3, 2, 1, 0, 1] -flagship 0.4 0.91652 [0, 0, 0, 0, 0, 0, 0, 1, 3, 0] -flatter 0.4 1.42829 [-2, -2, 1, 2, 1, -1, 1, 2, 1, 1] -flattered 1.6 2.00998 [2, 3, 3, 1, 2, 3, 3, 1, 2, -4] -flatterer -0.3 1.9 [-4, 2, -1, 1, 2, 2, -2, -1, -1, -1] -flatterers 0.3 1.84662 [2, 1, -2, 1, 0, -4, 2, 1, 2, 0] -flatteries 1.2 1.16619 [2, 2, 3, 1, -1, 0, 0, 1, 2, 2] -flattering 1.3 2.19317 [3, 2, 2, 3, -4, 4, -1, 2, 1, 1] -flatteringly 1.0 1.61245 [2, 2, 1, 2, 1, -3, -1, 2, 2, 2] -flatters 0.6 2.10713 [1, 1, 2, 2, 3, -1, -2, 2, -4, 2] -flattery 0.4 1.49666 [1, -1, -2, 1, 3, -2, 1, 1, 1, 1] -flawed -2.1 0.99443 [-1, -2, -2, -4, -3, -2, -3, -1, -2, -1] -flawless 2.3 2.14709 [4, 3, 4, 4, 1, 2, 4, 4, -2, -1] -flawlessly 0.8 1.83303 [-2, 2, 3, 1, 0, -2, 2, 2, -1, 3] -flees -0.7 1.18743 [-3, 0, -2, 0, -1, -1, -1, 1, -1, 1] -flexibilities 1.0 1.09545 [1, 3, 1, 0, 1, -1, 2, 0, 2, 1] -flexibility 1.4 0.8 [2, 2, 0, 2, 1, 2, 1, 0, 2, 2] -flexible 0.9 0.83066 [2, 1, 0, 0, 1, 2, 0, 1, 2, 0] -flexibly 1.3 0.78102 [2, 1, 0, 0, 1, 2, 2, 1, 2, 2] -flirtation 1.7 0.64031 [3, 1, 1, 2, 2, 1, 2, 1, 2, 2] -flirtations -0.1 1.64012 [0, -4, 1, 0, 0, -2, 1, 1, 2, 0] -flirtatious 0.5 2.5 [-4, 1, 2, 1, 2, -3, 3, 4, -2, 1] -flirtatiously -0.1 1.86815 [2, -1, 1, 2, 1, 1, -3, -3, -2, 1] -flirtatiousness 0.6 1.85472 [1, 0, 2, 1, 1, 2, 1, -4, -1, 3] -flirted -0.2 1.98997 [1, 2, -1, 1, 1, 1, -3, -3, -3, 2] -flirter -0.4 1.85472 [1, 2, -1, 0, 1, 1, -3, -3, -3, 1] -flirters 0.6 2.10713 [1, 4, 0, 1, 2, 1, -4, 2, 1, -2] -flirtier -0.1 1.37477 [-2, 1, 1, 1, 1, -2, 1, -1, -2, 1] -flirtiest 0.4 1.74356 [3, 1, 2, 1, 1, -1, -3, -2, 1, 1] -flirting 0.8 1.83303 [1, 2, 2, 2, 2, -1, 1, 2, -4, 1] -flirts 0.7 1.18743 [2, -1, 2, 1, 1, -2, 1, 1, 1, 1] -flirty 0.6 1.35647 [2, -2, 2, 1, 1, -2, 1, 1, 1, 1] -flop -1.4 0.4899 [-1, -1, -2, -1, -2, -1, -2, -1, -2, -1] -flops -1.4 0.8 [-2, -2, -2, 0, -2, -1, -2, -1, 0, -2] -flu -1.6 0.8 [0, -2, -1, -2, -1, -2, -3, -1, -2, -2] -flunk -1.3 0.78102 [-2, -1, -1, -3, -1, -1, 0, -2, -1, -1] -flunked -2.1 0.9434 [-4, -1, -3, -2, -1, -1, -3, -2, -2, -2] -flunker -1.9 1.04403 [-4, -1, -3, -2, -1, -1, -3, -2, -1, -1] -flunkers -1.6 0.8 [-2, -1, -3, -2, 0, -1, -1, -2, -2, -2] -flunkey -1.8 0.9798 [-4, -1, -3, -2, -1, -1, -2, -2, -1, -1] -flunkeys -0.6 1.2 [-2, -1, -1, 2, -1, 0, -1, -2, 1, -1] -flunkies -1.4 1.11355 [-2, -2, 0, -3, 1, -2, -1, -2, -1, -2] -flunking -1.5 0.92195 [-2, -1, -1, -3, -1, -1, 0, -2, -3, -1] -flunks -1.8 1.32665 [0, -2, -3, -3, -2, -3, -2, -1, 1, -3] -flunky -1.8 1.4 [-2, -3, -3, -3, -2, -1, -2, -2, 2, -2] -flustered -1.0 1.18322 [-1, -1, -1, -1, -3, -2, 2, -1, -1, -1] -focused 1.6 0.91652 [2, 2, 1, 3, 0, 1, 1, 2, 3, 1] -foe -1.9 1.22066 [-1, -3, -2, -2, -2, -2, -4, 1, -2, -2] -foehns 0.2 0.4 [1, 0, 0, 0, 0, 0, 0, 0, 1, 0] -foeman -1.8 0.6 [-2, -3, -1, -2, -2, -2, -2, -1, -1, -2] -foemen -0.3 1.18743 [0, 0, -1, 0, 0, -2, -2, -1, 2, 1] -foes -2.0 0.89443 [-2, -1, -2, -2, -4, -3, -2, -1, -1, -2] -foetal -0.1 0.3 [0, -1, 0, 0, 0, 0, 0, 0, 0, 0] -foetid -2.3 1.41774 [-1, -3, 0, -2, -3, 0, -3, -3, -4, -4] -foetor -3.0 0.89443 [-3, -4, -2, -3, -3, -1, -4, -4, -3, -3] -foetors -2.1 1.04403 [-2, -3, -1, -3, -2, -2, 0, -4, -2, -2] -foetus 0.2 0.6 [0, 0, 0, 0, 0, 0, 0, 0, 2, 0] -foetuses 0.2 0.6 [2, 0, 0, 0, 0, 0, 0, 0, 0, 0] -fond 1.9 0.83066 [2, 3, 2, 3, 1, 1, 3, 2, 1, 1] -fondly 1.9 0.7 [1, 2, 3, 2, 2, 3, 2, 1, 1, 2] -fondness 2.5 0.67082 [3, 2, 2, 2, 2, 3, 4, 3, 2, 2] -fool -1.9 0.53852 [-2, -2, -2, -2, -1, -2, -2, -3, -1, -2] -fooled -1.6 0.4899 [-2, -1, -1, -2, -2, -1, -2, -1, -2, -2] -fooleries -1.8 1.07703 [-1, -2, 0, -2, -1, -2, -4, -2, -3, -1] -foolery -1.8 0.87178 [-2, -2, -3, 0, -3, -1, -2, -2, -2, -1] -foolfish -0.8 0.87178 [-1, 0, -1, -2, 0, 0, 0, -2, 0, -2] -foolfishes -0.4 0.4899 [-1, -1, -1, 0, 0, 0, 0, 0, 0, -1] -foolhardier -1.5 0.67082 [-2, -1, -2, -1, -2, -1, -2, -2, 0, -2] -foolhardiest -1.3 0.64031 [0, -2, -1, -1, -1, -1, -2, -1, -2, -2] -foolhardily -1.0 1.41421 [-1, -1, -2, -2, -2, -2, -1, -1, 3, -1] -foolhardiness -1.6 0.66332 [-3, -1, -1, -1, -2, -1, -2, -2, -2, -1] -foolhardy -1.4 0.4899 [-2, -2, -1, -1, -1, -2, -1, -1, -2, -1] -fooling -1.7 0.64031 [-2, -2, -1, -2, -2, -2, -1, -3, -1, -1] -foolish -1.1 0.83066 [-1, -1, -1, -2, -2, -1, -1, -2, 1, -1] -foolisher -1.7 0.64031 [-2, -1, -2, -1, -2, -1, -2, -3, -2, -1] -foolishest -1.4 1.28062 [-2, 1, -2, -3, -2, -2, -1, 1, -2, -2] -foolishly -1.8 0.6 [-2, -1, -2, -2, -3, -1, -1, -2, -2, -2] -foolishness -1.8 0.6 [-1, -1, -2, -2, -2, -1, -3, -2, -2, -2] -foolishnesses -2.0 0.89443 [-1, -1, -1, -2, -3, -1, -3, -3, -2, -3] -foolproof 1.6 0.91652 [2, 1, 3, 1, 1, 0, 1, 2, 2, 3] -fools -2.2 0.74833 [-2, -4, -2, -2, -1, -2, -2, -2, -2, -3] -foolscaps -0.8 0.6 [0, -1, -1, -1, 0, -1, -2, 0, -1, -1] -forbid -1.3 0.78102 [-2, -2, -1, -1, -1, -1, 0, -1, -1, -3] -forbiddance -1.4 1.35647 [-3, -1, -2, -3, -1, 2, -1, -2, -2, -1] -forbiddances -1.0 2.0 [-2, 3, 1, -2, -4, -2, -3, -1, -1, 1] -forbidden -1.8 0.74833 [-1, -2, -2, -2, -1, -1, -3, -3, -2, -1] -forbidder -1.6 0.66332 [-1, -2, -2, -2, -2, 0, -2, -2, -2, -1] -forbidders -1.5 0.80623 [-1, -2, -1, -3, -2, -2, 0, -2, -1, -1] -forbidding -1.9 0.7 [-3, -1, -1, -2, -2, -1, -3, -2, -2, -2] -forbiddingly -1.9 0.53852 [-2, -1, -2, -2, -2, -2, -3, -2, -1, -2] -forbids -1.3 0.45826 [-1, -1, -2, -1, -1, -2, -1, -2, -1, -1] -forced -2.0 0.63246 [-1, -2, -3, -3, -1, -2, -2, -2, -2, -2] -foreclosure -0.5 1.43178 [-1, -2, -3, 2, -1, 1, -1, 0, 1, -1] -foreclosures -2.4 0.66332 [-3, -2, -3, -2, -3, -3, -1, -2, -2, -3] -forgave 1.4 0.91652 [2, 2, 1, 2, 1, -1, 1, 2, 2, 2] -forget -0.9 0.53852 [-1, -1, -1, -1, 0, -1, -1, 0, -2, -1] -forgetful -1.1 1.3 [-3, -1, -2, 1, 0, -2, 1, -1, -2, -2] -forgivable 1.7 0.64031 [2, 1, 2, 1, 2, 2, 1, 2, 3, 1] -forgivably 1.6 0.66332 [1, 1, 2, 1, 2, 2, 1, 2, 3, 1] -forgive 1.1 1.22066 [2, 1, 1, 3, 1, 1, 1, 2, -2, 1] -forgiven 1.6 0.66332 [2, 1, 1, 3, 2, 2, 1, 2, 1, 1] -forgiveness 1.1 1.22066 [2, 1, 1, 1, 3, 2, -2, 1, 1, 1] -forgiver 1.7 0.78102 [3, 1, 1, 3, 1, 2, 1, 2, 2, 1] -forgivers 1.2 0.6 [2, 1, 2, 1, 0, 1, 1, 2, 1, 1] -forgives 1.7 0.78102 [2, 1, 3, 1, 1, 3, 2, 1, 1, 2] -forgiving 1.9 0.7 [2, 3, 2, 1, 2, 3, 1, 1, 2, 2] -forgivingly 1.4 0.4899 [2, 1, 2, 1, 1, 1, 2, 1, 2, 1] -forgivingness 1.8 0.6 [3, 1, 2, 1, 2, 2, 2, 2, 2, 1] -forgotten -0.9 0.53852 [-1, 0, -1, 0, -1, -1, -1, -1, -2, -1] -fortunate 1.9 0.53852 [2, 2, 1, 1, 2, 2, 2, 3, 2, 2] -fought -1.3 0.78102 [-2, -1, -2, -1, 0, -1, -1, -1, -1, -3] -foughten -1.9 1.3 [-1, -3, 0, -2, -4, -3, -2, 0, -1, -3] -frantic -1.9 0.7 [-3, -2, -2, -1, -2, -1, -2, -3, -1, -2] -frantically -1.4 0.4899 [-2, -1, -2, -1, -1, -1, -1, -1, -2, -2] -franticness -0.7 1.18743 [-1, -2, 2, -1, -1, -1, 1, -2, -1, -1] -fraud -2.8 0.6 [-3, -3, -2, -3, -2, -3, -3, -2, -4, -3] -frauds -2.3 0.45826 [-2, -2, -2, -3, -3, -2, -3, -2, -2, -2] -fraudster -2.5 0.92195 [-4, -1, -2, -2, -4, -2, -3, -2, -3, -2] -fraudsters -2.4 0.91652 [-4, -3, -3, -3, -1, -2, -2, -2, -1, -3] -fraudulence -2.3 0.78102 [-3, -2, -2, -3, -2, -1, -2, -4, -2, -2] -fraudulent -2.2 0.6 [-2, -3, -2, -2, -2, -1, -3, -3, -2, -2] -freak -1.9 0.9434 [-3, -2, -1, -2, -4, -1, -2, -1, -2, -1] -freaked -1.2 1.32665 [-2, -2, 1, 0, -1, -2, -3, 1, -2, -2] -freakier -1.3 1.1 [-3, -2, -2, 1, -2, -2, -1, 0, -1, -1] -freakiest -1.6 1.0198 [-2, -3, -3, -3, -1, -1, -1, 0, -1, -1] -freakiness -1.4 0.8 [-1, -1, -1, -2, -3, 0, -2, -1, -2, -1] -freaking -1.8 1.16619 [0, -4, -3, -2, -3, -1, -1, -1, -2, -1] -freakish -2.1 1.37477 [-1, -3, -2, -1, -2, -3, -4, -3, 1, -3] -freakishly -0.8 1.249 [-2, -2, 1, -2, -1, 1, -1, 1, -1, -2] -freakishness -1.4 1.68523 [-2, -4, -1, 0, -1, -2, 1, 1, -4, -2] -freakout -1.8 1.6 [-3, 1, -3, -2, -3, -1, -4, 1, -2, -2] -freakouts -1.5 0.92195 [-2, -2, -1, -1, -2, -2, -2, 1, -2, -2] -freaks -0.4 1.35647 [2, 0, -2, -1, 0, 1, -2, 1, -1, -2] -freaky -1.5 1.20416 [-2, -2, -2, -2, -1, -2, 2, -2, -2, -2] -free 2.3 0.9 [2, 4, 3, 3, 2, 1, 2, 3, 1, 2] -freebase -0.1 1.44568 [2, 0, -2, 1, -3, 0, -1, 0, 1, 1] -freebased 0.8 1.16619 [2, 0, -1, 0, 3, 0, 1, 2, 1, 0] -freebases 0.8 1.249 [2, 0, -1, 0, 2, 0, 0, 3, 2, 0] -freebasing -0.4 1.56205 [-4, -2, 0, 0, 1, 2, 0, -1, 0, 0] -freebee 1.3 0.78102 [1, 2, 1, 1, 1, 0, 3, 2, 1, 1] -freebees 1.3 1.26886 [2, 2, -2, 2, 2, 2, 0, 2, 1, 2] -freebie 1.8 0.9798 [2, 1, 3, 2, 2, 4, 1, 1, 1, 1] -freebies 1.8 0.9798 [2, 3, 1, 1, 2, 4, 1, 1, 2, 1] -freeboard 0.3 0.64031 [0, 0, 0, 0, 0, 1, 0, 0, 0, 2] -freeboards 0.7 0.9 [0, 0, 0, 1, 0, 0, 2, 2, 2, 0] -freeboot -0.7 1.67631 [1, -2, -3, -2, -1, -2, -1, 2, -1, 2] -freebooter -1.7 1.00499 [-2, -2, -3, -3, -2, -2, 0, -1, 0, -2] -freebooters -0.2 1.32665 [-1, -3, 1, 0, -2, 1, 0, 1, 0, 1] -freebooting -0.8 1.249 [-2, -2, -1, 2, -1, -1, -1, 1, -2, -1] -freeborn 1.2 0.74833 [1, 0, 3, 1, 1, 1, 1, 1, 2, 1] -freed 1.7 1.34536 [-2, 2, 3, 2, 2, 2, 3, 1, 2, 2] -freedman 1.1 0.9434 [1, 2, 0, 1, 2, 1, 3, 0, 0, 1] -freedmen 0.7 0.78102 [1, 2, 1, 2, 0, 1, 0, 0, 0, 0] -freedom 3.2 0.9798 [4, 4, 1, 3, 2, 4, 4, 3, 3, 4] -freedoms 1.2 1.07703 [2, 1, 1, 3, 2, 1, 2, 1, -1, 0] -freedwoman 1.6 1.74356 [3, 2, 0, 4, 4, 3, 1, -1, 0, 0] -freedwomen 1.3 0.78102 [2, 0, 2, 0, 2, 1, 1, 1, 2, 2] -freeform 0.9 0.83066 [0, 0, 0, 2, 1, 2, 1, 1, 2, 0] -freehand 0.5 0.80623 [0, 0, 0, 1, 0, 2, 0, 2, 0, 0] -freehanded 1.4 0.91652 [3, 0, 0, 2, 1, 2, 2, 1, 2, 1] -freehearted 1.5 0.67082 [2, 0, 1, 2, 2, 2, 2, 1, 1, 2] -freehold 0.7 0.78102 [1, 1, 0, 0, 2, 0, 2, 0, 1, 0] -freeholder 0.5 0.5 [1, 1, 0, 0, 0, 1, 1, 0, 1, 0] -freeholders 0.1 0.83066 [0, 0, 1, 0, 0, 1, 0, -2, 0, 1] -freeholds 1.0 0.63246 [1, 0, 2, 0, 1, 2, 1, 1, 1, 1] -freeing 2.1 1.04403 [2, 1, 1, 1, 4, 2, 2, 4, 2, 2] -freelance 1.2 1.66132 [3, 0, 0, 0, 0, 1, 4, 0, 4, 0] -freelanced 0.7 1.00499 [3, 0, 0, 0, 0, 2, 1, 0, 1, 0] -freelancer 1.1 1.04403 [2, 0, 3, 2, 1, 0, 0, 0, 2, 1] -freelancers 0.4 0.66332 [0, 0, 0, 2, 0, 0, 0, 1, 1, 0] -freelances 0.7 0.9 [1, 0, 0, 0, 0, 2, 2, 0, 2, 0] -freelancing 0.4 0.66332 [2, 0, 0, 0, 1, 0, 0, 0, 1, 0] -freeload -1.9 1.04403 [-2, -3, -1, -2, -1, 0, -1, -3, -3, -3] -freeloaded -1.6 0.8 [-2, 0, -3, -1, -1, -2, -2, -2, -2, -1] -freeloader -0.7 1.00499 [-2, 0, -1, -2, -1, 1, -1, 1, -1, -1] -freeloaders -0.1 1.57797 [-2, -2, -1, 0, 0, 2, -2, 0, 2, 2] -freeloading -1.3 2.0025 [1, -2, -4, -2, -3, -3, 1, 2, 0, -3] -freeloads -1.3 0.9 [-1, -1, -2, -2, -2, 0, 0, -1, -1, -3] -freely 1.9 0.53852 [2, 1, 2, 2, 2, 3, 2, 2, 1, 2] -freeman 1.7 0.78102 [2, 2, 2, 1, 2, 0, 3, 1, 2, 2] -freemartin -0.5 0.92195 [0, 0, 0, -1, 0, -1, 0, 0, -3, 0] -freemasonries 0.7 0.78102 [0, 1, 0, 0, 0, 1, 1, 0, 2, 2] -freemasonry 0.3 0.64031 [1, 0, 2, 0, 0, 0, 0, 0, 0, 0] -freemen 1.5 0.67082 [1, 1, 0, 2, 2, 2, 2, 2, 1, 2] -freeness 1.6 0.66332 [1, 2, 3, 2, 2, 1, 1, 1, 2, 1] -freenesses 1.7 0.78102 [1, 2, 1, 2, 2, 2, 3, 2, 2, 0] -freer 1.1 0.7 [2, 2, 0, 2, 1, 1, 1, 0, 1, 1] -freers 1.0 0.89443 [0, 1, 1, 2, 3, 1, 0, 1, 0, 1] -frees 1.2 0.6 [1, 2, 0, 1, 1, 1, 2, 1, 1, 2] -freesia 0.4 0.91652 [0, 0, 3, 0, 1, 0, 0, 0, 0, 0] -freesias 0.4 0.66332 [0, 0, 0, 1, 1, 2, 0, 0, 0, 0] -freest 1.6 1.28062 [3, 4, 0, 3, 0, 1, 1, 2, 1, 1] -freestanding 1.1 0.83066 [2, 1, 1, 2, 0, 0, 0, 2, 1, 2] -freestyle 0.7 0.9 [2, 0, 1, 0, 2, 0, 0, 2, 0, 0] -freestyler 0.4 0.91652 [0, 0, 0, 0, 1, 0, 0, 0, 0, 3] -freestylers 0.8 0.87178 [2, 1, 0, 0, 0, 1, 0, 2, 2, 0] -freestyles 0.3 0.64031 [0, 0, 0, 0, 1, 0, 0, 0, 0, 2] -freethinker 1.0 0.63246 [1, 2, 1, 1, 2, 1, 0, 0, 1, 1] -freethinkers 1.0 0.7746 [1, 0, 0, 1, 2, 2, 1, 2, 0, 1] -freethinking 1.1 0.7 [1, 0, 1, 1, 2, 2, 0, 2, 1, 1] -freeware 0.7 1.48661 [1, 0, 0, 2, 4, 0, 1, -2, 1, 0] -freeway 0.2 0.6 [0, 0, 0, 0, 0, 0, 2, 0, 0, 0] -freewheel 0.5 1.11803 [2, 0, 1, 2, 0, -2, 0, 0, 1, 1] -freewheeled 0.3 0.78102 [1, 0, 0, 0, 0, 1, 2, -1, 0, 0] -freewheeler 0.2 0.87178 [-2, 1, 0, 0, 0, 1, 1, 1, 0, 0] -freewheelers -0.3 1.00499 [-2, 0, 0, 0, 2, -1, -1, 0, -1, 0] -freewheeling 0.5 1.11803 [-1, 2, 0, -1, 1, 2, 2, 0, 0, 0] -freewheelingly 0.8 0.87178 [1, 2, 0, 0, 1, 2, 1, -1, 1, 1] -freewheels 0.6 0.91652 [0, 3, 1, 1, 1, 0, 0, 0, 0, 0] -freewill 1.0 0.7746 [1, 1, 1, -1, 1, 1, 1, 2, 2, 1] -freewriting 0.8 1.07703 [0, 2, 0, 0, 1, 0, 3, 0, 2, 0] -freeze 0.2 0.9798 [-1, 0, 1, 1, -1, 0, 0, -1, 2, 1] -freezers -0.1 0.3 [0, 0, 0, -1, 0, 0, 0, 0, 0, 0] -freezes -0.1 1.13578 [0, -2, -2, 1, 0, 0, 0, 0, 2, 0] -freezing -0.4 1.28062 [-2, -1, -2, -2, 0, 0, 0, 1, 2, 0] -freezingly -1.6 0.4899 [-1, -2, -2, -1, -2, -2, -2, -2, -1, -1] -frenzy -1.3 1.48661 [-1, -1, -2, -2, 2, -4, -1, -2, 0, -2] -fresh 1.3 0.45826 [2, 2, 1, 1, 1, 1, 2, 1, 1, 1] -friend 2.2 0.6 [2, 2, 3, 2, 3, 3, 1, 2, 2, 2] -friended 1.7 0.78102 [2, 2, 1, 3, 1, 1, 2, 3, 1, 1] -friending 1.8 1.07703 [1, 4, 2, 0, 1, 3, 2, 2, 1, 2] -friendless -1.5 0.67082 [-1, -2, -2, -1, 0, -2, -1, -2, -2, -2] -friendlessness -0.3 2.05183 [-2, -2, 2, 1, -4, -1, 2, 1, -2, 2] -friendlier 2.0 0.63246 [3, 2, 2, 1, 2, 2, 2, 1, 3, 2] -friendlies 2.2 0.74833 [3, 2, 2, 3, 2, 2, 1, 3, 1, 3] -friendliest 2.6 0.91652 [3, 3, 1, 3, 2, 1, 3, 3, 4, 3] -friendlily 1.8 0.74833 [1, 2, 2, 1, 3, 1, 1, 2, 3, 2] -friendliness 2.0 0.7746 [3, 1, 3, 2, 2, 3, 2, 1, 2, 1] -friendly 2.2 0.6 [2, 1, 3, 3, 2, 2, 3, 2, 2, 2] -friends 2.1 0.53852 [3, 3, 2, 2, 2, 1, 2, 2, 2, 2] -friendship 1.9 0.53852 [1, 2, 2, 1, 3, 2, 2, 2, 2, 2] -friendships 1.6 0.91652 [2, 1, 1, 0, 3, 2, 2, 3, 1, 1] -fright -1.6 1.35647 [-2, -1, 0, -3, -2, -4, 1, -1, -2, -2] -frighted -1.4 0.91652 [0, -1, -1, -1, -2, -1, -3, -1, -1, -3] -frighten -1.4 0.8 [0, -1, -1, -1, -2, -1, -3, -2, -1, -2] -frightened -1.9 0.7 [-2, -3, -1, -1, -2, -2, -3, -1, -2, -2] -frightening -2.2 0.9798 [-1, -1, -4, -3, -3, -3, -2, -2, -1, -2] -frighteningly -2.1 0.7 [-2, -2, -2, -2, -4, -2, -1, -2, -2, -2] -frightens -1.7 0.78102 [-2, -1, -2, -1, -1, -1, -2, -3, -3, -1] -frightful -2.3 0.78102 [-2, -2, -2, -2, -3, -2, -3, -1, -4, -2] -frightfully -1.7 0.78102 [-1, -1, -1, -2, -2, -1, -2, -3, -1, -3] -frightfulness -1.9 0.7 [-1, -1, -2, -3, -3, -2, -1, -2, -2, -2] -frighting -1.5 0.67082 [-1, -2, -2, -3, -1, -1, -1, -1, -2, -1] -frights -1.1 0.83066 [-2, 0, -2, 0, -2, -1, 0, -1, -1, -2] -frisky 1.0 1.48324 [1, -2, 1, 1, 1, 3, 3, 2, -1, 1] -frowning -1.4 1.42829 [-1, -1, -1, -3, -3, 1, -2, -3, 1, -2] -frustrate -2.0 0.63246 [-2, -3, -2, -1, -3, -2, -2, -1, -2, -2] -frustrated -2.4 0.66332 [-2, -1, -3, -3, -2, -2, -3, -2, -3, -3] -frustrates -1.9 0.7 [-1, -1, -3, -2, -1, -2, -2, -2, -3, -2] -frustrating -1.9 0.83066 [-2, -2, -1, -1, -1, -2, -2, -2, -4, -2] -frustratingly -2.0 0.63246 [-1, -3, -2, -2, -2, -2, -2, -3, -2, -1] -frustration -2.1 0.7 [-3, -2, -3, -2, -1, -2, -3, -2, -1, -2] -frustrations -2.0 0.7746 [-2, -1, -1, -3, -2, -2, -3, -3, -2, -1] -fuck -2.5 1.20416 [0, -3, -4, -3, -2, -3, -4, -1, -2, -3] -fucked -3.4 0.66332 [-2, -3, -4, -3, -4, -4, -3, -4, -3, -4] -fucker -3.3 0.78102 [-3, -4, -4, -2, -3, -4, -4, -2, -4, -3] -fuckers -2.9 0.9434 [-3, -3, -4, -3, -4, -4, -2, -1, -2, -3] -fuckface -3.2 1.07703 [-4, -2, -4, -1, -4, -4, -2, -4, -3, -4] -fuckhead -3.1 1.04403 [-1, -4, -2, -4, -3, -3, -2, -4, -4, -4] -fucks -2.1 1.13578 [-3, -2, -1, -1, -1, -2, -4, -2, -4, -1] -fucktard -3.1 0.9434 [-4, -4, -4, -3, -4, -2, -4, -2, -2, -2] -fud -1.1 1.37477 [-1, -3, -1, -1, -3, -2, 2, 0, -1, -1] -fuked -2.5 0.92195 [-2, -3, -3, -3, -3, -3, 0, -3, -3, -2] -fuking -3.2 0.9798 [-4, -1, -3, -4, -3, -2, -4, -3, -4, -4] -fulfill 1.9 1.04403 [1, 1, 2, 4, 1, 1, 2, 1, 3, 3] -fulfilled 1.8 0.87178 [1, 2, 1, 0, 2, 2, 3, 2, 2, 3] -fulfills 1.0 1.09545 [2, 1, 1, 1, 1, -2, 2, 2, 1, 1] -fume -1.2 1.16619 [0, 0, 0, -2, -3, -2, -1, -3, -1, 0] -fumed -1.8 0.87178 [-3, -2, -3, -2, -2, 0, -2, -1, -1, -2] -fumeless 0.3 0.64031 [0, 0, 0, 1, 0, 0, 0, 2, 0, 0] -fumelike -0.7 1.18743 [0, 0, -3, 0, 0, -2, -1, -2, 1, 0] -fumer 0.7 0.9 [2, 1, 0, 1, 0, 2, 0, -1, 1, 1] -fumers -0.8 0.6 [0, -1, -1, -2, -1, 0, 0, -1, -1, -1] -fumes -0.1 1.13578 [0, -2, 0, 0, -1, 1, -1, -1, 1, 2] -fumet 0.4 1.0198 [2, 0, 0, -1, 0, 1, -1, 0, 2, 1] -fumets -0.4 0.66332 [0, -1, 0, -1, 0, 0, -2, 0, 0, 0] -fumette -0.6 1.11355 [-2, -2, 0, -1, -1, 2, 0, 0, -1, -1] -fuming -2.7 0.64031 [-2, -3, -3, -2, -3, -4, -3, -2, -2, -3] -fun 2.3 0.45826 [2, 3, 2, 3, 2, 2, 3, 2, 2, 2] -funeral -1.5 1.74642 [-2, -3, -2, -1, -3, -1, -4, 1, 2, -2] -funerals -1.6 2.2891 [-3, -4, -1, -4, 2, -3, -3, 2, 1, -3] -funky -0.4 1.62481 [0, -1, 2, -1, 2, 0, -4, -1, 0, -1] -funned 2.3 0.9 [2, 3, 3, 4, 1, 2, 2, 2, 3, 1] -funnel 0.1 0.53852 [1, 0, 0, 0, 0, -1, 0, 0, 1, 0] -funneled 0.1 0.3 [0, 0, 0, 0, 0, 1, 0, 0, 0, 0] -funnelform 0.5 0.80623 [0, 0, 1, 0, 0, 0, 0, 2, 2, 0] -funneling -0.1 0.3 [0, 0, 0, 0, -1, 0, 0, 0, 0, 0] -funnelled -0.1 0.3 [0, 0, 0, 0, -1, 0, 0, 0, 0, 0] -funnelling 0.1 0.3 [0, 0, 0, 0, 1, 0, 0, 0, 0, 0] -funnels 0.4 0.66332 [0, 0, 0, 1, 0, 0, 0, 0, 2, 1] -funner 2.2 0.74833 [2, 2, 3, 4, 1, 2, 2, 2, 2, 2] -funnest 2.9 0.7 [4, 3, 4, 3, 2, 3, 2, 3, 2, 3] -funnier 1.7 1.00499 [2, 2, -1, 2, 2, 2, 3, 1, 2, 2] -funnies 1.3 1.00499 [2, 1, -1, 2, 1, 2, 3, 1, 1, 1] -funniest 2.6 0.8 [3, 3, 3, 3, 2, 2, 1, 2, 4, 3] -funnily 1.9 0.53852 [2, 3, 1, 2, 2, 2, 2, 1, 2, 2] -funniness 1.8 0.9798 [3, 2, 3, 2, 2, 1, 3, 0, 1, 1] -funninesses 1.6 0.91652 [1, 3, 0, 3, 1, 2, 1, 2, 2, 1] -funning 1.8 0.9798 [2, 2, 1, 2, 1, 4, 0, 2, 2, 2] -funny 1.9 0.53852 [3, 2, 2, 1, 2, 2, 1, 2, 2, 2] -funnyman 1.4 0.4899 [2, 2, 1, 2, 1, 1, 1, 1, 2, 1] -funnymen 1.3 1.1 [2, 1, 1, 0, 0, 3, 3, 1, 2, 0] -furious -2.7 1.41774 [-3, -3, -3, -4, -4, -4, 1, -2, -3, -2] -furiously -1.9 1.04403 [-2, -2, -4, -2, -1, -2, -1, -3, 0, -2] -fury -2.7 0.78102 [-4, -3, -2, -2, -2, -3, -4, -2, -3, -2] -futile -1.9 0.83066 [0, -3, -2, -2, -2, -2, -3, -1, -2, -2] -gag -1.4 1.0198 [-2, -2, -1, -2, 0, -2, -3, 0, 0, -2] -gagged -1.3 1.55242 [-2, -2, -1, -2, 2, -3, -1, -3, 1, -2] -gain 2.4 0.4899 [2, 3, 2, 2, 3, 2, 3, 2, 3, 2] -gained 1.6 0.66332 [2, 1, 2, 1, 1, 3, 2, 1, 2, 1] -gaining 1.8 0.4 [1, 2, 2, 2, 1, 2, 2, 2, 2, 2] -gains 1.4 0.4899 [1, 2, 1, 2, 2, 2, 1, 1, 1, 1] -gallant 1.7 1.1 [4, 0, 3, 1, 1, 2, 2, 2, 1, 1] -gallantly 1.9 0.53852 [2, 2, 3, 2, 2, 2, 2, 1, 2, 1] -gallantry 2.6 0.8 [3, 3, 1, 2, 2, 3, 4, 2, 3, 3] -geek -0.8 0.9798 [0, 0, 0, -2, -3, -1, -1, 0, 0, -1] -geekier 0.2 1.4 [0, 3, -1, -1, -1, 1, 2, 1, -1, -1] -geekiest -0.1 0.9434 [1, -1, -1, -1, -1, 1, 1, 1, 0, -1] -geeks -0.4 0.91652 [0, 0, -1, 0, 0, 0, 0, 0, -3, 0] -geeky -0.6 0.91652 [0, 0, -1, 0, -1, 0, -1, 0, -3, 0] -generosities 2.6 0.4899 [3, 3, 2, 3, 2, 3, 2, 3, 2, 3] -generosity 2.3 0.64031 [3, 1, 2, 2, 3, 2, 3, 3, 2, 2] -generous 2.3 0.78102 [3, 2, 4, 2, 2, 1, 2, 3, 2, 2] -generously 1.8 0.74833 [3, 3, 2, 1, 2, 1, 1, 2, 1, 2] -generousness 2.4 0.91652 [3, 2, 3, 1, 3, 4, 3, 2, 2, 1] -genial 1.8 0.6 [3, 1, 2, 1, 2, 2, 1, 2, 2, 2] -gentle 1.9 0.53852 [2, 2, 2, 1, 2, 3, 2, 2, 1, 2] -gentler 1.4 0.4899 [2, 1, 1, 1, 1, 2, 2, 1, 2, 1] -gentlest 1.8 0.4 [2, 1, 2, 2, 2, 1, 2, 2, 2, 2] -gently 2.0 0.7746 [2, 2, 2, 1, 1, 3, 3, 2, 1, 3] -ghost -1.3 1.34536 [-2, 0, 0, 0, 0, -3, -2, -3, 0, -3] -giddy -0.6 1.62481 [-2, -2, 3, -1, -1, -1, -1, -2, 2, -1] -gift 1.9 0.53852 [2, 1, 2, 2, 2, 1, 2, 3, 2, 2] -giggle 1.8 0.9798 [2, 2, 2, 2, 2, 3, 2, -1, 2, 2] -giggled 1.5 1.20416 [1, 3, 1, 3, 3, 1, 1, -1, 2, 1] -giggler 0.6 0.8 [1, 1, 1, 1, -1, 1, 1, 1, -1, 1] -gigglers 1.4 0.4899 [1, 2, 2, 1, 2, 1, 1, 1, 1, 2] -giggles 0.8 1.249 [1, 2, 2, 1, -1, 1, 1, 2, -2, 1] -gigglier 1.0 1.09545 [2, 1, 1, 2, 2, 1, -1, 2, 1, -1] -giggliest 1.7 1.26886 [4, 2, 1, 2, 1, 3, 2, 2, -1, 1] -giggling 1.5 0.5 [2, 2, 1, 2, 2, 1, 1, 1, 1, 2] -gigglingly 1.1 1.37477 [1, 2, 1, 1, -1, 2, 1, -1, 4, 1] -giggly 1.0 1.41421 [1, 2, -2, 1, 2, 3, 1, -1, 2, 1] -giver 1.4 0.66332 [1, 2, 2, 0, 1, 2, 1, 2, 1, 2] -givers 1.7 1.34536 [2, -1, 3, 3, 3, 1, 1, 2, 0, 3] -giving 1.4 1.0198 [1, 1, 3, 1, 1, 2, 3, 0, 2, 0] -glad 2.0 0.63246 [3, 2, 1, 2, 2, 2, 1, 3, 2, 2] -gladly 1.4 0.4899 [2, 2, 1, 2, 1, 1, 2, 1, 1, 1] -glamor 2.1 0.9434 [1, 2, 2, 2, 1, 3, 2, 4, 3, 1] -glamorise 1.3 1.1 [0, 1, 4, 1, 0, 2, 1, 2, 1, 1] -glamorised 1.8 0.74833 [1, 2, 2, 2, 2, 2, 0, 2, 3, 2] -glamorises 2.1 1.04403 [1, 3, 2, 4, 2, 2, 0, 2, 3, 2] -glamorising 1.2 1.16619 [3, 2, 0, 3, 1, 2, 0, 1, 0, 0] -glamorization 1.6 0.91652 [2, 2, 3, 0, 3, 1, 2, 1, 1, 1] -glamorize 1.7 1.1 [1, 2, 1, 4, 2, 0, 3, 1, 2, 1] -glamorized 2.1 1.04403 [3, 2, 1, 2, 4, 2, 2, 0, 3, 2] -glamorizer 2.4 1.0198 [3, 2, 2, 3, 4, 3, 2, 0, 3, 2] -glamorizers 1.6 1.11355 [4, 1, 1, 1, 1, 2, 0, 2, 3, 1] -glamorizes 2.4 1.2 [3, 2, 2, 4, 4, 1, 2, 0, 3, 3] -glamorizing 1.8 1.16619 [3, 0, 1, 2, 3, 2, 1, 0, 3, 3] -glamorous 2.3 0.78102 [3, 2, 4, 2, 2, 2, 3, 2, 2, 1] -glamorously 2.1 1.04403 [1, 3, 2, 1, 2, 1, 4, 1, 3, 3] -glamors 1.4 0.66332 [1, 1, 2, 2, 2, 1, 2, 2, 0, 1] -glamour 2.4 0.91652 [2, 4, 2, 1, 3, 2, 2, 2, 2, 4] -glamourize 0.8 1.32665 [2, 1, 0, 1, 0, 4, 0, 0, -1, 1] -glamourless -1.6 1.49666 [-4, -1, -1, -2, -2, -3, -2, -1, 2, -2] -glamourous 2.0 0.7746 [1, 3, 3, 2, 1, 2, 2, 2, 3, 1] -glamours 1.9 0.83066 [1, 3, 2, 2, 3, 2, 1, 1, 3, 1] -glee 3.2 0.4 [3, 4, 3, 3, 4, 3, 3, 3, 3, 3] -gleeful 2.9 0.53852 [3, 3, 3, 3, 3, 4, 2, 2, 3, 3] -gloom -2.6 0.66332 [-4, -2, -3, -3, -2, -3, -2, -2, -2, -3] -gloomed -1.9 0.7 [-1, -2, -3, -1, -2, -2, -1, -2, -3, -2] -gloomful -2.1 0.9434 [-3, -1, -4, -2, -1, -1, -2, -3, -2, -2] -gloomier -1.5 1.20416 [-3, -2, -2, -3, -1, -2, 0, 1, -1, -2] -gloomiest -1.8 2.03961 [-2, -2, 2, -4, -2, -3, -4, -3, 2, -2] -gloominess -1.8 0.6 [-2, -1, -2, -3, -2, -1, -2, -2, -2, -1] -gloominesses -1.0 1.09545 [-1, -2, -2, -1, -1, -2, 2, -1, -1, -1] -glooming -1.8 0.74833 [-1, -2, -2, -1, -2, -1, -3, -1, -3, -2] -glooms -0.9 1.57797 [3, -2, -1, -2, -2, -2, 1, -2, -1, -1] -gloomy -0.6 1.56205 [2, -1, -2, -2, -2, -1, 1, -2, 2, -1] -gloried 2.4 1.0198 [2, 3, 3, 4, 4, 1, 1, 2, 2, 2] -glories 2.1 1.3 [4, 1, 4, 1, 1, 4, 2, 2, 1, 1] -glorification 2.0 0.89443 [3, 1, 3, 2, 3, 1, 1, 3, 2, 1] -glorified 2.3 0.9 [1, 4, 2, 2, 4, 2, 2, 2, 2, 2] -glorifier 2.3 1.00499 [1, 4, 1, 2, 4, 2, 3, 2, 2, 2] -glorifiers 1.6 1.0198 [2, 1, 2, -1, 2, 2, 2, 1, 2, 3] -glorifies 2.2 0.9798 [1, 4, 2, 2, 4, 2, 1, 2, 2, 2] -glorify 2.7 0.78102 [3, 3, 4, 3, 1, 3, 2, 3, 2, 3] -glorifying 2.4 1.28062 [3, 4, 2, 2, 4, 4, 0, 1, 2, 2] -gloriole 1.5 1.36015 [2, 4, 1, 2, 0, -1, 1, 3, 2, 1] -glorioles 1.2 0.87178 [0, 2, 0, 2, 0, 1, 2, 2, 1, 2] -glorious 3.2 0.6 [4, 3, 3, 2, 3, 3, 3, 4, 3, 4] -gloriously 2.9 0.83066 [3, 4, 3, 2, 4, 2, 2, 2, 4, 3] -gloriousness 2.6 1.0198 [3, 2, 3, 4, 3, 2, 1, 4, 3, 1] -glory 2.5 0.80623 [1, 3, 3, 1, 3, 3, 3, 2, 3, 3] -glum -2.1 0.7 [-2, -1, -3, -3, -1, -2, -2, -3, -2, -2] -gn8 0.6 0.66332 [1, 1, 0, 0, 0, 0, 2, 1, 0, 1] -god 1.1 1.51327 [0, 0, 0, 1, 0, 3, 0, 3, 0, 4] -goddam -2.5 1.28452 [0, -3, -3, -4, -3, -1, -4, -1, -3, -3] -goddammed -2.4 0.91652 [-2, -3, -1, -1, -2, -2, -4, -3, -3, -3] -goddamn -2.1 1.75784 [-3, -3, -2, -4, -4, -3, -3, -1, 1, 1] -goddamned -1.8 2.03961 [-3, -3, -3, -4, -1, 2, -2, -3, 2, -3] -goddamns -2.1 1.51327 [-3, -2, -4, 2, -2, -3, -3, -2, -2, -2] -goddams -1.9 1.92094 [-3, -3, -2, -4, -4, -2, -3, -1, 2, 1] -godsend 2.8 0.87178 [2, 3, 3, 2, 4, 3, 3, 1, 4, 3] -good 1.9 0.9434 [2, 1, 1, 3, 2, 4, 2, 2, 1, 1] -goodness 2.0 1.54919 [2, 2, 2, 3, 1, 2, -2, 4, 3, 3] -gorgeous 3.0 0.63246 [3, 3, 2, 3, 3, 3, 4, 4, 3, 2] -gorgeously 2.3 0.78102 [2, 2, 2, 3, 1, 2, 4, 3, 2, 2] -gorgeousness 2.9 0.9434 [3, 4, 3, 1, 4, 4, 2, 2, 3, 3] -gorgeousnesses 2.1 0.7 [3, 2, 1, 3, 2, 2, 1, 2, 3, 2] -gossip -0.7 0.45826 [-1, -1, -1, 0, 0, -1, -1, 0, -1, -1] -gossiped -1.1 0.53852 [-1, -1, -1, -1, -1, -1, 0, -1, -2, -2] -gossiper -1.1 0.7 [-1, -1, -1, 0, -2, -1, -1, -2, 0, -2] -gossipers -1.1 0.53852 [-1, 0, -1, -1, -1, -1, -1, -1, -2, -2] -gossiping -1.6 0.4899 [-1, -2, -1, -2, -1, -2, -2, -1, -2, -2] -gossipmonger -1.0 1.41421 [-1, -2, 1, -3, -2, 1, -1, -2, -2, 1] -gossipmongers -1.4 0.66332 [-2, -1, -1, -1, -2, -2, -1, 0, -2, -2] -gossipped -1.3 0.9 [-2, -2, -1, -2, -1, -1, -2, -1, 1, -2] -gossipping -1.8 0.6 [-2, -1, -2, -2, -1, -2, -2, -1, -3, -2] -gossipries -0.8 0.6 [-1, -1, -1, 0, -1, 0, -1, 0, -2, -1] -gossipry -1.2 1.16619 [1, 0, -1, -2, -1, -1, -1, -3, -3, -1] -gossips -1.3 0.64031 [-1, -2, -1, -1, -2, -1, 0, -1, -2, -2] -gossipy -1.3 0.78102 [-1, -2, -2, -1, -2, -1, 0, 0, -2, -2] -grace 1.8 0.4 [2, 1, 2, 2, 1, 2, 2, 2, 2, 2] -graced 0.9 1.04403 [1, 1, 2, -2, 1, 1, 1, 2, 1, 1] -graceful 2.0 0.63246 [2, 1, 2, 2, 2, 3, 3, 2, 2, 1] -gracefuller 2.2 0.74833 [2, 3, 2, 2, 1, 2, 3, 1, 3, 3] -gracefullest 2.8 0.74833 [3, 3, 3, 3, 1, 3, 3, 3, 4, 2] -gracefully 2.4 0.66332 [3, 3, 2, 1, 3, 2, 2, 2, 3, 3] -gracefulness 2.2 0.6 [3, 2, 1, 2, 2, 2, 3, 2, 2, 3] -graces 1.6 0.4899 [2, 2, 2, 1, 1, 2, 1, 2, 1, 2] -gracile 1.7 0.78102 [1, 3, 2, 1, 2, 3, 2, 1, 1, 1] -graciles 0.6 0.8 [0, 0, 0, 0, 0, 0, 2, 1, 2, 1] -gracilis 0.4 0.66332 [0, 0, 0, 0, 0, 1, 0, 1, 0, 2] -gracility 1.2 0.87178 [1, 1, 0, 1, 1, 3, 2, 2, 0, 1] -gracing 1.3 0.9 [1, 0, 3, 2, 1, 2, 0, 1, 2, 1] -gracioso 1.0 0.63246 [2, 2, 1, 1, 1, 1, 0, 1, 0, 1] -gracious 2.6 0.8 [2, 2, 3, 3, 3, 3, 2, 4, 1, 3] -graciously 2.3 0.9 [2, 4, 1, 3, 3, 2, 1, 2, 3, 2] -graciousness 2.4 0.66332 [2, 2, 2, 2, 2, 3, 4, 3, 2, 2] -grand 2.0 0.63246 [2, 2, 3, 1, 2, 2, 2, 2, 3, 1] -grandee 1.1 0.83066 [0, 1, 1, 0, 1, 1, 2, 1, 3, 1] -grandees 1.2 0.87178 [0, 2, 2, 1, 0, 1, 0, 2, 2, 2] -grander 1.7 0.9 [3, 1, 1, 2, 2, 2, 0, 2, 3, 1] -grandest 2.4 1.2 [3, 3, 1, 2, 2, 0, 4, 2, 4, 3] -grandeur 2.4 1.11355 [3, 2, 3, 2, 4, 1, 1, 4, 1, 3] -grandeurs 2.1 1.3 [2, 2, 1, 0, 0, 4, 3, 3, 3, 3] -grant 1.5 0.80623 [2, 2, 1, 0, 3, 1, 1, 1, 2, 2] -granted 1.0 1.09545 [3, 0, 0, 0, 0, 1, 2, 2, 2, 0] -granting 1.3 0.45826 [2, 1, 1, 2, 1, 2, 1, 1, 1, 1] -grants 0.9 0.7 [2, 1, 2, 1, 0, 1, 0, 0, 1, 1] -grateful 2.0 0.63246 [2, 3, 1, 2, 2, 2, 3, 1, 2, 2] -gratefuller 1.8 0.87178 [2, 3, 0, 3, 2, 1, 1, 2, 2, 2] -gratefully 2.1 0.53852 [2, 3, 2, 2, 2, 2, 2, 3, 1, 2] -gratefulness 2.2 0.6 [2, 3, 2, 1, 2, 2, 3, 2, 3, 2] -graticule 0.1 0.3 [0, 0, 0, 1, 0, 0, 0, 0, 0, 0] -graticules 0.2 0.6 [0, 0, 0, 0, 2, 0, 0, 0, 0, 0] -gratification 1.6 0.8 [1, 2, 3, 2, 2, 1, 2, 0, 2, 1] -gratifications 1.8 0.4 [2, 2, 1, 2, 2, 1, 2, 2, 2, 2] -gratified 1.6 0.91652 [3, 1, 1, 1, 3, 1, 1, 1, 1, 3] -gratifies 1.5 0.80623 [3, 1, 1, 1, 2, 1, 1, 1, 1, 3] -gratify 1.3 1.00499 [2, -1, 1, 3, 1, 1, 1, 1, 2, 2] -gratifying 2.3 0.45826 [2, 3, 2, 2, 2, 2, 3, 2, 2, 3] -gratifyingly 2.0 0.63246 [2, 2, 2, 1, 3, 2, 1, 3, 2, 2] -gratin 0.4 0.91652 [0, 1, 0, 0, 0, 0, 2, 0, -1, 2] -grating -0.4 0.4899 [-1, -1, -1, 0, 0, -1, 0, 0, 0, 0] -gratingly -0.2 1.6 [1, -3, -2, -2, 0, 2, 1, -1, 1, 1] -gratings -0.8 0.9798 [0, -2, -1, -1, 0, 0, -3, 0, 0, -1] -gratins 0.2 0.6 [0, 0, 0, 0, 0, 0, 0, 0, 2, 0] -gratis 0.2 0.9798 [-2, 1, 1, 0, 0, 0, -1, 1, 1, 1] -gratitude 2.3 0.64031 [2, 2, 3, 1, 2, 3, 2, 3, 3, 2] -gratz 2.0 0.89443 [2, 3, 2, 1, 1, 1, 2, 2, 4, 2] -grave -1.6 1.62481 [-2, -2, 0, -2, -3, 2, -3, -1, -1, -4] -graved -0.9 1.13578 [0, 0, -1, 0, -1, -1, -1, -1, -4, 0] -gravel -0.5 0.5 [0, -1, 0, -1, -1, -1, -1, 0, 0, 0] -graveled -0.5 0.80623 [0, 0, 0, 0, -1, -2, 0, 0, -2, 0] -graveless -1.3 1.34536 [-2, -2, 0, -1, 0, -2, -4, 1, -1, -2] -graveling -0.4 1.28062 [-3, 0, -2, 0, 2, -1, 0, 0, 0, 0] -gravelled -0.9 0.53852 [0, -1, -1, -2, 0, -1, -1, -1, -1, -1] -gravelling -0.4 1.11355 [0, -1, -2, -2, 0, -1, 0, 0, 2, 0] -gravelly -0.9 0.7 [0, -2, -1, -1, 0, -1, -1, 0, -1, -2] -gravels -0.5 0.80623 [0, -1, 0, 0, 0, -2, 0, 0, 0, -2] -gravely -1.5 1.0247 [0, -3, -1, 0, -3, -2, -1, -1, -2, -2] -graven -0.9 1.22066 [0, 0, -1, 0, -2, -1, -1, 0, -4, 0] -graveness -1.5 0.67082 [-1, -2, -2, -3, -2, -1, -1, -1, -1, -1] -graver -1.1 1.22066 [0, -2, -1, 0, 0, -2, -1, 0, -4, -1] -gravers -1.2 1.6 [-4, 0, -2, 0, -2, -2, -2, 0, 2, -2] -graves -1.2 1.07703 [0, 0, -1, -1, -2, -1, -1, -1, -4, -1] -graveside -0.8 0.6 [-1, -1, -1, 0, 0, 0, -1, -2, -1, -1] -gravesides -1.6 1.2 [-2, -1, 0, -3, -1, 0, -1, -2, -2, -4] -gravest -1.3 1.9 [-3, -1, -2, -2, 1, 1, -2, 2, -3, -4] -gravestone -0.7 0.78102 [0, -1, 0, -1, -1, -2, 0, 0, -2, 0] -gravestones -0.5 0.5 [-1, -1, 0, -1, -1, -1, 0, 0, 0, 0] -graveyard -1.2 0.87178 [0, 0, -1, -2, -1, -1, -2, -1, -3, -1] -graveyards -1.2 0.87178 [0, -1, -3, -1, -1, -2, 0, -1, -2, -1] -great 3.1 0.7 [2, 4, 4, 4, 3, 3, 3, 3, 2, 3] -greater 1.5 0.67082 [2, 1, 2, 1, 2, 2, 2, 1, 0, 2] -greatest 3.2 0.74833 [3, 4, 3, 3, 3, 4, 4, 2, 2, 4] -greed -1.7 1.61555 [-2, -1, -2, -1, -2, -4, -1, 2, -4, -2] -greedier -2.0 0.63246 [-2, -2, -2, -2, -2, -3, -2, -1, -1, -3] -greediest -2.8 0.87178 [-3, -4, -3, -2, -2, -4, -4, -2, -2, -2] -greedily -1.9 1.22066 [-2, -1, -3, -3, -3, -2, -1, -2, 1, -3] -greediness -1.7 1.00499 [-2, -1, -2, -1, -2, -4, -1, 0, -2, -2] -greeds -1.0 1.18322 [-1, -2, -2, -2, -2, -2, 1, 0, -1, 1] -greedy -1.3 1.48661 [-2, -2, -2, -2, -3, -2, 2, -1, -2, 1] -greenwash -1.8 1.4 [-1, 0, -2, -2, -3, -4, 0, 0, -3, -3] -greenwashing -0.4 0.91652 [-1, 0, 0, 1, 1, -2, -1, -1, 0, -1] -greet 1.3 0.64031 [1, 1, 1, 1, 0, 2, 2, 2, 2, 1] -greeted 1.1 0.9434 [2, 0, 0, 1, 1, 1, 0, 2, 1, 3] -greeting 1.6 0.4899 [2, 1, 2, 2, 1, 2, 2, 1, 1, 2] -greetings 1.8 1.07703 [1, 2, 3, 3, 1, 1, 1, 4, 1, 1] -greets 0.6 0.66332 [0, 0, 2, 0, 1, 1, 0, 1, 1, 0] -grey 0.2 0.4 [0, 0, 1, 0, 0, 0, 1, 0, 0, 0] -grief -2.2 0.6 [-2, -1, -3, -2, -3, -3, -2, -2, -2, -2] -grievance -2.1 0.53852 [-2, -2, -3, -2, -2, -3, -2, -1, -2, -2] -grievances -1.5 0.5 [-2, -2, -1, -1, -2, -1, -1, -2, -2, -1] -grievant -0.8 1.249 [-2, 1, -1, -2, -1, 2, -2, -1, -1, -1] -grievants -1.1 0.83066 [-1, -1, -1, -1, -1, -1, 0, -2, 0, -3] -grieve -1.6 1.49666 [-2, -3, -1, -3, 1, -3, -1, -2, 1, -3] -grieved -2.0 0.89443 [-3, -3, -3, -2, -2, -3, -1, -1, -1, -1] -griever -1.9 0.83066 [-2, -2, -3, -2, -3, -3, -1, -1, -1, -1] -grievers -0.3 1.55242 [-1, 2, -2, -1, 1, -2, 2, -2, 1, -1] -grieves -2.1 0.9434 [-3, -3, -3, -2, -3, -3, -1, -1, -1, -1] -grieving -2.3 1.1 [-2, -4, -2, -3, -3, 0, -3, -2, -1, -3] -grievous -2.0 1.84391 [-3, -4, -2, -3, -1, 3, -2, -3, -2, -3] -grievously -1.7 1.55242 [-3, -1, -4, -2, -2, 1, -3, 1, -2, -2] -grievousness -2.7 0.78102 [-3, -3, -3, -2, -3, -4, -2, -1, -3, -3] -grim -2.7 0.64031 [-2, -4, -3, -3, -2, -2, -3, -3, -2, -3] -grimace -1.0 2.14476 [-4, -3, -2, -2, 2, -1, -1, -3, 2, 2] -grimaced -2.0 0.63246 [-2, -3, -2, -2, -2, -2, -1, -3, -1, -2] -grimaces -1.8 0.74833 [-1, -2, -1, -2, -2, -1, -3, -3, -1, -2] -grimacing -1.4 1.56205 [-3, -2, -3, -3, -1, -1, 1, 0, 1, -3] -grimalkin -0.9 1.04403 [-1, -2, -1, 1, -2, -2, -1, -1, 1, -1] -grimalkins -0.9 0.9434 [0, 0, 0, -2, -1, -1, -1, 0, -3, -1] -grime -1.5 0.92195 [-1, -2, -1, -1, -1, -3, 0, -2, -1, -3] -grimed -1.2 0.74833 [-2, -2, 0, -2, -1, -1, -1, -2, -1, 0] -grimes -1.0 0.7746 [-2, -2, 0, 0, -1, -1, -1, -2, -1, 0] -grimier -1.6 1.0198 [-1, -2, -2, -2, -1, 0, -4, -1, -1, -2] -grimiest -0.7 2.05183 [-2, -3, 1, -3, 2, -2, -2, -2, 2, 2] -grimily -0.7 1.61555 [-2, -1, -1, -2, -2, 2, -2, 2, 1, -2] -griminess -1.6 0.4899 [-1, -2, -2, -2, -1, -2, -2, -1, -1, -2] -griming -0.7 1.55242 [-3, -1, -1, -2, 0, 2, -1, -2, -1, 2] -grimly -1.3 1.55242 [-2, -1, 2, -2, -2, -1, -3, -3, 1, -2] -grimmer -1.5 1.36015 [1, -2, -3, 1, -2, -1, -2, -2, -3, -2] -grimmest -0.8 1.72047 [-2, -1, -3, 0, -2, -1, 0, 2, 2, -3] -grimness -0.8 1.98997 [2, -2, -3, -2, -3, 2, -1, 1, 1, -3] -grimy -1.8 0.87178 [-2, -2, -2, -1, -1, -3, 0, -2, -2, -3] -grin 2.1 0.83066 [2, 4, 2, 2, 2, 1, 2, 3, 1, 2] -grinned 1.1 0.9434 [1, 1, 2, 1, 3, 1, -1, 1, 1, 1] -grinner 1.1 0.83066 [1, 1, 2, 2, 2, 1, -1, 1, 1, 1] -grinners 1.6 0.8 [2, 2, 2, 3, 1, 0, 2, 2, 1, 1] -grinning 1.5 1.0247 [3, 2, 2, 1, 1, -1, 1, 2, 2, 2] -grins 0.9 1.92094 [1, 4, -3, 1, 2, 1, 2, -2, 2, 1] -gross -2.1 1.51327 [-1, -3, -2, -3, -3, -3, -3, 2, -2, -3] -grossed -0.4 1.11355 [-1, -2, -1, -2, 0, 0, 1, 1, 1, -1] -grosser -0.3 1.41774 [1, -2, -1, -2, 0, -1, 1, 2, 1, -2] -grosses -0.8 1.77764 [-2, -2, 3, -2, -3, -1, 1, -1, 1, -2] -grossest -2.1 0.83066 [-2, -1, -2, -3, -3, -1, -3, -3, -1, -2] -grossing -0.3 1.79165 [-1, -3, -1, 1, 0, -1, -3, 1, 1, 3] -grossly -0.9 1.44568 [1, -2, 0, -3, -1, -2, 1, 1, -2, -2] -grossness -1.8 0.6 [-2, -2, -1, -1, -1, -3, -2, -2, -2, -2] -grossular -0.3 1.34536 [0, -2, 0, -1, -2, -1, 0, 0, 0, 3] -grossularite -0.1 1.13578 [2, 0, 0, 0, 0, -3, 0, 0, 0, 0] -grossularites -0.7 1.26886 [0, -4, -1, -2, 0, 0, 0, 0, 0, 0] -grossulars -0.3 0.45826 [0, 0, 0, 0, -1, -1, 0, 0, 0, -1] -grouch -2.2 0.87178 [-2, -3, -3, -3, -2, -1, -3, -1, -1, -3] -grouched -0.8 0.9798 [-2, -1, -2, -2, 1, -1, 0, 0, 0, -1] -grouches -0.9 1.13578 [-2, -1, -2, -1, -1, -1, -1, 2, 0, -2] -grouchier -2.0 0.63246 [-2, -3, -3, -2, -2, -2, -2, -1, -2, -1] -grouchiest -2.3 0.78102 [-3, -3, -2, -2, -1, -3, -1, -3, -3, -2] -grouchily -1.4 1.56205 [-2, -1, -2, -3, -3, 2, -2, -2, 1, -2] -grouchiness -2.0 0.7746 [-2, -2, -3, -2, -3, -2, -2, 0, -2, -2] -grouching -1.7 1.1 [-1, -3, -2, 1, -2, -3, -2, -1, -2, -2] -grouchy -1.9 0.7 [-1, -3, -2, -2, -1, -3, -1, -2, -2, -2] -growing 0.7 0.64031 [0, 1, 1, 2, 1, 0, 0, 1, 1, 0] -growth 1.6 1.0198 [2, 0, 3, 0, 2, 3, 1, 1, 2, 2] -guarantee 1.0 1.0 [2, 3, 1, 0, 2, 0, 1, 0, 0, 1] -guilt -1.1 1.22066 [-1, -3, 2, -1, -1, -2, -1, -2, -1, -1] -guiltier -2.0 0.63246 [-2, -1, -3, -1, -3, -2, -2, -2, -2, -2] -guiltiest -1.7 1.79165 [-3, -2, -2, -4, -1, -2, 3, -1, -3, -2] -guiltily -1.1 1.57797 [-3, -1, -1, -2, 0, -2, 3, -2, -1, -2] -guiltiness -1.8 0.6 [-2, -2, -1, -2, -1, -1, -2, -2, -3, -2] -guiltless 0.8 1.53623 [3, 2, 1, 2, -2, 1, 1, -2, 1, 1] -guiltlessly 0.7 1.18743 [-1, 1, -2, 2, 1, 1, 1, 1, 2, 1] -guiltlessness 0.6 1.42829 [1, 1, -1, -1, -1, 1, 2, 3, -1, 2] -guilts -1.4 0.66332 [-1, -2, -1, -1, -3, -1, -1, -2, -1, -1] -guilty -1.8 0.6 [-1, -2, -2, -3, -2, -2, -1, -2, -2, -1] -gullibility -1.6 0.66332 [-1, -1, -2, -2, -1, -2, -1, -2, -1, -3] -gullible -1.5 0.67082 [-1, -2, -2, -1, -1, -3, -2, -1, -1, -1] -gun -1.4 1.49666 [0, -4, 0, -3, 0, -3, -2, 0, -2, 0] -h8 -2.7 1.00499 [-4, -3, -4, -1, -1, -3, -3, -3, -2, -3] -ha 1.4 0.8 [1, 0, 1, 1, 3, 2, 2, 1, 2, 1] -hacked -1.7 1.00499 [-2, -1, -2, -4, 0, -2, -2, -1, -1, -2] -haha 2.0 0.89443 [1, 1, 2, 3, 2, 1, 4, 2, 2, 2] -hahaha 2.6 1.0198 [2, 4, 2, 4, 1, 2, 3, 4, 2, 2] -hahas 1.8 0.9798 [1, 2, 2, 4, 3, 2, 1, 1, 1, 1] -hail 0.3 0.9 [0, 0, 0, 2, 0, 0, 2, 0, -1, 0] -hailed 0.9 0.83066 [1, 2, 1, 1, 0, 0, 0, 2, 2, 0] -hallelujah 3.0 0.7746 [3, 4, 3, 1, 3, 3, 3, 3, 3, 4] -handsome 2.2 0.74833 [2, 2, 2, 2, 2, 3, 4, 1, 2, 2] -handsomely 1.9 0.7 [1, 3, 1, 1, 2, 2, 2, 2, 2, 3] -handsomeness 2.4 1.28062 [2, 4, 1, 4, 0, 2, 4, 3, 2, 2] -handsomer 2.0 0.63246 [2, 3, 2, 2, 2, 2, 1, 3, 1, 2] -handsomest 2.6 0.91652 [3, 2, 1, 2, 3, 4, 4, 3, 2, 2] -hapless -1.4 1.11355 [-3, -1, -1, -1, -2, -1, 1, -2, -3, -1] -haplessness -1.4 1.0198 [-1, -2, 0, -1, -1, -1, -1, -2, -1, -4] -happier 2.4 0.66332 [3, 1, 2, 3, 2, 2, 3, 3, 3, 2] -happiest 3.2 0.74833 [4, 3, 2, 4, 4, 3, 3, 3, 2, 4] -happily 2.6 0.91652 [4, 1, 2, 4, 2, 3, 2, 2, 3, 3] -happiness 2.6 0.4899 [2, 3, 3, 3, 3, 2, 2, 3, 2, 3] -happing 1.1 0.83066 [1, 1, 1, 0, 2, 2, 0, 2, 0, 2] -happy 2.7 0.9 [2, 2, 2, 4, 2, 4, 3, 4, 2, 2] -harass -2.2 0.6 [-2, -3, -2, -2, -2, -3, -2, -3, -1, -2] -harassed -2.5 0.80623 [-4, -2, -3, -3, -2, -2, -3, -2, -3, -1] -harasser -2.4 0.8 [-3, -2, -2, -3, -2, -2, -4, -2, -3, -1] -harassers -2.8 0.6 [-3, -3, -2, -2, -3, -3, -3, -4, -2, -3] -harasses -2.5 0.80623 [-3, -3, -2, -3, -2, -2, -4, -2, -3, -1] -harassing -2.5 1.62788 [-2, -4, -3, -4, -3, -3, 2, -2, -3, -3] -harassment -2.5 0.67082 [-2, -3, -2, -2, -3, -2, -4, -3, -2, -2] -harassments -2.6 0.4899 [-3, -3, -2, -3, -2, -3, -3, -2, -2, -3] -hard -0.4 1.2 [0, -1, 0, -1, 0, 1, -2, -1, -2, 2] -hardier -0.6 1.68523 [-3, -2, -2, 1, 1, 2, 1, 0, -2, -2] -hardship -1.3 1.84662 [-2, 2, -4, -1, -2, -3, -1, -2, 2, -2] -hardy 1.7 1.00499 [1, 2, 1, 0, 2, 2, 4, 1, 2, 2] -harm -2.5 0.80623 [-2, -2, -2, -3, -2, -1, -3, -3, -3, -4] -harmed -2.1 0.83066 [-1, -4, -2, -2, -2, -2, -1, -2, -3, -2] -harmfully -2.6 0.91652 [-3, -4, -3, -1, -3, -3, -3, -3, -1, -2] -harmfulness -2.6 0.8 [-3, -1, -3, -3, -3, -2, -4, -2, -2, -3] -harming -2.6 0.66332 [-3, -3, -2, -2, -3, -3, -2, -2, -2, -4] -harmless 1.0 0.7746 [2, 1, 1, 1, 1, 0, 0, 2, 0, 2] -harmlessly 1.4 1.2 [4, 0, 1, 0, 1, 1, 1, 2, 3, 1] -harmlessness 0.8 1.16619 [1, 2, 0, 1, 0, 1, 2, 1, 2, -2] -harmonic 1.8 0.87178 [2, 1, 2, 3, 0, 1, 3, 2, 2, 2] -harmonica 0.6 0.8 [0, 1, 0, 0, 0, 2, 1, 0, 2, 0] -harmonically 2.1 1.13578 [3, 3, 4, 1, 0, 1, 2, 2, 2, 3] -harmonicas 0.1 0.3 [0, 0, 0, 0, 0, 0, 1, 0, 0, 0] -harmonicist 0.5 0.92195 [0, 0, 0, 0, 1, 0, 0, 0, 1, 3] -harmonicists 0.9 1.3 [2, 1, 0, 0, 2, 0, 0, 0, 4, 0] -harmonics 1.5 1.0247 [2, 2, 2, 0, 0, 2, 3, 2, 0, 2] -harmonies 1.3 0.9 [2, 0, 2, 1, 2, 2, 0, 2, 0, 2] -harmonious 2.0 1.09545 [3, 4, 2, 2, 2, 0, 2, 3, 1, 1] -harmoniously 1.9 0.9434 [4, 2, 2, 1, 2, 1, 1, 3, 2, 1] -harmoniousness 1.8 0.6 [1, 2, 2, 2, 2, 1, 2, 3, 2, 1] -harmonise 1.8 0.74833 [1, 1, 2, 3, 2, 1, 1, 3, 2, 2] -harmonised 1.3 0.9 [2, 3, 2, 0, 2, 1, 1, 1, 1, 0] -harmonising 1.4 0.66332 [1, 2, 1, 1, 2, 1, 1, 1, 1, 3] -harmonium 0.9 1.22066 [0, 3, 0, 2, 3, 0, 0, 0, 0, 1] -harmoniums 0.8 0.9798 [0, 0, 0, 2, 0, 2, 0, 2, 2, 0] -harmonization 1.9 0.83066 [3, 1, 2, 2, 2, 2, 3, 0, 2, 2] -harmonizations 0.9 0.9434 [0, 0, 2, 0, 2, 2, 0, 2, 1, 0] -harmonize 1.7 0.78102 [3, 2, 2, 1, 2, 2, 0, 1, 2, 2] -harmonized 1.6 0.91652 [1, 2, 1, 1, 2, 2, 3, 3, 0, 1] -harmonizer 1.6 0.8 [1, 2, 1, 1, 2, 2, 2, 3, 0, 2] -harmonizers 1.6 1.11355 [2, 2, 2, 1, 2, 0, 4, 0, 2, 1] -harmonizes 1.5 0.92195 [0, 2, 2, 2, 0, 1, 1, 2, 3, 2] -harmonizing 1.4 0.66332 [0, 1, 1, 2, 2, 1, 2, 2, 1, 2] -harmony 1.7 0.45826 [2, 2, 2, 2, 1, 2, 2, 2, 1, 1] -harms -2.2 1.6 [2, -3, -2, -2, -3, -2, -4, -4, -2, -2] -harried -1.4 0.4899 [-1, -1, -2, -1, -2, -2, -1, -1, -1, -2] -harsh -1.9 0.7 [-1, -1, -2, -2, -1, -3, -3, -2, -2, -2] -harsher -2.2 0.6 [-2, -3, -2, -3, -2, -2, -1, -3, -2, -2] -harshest -2.9 0.83066 [-4, -2, -2, -2, -2, -3, -3, -4, -4, -3] -hate -2.7 1.00499 [-4, -3, -4, -4, -2, -2, -2, -2, -1, -3] -hated -3.2 0.6 [-3, -3, -4, -3, -2, -3, -3, -4, -4, -3] -hateful -2.2 1.249 [-3, 1, -3, -3, -1, -2, -2, -3, -3, -3] -hatefully -2.3 0.78102 [-1, -3, -3, -3, -1, -2, -2, -2, -3, -3] -hatefulness -3.6 0.4899 [-4, -4, -3, -3, -3, -4, -4, -4, -4, -3] -hater -1.8 0.6 [-2, -1, -2, -2, -2, -1, -1, -2, -2, -3] -haters -2.2 0.6 [-2, -1, -3, -2, -3, -2, -3, -2, -2, -2] -hates -1.9 0.7 [-2, -1, -2, -2, -3, -1, -1, -2, -2, -3] -hating -2.3 1.1 [-4, -3, -4, -1, -2, -2, -1, -2, -1, -3] -hatred -3.2 0.9798 [-1, -3, -2, -4, -3, -3, -4, -4, -4, -4] -haunt -1.7 1.00499 [-1, -1, -3, -1, -2, -2, -1, -4, -1, -1] -haunted -2.1 0.7 [-2, -2, -1, -3, -3, -2, -2, -3, -1, -2] -haunting -1.1 0.83066 [-3, 0, -2, -1, 0, -1, -1, -1, -1, -1] -haunts -1.0 1.41421 [0, -2, -2, -2, -2, -1, 2, -2, 1, -2] -havoc -2.9 0.7 [-2, -4, -4, -3, -2, -3, -3, -3, -2, -3] -healthy 1.7 0.9 [1, 3, 1, 1, 3, 3, 1, 2, 1, 1] -heartbreak -2.7 0.78102 [-1, -3, -3, -3, -2, -4, -2, -3, -3, -3] -heartbreaker -2.2 1.07703 [-2, -3, 0, -3, -2, -1, -4, -3, -2, -2] -heartbreakers -2.1 0.9434 [-3, -2, -3, -2, -1, -1, -4, -1, -2, -2] -heartbreaking -2.0 1.73205 [-3, -1, -3, -3, -4, 2, -3, -2, 0, -3] -heartbreakingly -1.8 2.08806 [-3, 3, 1, -3, -3, -2, -3, -3, -4, -1] -heartbreaks -1.8 1.77764 [-2, 1, -3, -2, -3, -2, -3, 2, -4, -2] -heartbroken -3.3 0.45826 [-4, -3, -3, -4, -3, -3, -4, -3, -3, -3] -heartfelt 2.5 0.5 [3, 3, 2, 3, 2, 2, 3, 2, 2, 3] -heartless -2.2 0.74833 [-2, -2, -2, -4, -2, -1, -2, -3, -2, -2] -heartlessly -2.8 0.6 [-3, -2, -3, -3, -2, -3, -4, -2, -3, -3] -heartlessness -2.8 0.87178 [-3, -3, -2, -3, -4, -4, -1, -3, -2, -3] -heartwarming 2.1 1.22066 [3, 2, 3, 3, 2, 2, 3, 3, -1, 1] -heaven 2.3 1.18743 [1, 1, 2, 4, 3, 3, 3, 4, 1, 1] -heavenlier 3.0 0.63246 [3, 2, 3, 3, 4, 3, 3, 4, 2, 3] -heavenliest 2.7 1.1 [3, 2, 3, 4, 2, 4, 3, 0, 3, 3] -heavenliness 2.7 0.9 [3, 2, 1, 4, 3, 2, 3, 4, 3, 2] -heavenlinesses 2.3 2.2383 [4, 4, 4, 3, -2, 3, 3, 4, -2, 2] -heavenly 3.0 0.63246 [3, 3, 3, 3, 2, 3, 3, 4, 2, 4] -heavens 1.7 1.18743 [4, 0, 1, 2, 0, 3, 2, 2, 2, 1] -heavenward 1.4 1.35647 [0, 3, 0, 4, 1, 2, 2, 0, 2, 0] -heavenwards 1.2 1.32665 [1, 4, 0, 0, 2, 1, 1, 0, 3, 0] -heavyhearted -2.1 0.83066 [-2, -3, -3, -2, -3, -1, -1, -1, -2, -3] -heh -0.6 1.28062 [0, 1, -1, 1, -1, -2, -1, -3, 1, -1] -hell -3.6 0.66332 [-4, -4, -4, -4, -4, -2, -3, -4, -3, -4] -hellish -3.2 0.74833 [-3, -3, -2, -2, -4, -3, -4, -4, -3, -4] -help 1.7 0.78102 [3, 2, 1, 2, 1, 2, 3, 1, 1, 1] -helper 1.4 0.8 [1, 1, 0, 1, 1, 2, 1, 2, 3, 2] -helpers 1.1 0.83066 [1, 1, 0, 2, 1, 1, 1, 1, 3, 0] -helpful 1.8 0.87178 [2, 1, 3, 1, 1, 3, 1, 2, 3, 1] -helpfully 2.3 0.9 [1, 2, 2, 3, 2, 3, 3, 2, 4, 1] -helpfulness 1.9 1.13578 [1, 4, 1, 2, 2, 1, 1, 2, 4, 1] -helping 1.2 0.6 [2, 1, 1, 2, 0, 1, 1, 1, 2, 1] -helpless -2.0 0.63246 [-2, -3, -2, -2, -2, -3, -1, -2, -1, -2] -helplessly -1.4 0.4899 [-1, -1, -2, -2, -1, -1, -1, -2, -2, -1] -helplessness -2.1 0.9434 [-2, -4, -1, -2, -1, -3, -3, -2, -1, -2] -helplessnesses -1.7 0.64031 [-2, -1, -2, -1, -2, -1, -3, -2, -1, -2] -helps 1.6 0.4899 [1, 1, 1, 2, 2, 2, 1, 2, 2, 2] -hero 2.6 0.8 [2, 3, 2, 2, 4, 4, 2, 3, 2, 2] -heroes 2.3 0.9 [3, 4, 3, 1, 3, 2, 1, 2, 2, 2] -heroic 2.6 0.8 [3, 3, 1, 4, 2, 3, 2, 3, 2, 3] -heroical 2.9 1.04403 [4, 4, 2, 4, 2, 3, 1, 4, 2, 3] -heroically 2.4 0.8 [2, 2, 2, 3, 3, 3, 4, 1, 2, 2] -heroicomic 1.0 1.0 [1, 0, 1, 0, 2, 0, 3, 1, 2, 0] -heroicomical 1.1 0.83066 [2, 0, 0, 2, 1, 2, 1, 2, 1, 0] -heroics 2.4 0.8 [2, 1, 2, 2, 2, 3, 3, 3, 4, 2] -heroin -2.2 1.83303 [0, -2, -4, 2, -4, -2, -2, -3, -3, -4] -heroine 2.7 1.1 [0, 2, 4, 4, 3, 3, 3, 3, 2, 3] -heroines 1.8 1.32665 [2, 1, 1, 4, 3, 1, 0, 3, 3, 0] -heroinism -2.0 2.0 [-3, -4, 2, -2, -4, -3, -2, -1, 1, -4] -heroism 2.8 0.6 [3, 3, 4, 3, 2, 2, 3, 3, 2, 3] -heroisms 2.2 0.87178 [3, 1, 2, 4, 3, 2, 2, 2, 1, 2] -heroize 2.1 0.7 [3, 2, 3, 1, 2, 2, 2, 3, 1, 2] -heroized 2.0 1.18322 [1, 0, 3, 3, 2, 0, 3, 3, 2, 3] -heroizes 2.2 0.9798 [1, 3, 2, 3, 4, 3, 2, 1, 2, 1] -heroizing 1.9 1.64012 [2, 3, -2, 2, 4, 3, 2, 2, 3, 0] -heron 0.1 0.3 [0, 0, 0, 0, 0, 1, 0, 0, 0, 0] -heronries 0.7 1.1 [2, 0, 0, 0, 2, 0, 3, 0, 0, 0] -heronry 0.1 0.9434 [0, 0, 0, 0, 0, 2, 0, 1, -2, 0] -herons 0.5 1.0247 [0, 0, 0, 3, 0, 2, 0, 0, 0, 0] -heros 1.3 1.18743 [3, 0, 0, 2, 0, 2, 2, 3, 1, 0] -hesitance -0.9 0.3 [-1, -1, 0, -1, -1, -1, -1, -1, -1, -1] -hesitancies -1.0 0.63246 [-1, -1, -1, -2, -1, -1, -2, 0, 0, -1] -hesitancy -0.9 0.53852 [0, -1, 0, -2, -1, -1, -1, -1, -1, -1] -hesitant -1.0 0.7746 [0, -1, 0, -1, -2, 0, -1, -2, -1, -2] -hesitantly -1.2 0.4 [-1, -1, -2, -1, -1, -1, -1, -2, -1, -1] -hesitate -1.1 0.53852 [-2, -1, -1, -1, -2, -1, -1, 0, -1, -1] -hesitated -1.3 0.9 [-1, -2, -1, -2, -2, -2, -1, 1, -1, -2] -hesitater -1.4 0.66332 [-1, -1, -1, -1, -1, -2, -1, -3, -2, -1] -hesitaters -1.4 0.4899 [-1, -2, -1, -1, -1, -1, -2, -2, -2, -1] -hesitates -1.4 0.4899 [-1, -1, -1, -2, -1, -2, -1, -2, -2, -1] -hesitating -1.4 0.66332 [-1, -1, -2, -1, -1, -3, -2, -1, -1, -1] -hesitatingly -1.5 0.80623 [-1, -1, -1, -1, -3, -2, -3, -1, -1, -1] -hesitation -1.1 0.53852 [-2, 0, -1, -1, -1, -1, -1, -2, -1, -1] -hesitations -1.1 0.53852 [-1, -1, -1, 0, -2, -1, -1, -2, -1, -1] -hid -0.4 0.4899 [0, -1, 0, 0, -1, -1, -1, 0, 0, 0] -hide -0.7 0.64031 [0, -1, -1, -1, -1, 0, 0, -2, -1, 0] -hides -0.7 0.9 [-1, -2, -1, 0, -1, 0, 0, -2, 1, -1] -hiding -1.2 0.4 [-1, -1, -2, -1, -1, -1, -1, -1, -2, -1] -highlight 1.4 0.91652 [3, 0, 1, 1, 2, 1, 0, 2, 2, 2] -hilarious 1.7 1.41774 [2, 2, 2, 3, 3, 1, -2, 2, 3, 1] -hindrance -1.7 0.78102 [-2, -3, -2, -1, -1, -1, -3, -1, -2, -1] -hoax -1.1 1.04403 [-3, -1, -2, -1, 1, -2, -1, -1, -1, 0] -holiday 1.7 1.18743 [1, 3, 2, 2, 0, 0, 1, 2, 4, 2] -holidays 1.6 1.0198 [2, 0, 1, 2, 3, 0, 1, 2, 3, 2] -homesick -0.7 1.67631 [-2, -1, -1, -2, -1, -2, 2, -1, 3, -2] -homesickness -1.8 1.249 [-3, -2, -1, -1, -3, -2, -1, 1, -3, -3] -homesicknesses -1.8 0.6 [-1, -2, -2, -2, -1, -2, -1, -2, -3, -2] -honest 2.3 0.9 [3, 2, 1, 2, 3, 1, 2, 3, 2, 4] -honester 1.9 0.7 [2, 3, 2, 2, 1, 3, 1, 1, 2, 2] -honestest 3.0 0.7746 [1, 3, 3, 3, 3, 3, 4, 4, 3, 3] -honesties 1.8 1.07703 [4, 3, 1, 1, 1, 1, 3, 2, 1, 1] -honestly 2.0 0.63246 [2, 3, 2, 2, 1, 2, 2, 1, 3, 2] -honesty 2.2 0.6 [2, 3, 2, 2, 1, 2, 3, 2, 3, 2] -honor 2.2 1.16619 [3, 2, 1, 2, 0, 4, 3, 1, 3, 3] -honorability 2.2 0.4 [3, 3, 2, 2, 2, 2, 2, 2, 2, 2] -honorable 2.5 0.67082 [2, 2, 3, 2, 4, 3, 2, 2, 2, 3] -honorableness 2.2 0.87178 [2, 4, 1, 3, 3, 2, 1, 2, 2, 2] -honorably 2.4 0.66332 [2, 2, 3, 2, 3, 3, 3, 1, 2, 3] -honoraria 0.6 0.8 [1, 0, 1, 0, 0, 0, 2, 0, 2, 0] -honoraries 1.5 1.5 [2, 2, 1, 3, 3, 1, -2, 2, 3, 0] -honorarily 1.9 0.7 [2, 2, 3, 1, 2, 1, 2, 1, 3, 2] -honorarium 0.7 1.48661 [3, 2, -1, 2, 1, -2, 1, 1, -1, 1] -honorariums 1.0 1.0 [0, 0, 0, 0, 1, 2, 1, 3, 2, 1] -honorary 1.4 0.91652 [2, 2, 2, 3, 1, 1, 0, 1, 2, 0] -honored 2.8 0.87178 [3, 4, 4, 3, 1, 2, 2, 3, 3, 3] -honoree 2.1 0.7 [3, 2, 3, 3, 1, 2, 1, 2, 2, 2] -honorees 2.3 0.78102 [1, 3, 3, 4, 2, 2, 2, 2, 2, 2] -honorer 1.7 0.78102 [2, 1, 3, 3, 1, 2, 1, 2, 1, 1] -honorers 1.3 0.45826 [1, 1, 2, 2, 1, 1, 2, 1, 1, 1] -honorific 1.4 1.2 [2, 2, 2, 2, 2, 1, 2, 1, 2, -2] -honorifically 2.2 0.74833 [3, 4, 1, 2, 2, 2, 2, 2, 2, 2] -honorifics 1.7 0.78102 [1, 2, 0, 1, 2, 2, 2, 3, 2, 2] -honoring 2.3 0.64031 [3, 3, 1, 2, 2, 3, 3, 2, 2, 2] -honors 2.3 0.64031 [3, 2, 2, 2, 1, 3, 3, 2, 3, 2] -honour 2.7 0.78102 [2, 3, 2, 2, 2, 3, 4, 4, 3, 2] -honourable 2.1 0.53852 [2, 3, 2, 2, 2, 1, 3, 2, 2, 2] -honoured 2.2 1.249 [3, 3, 4, 3, -1, 2, 2, 2, 2, 2] -honourer 1.8 0.87178 [2, 3, 2, 1, 2, 3, 1, 0, 2, 2] -honourers 1.6 1.0198 [0, 2, 2, 1, 2, 2, 1, 3, 0, 3] -honouring 2.1 0.3 [2, 2, 2, 3, 2, 2, 2, 2, 2, 2] -honours 2.2 0.87178 [4, 3, 2, 2, 3, 2, 2, 1, 2, 1] -hooligan -1.5 0.5 [-1, -2, -1, -2, -2, -2, -1, -1, -2, -1] -hooliganism -2.1 0.83066 [-3, -2, -3, -3, -2, -2, -2, -2, 0, -2] -hooligans -1.1 1.22066 [-2, -1, -1, 2, -1, -1, -1, -3, -2, -1] -hooray 2.3 0.9 [3, 2, 3, 2, 1, 3, 1, 2, 2, 4] -hope 1.9 0.53852 [3, 2, 2, 1, 2, 2, 1, 2, 2, 2] -hoped 1.6 0.4899 [1, 2, 1, 1, 2, 2, 1, 2, 2, 2] -hopeful 2.3 0.78102 [2, 1, 1, 3, 3, 3, 2, 3, 2, 3] -hopefully 1.7 0.78102 [1, 3, 1, 3, 1, 2, 1, 1, 2, 2] -hopefulness 1.6 1.35647 [2, 1, -2, 2, 3, 2, 1, 3, 2, 2] -hopeless -2.0 1.78885 [-3, -3, -3, -3, 3, -1, -3, -3, -2, -2] -hopelessly -2.2 0.74833 [-3, -4, -2, -2, -1, -2, -2, -2, -2, -2] -hopelessness -3.1 0.7 [-3, -4, -4, -3, -3, -3, -4, -3, -2, -2] -hopes 1.8 0.6 [1, 3, 1, 2, 2, 2, 1, 2, 2, 2] -hoping 1.8 0.4 [2, 2, 2, 1, 2, 2, 2, 2, 2, 1] -horrendous -2.8 0.87178 [-3, -3, -4, -4, -3, -3, -2, -2, -1, -3] -horrendously -1.9 1.92094 [-3, -2, -4, -4, 2, -1, -3, -2, 1, -3] -horrent -0.9 1.04403 [0, -1, -2, 0, 0, -3, -1, 0, -2, 0] -horrible -2.5 0.67082 [-2, -2, -3, -2, -2, -4, -3, -3, -2, -2] -horribleness -2.4 0.4899 [-3, -3, -2, -2, -3, -2, -2, -3, -2, -2] -horribles -2.1 0.7 [-2, -4, -2, -2, -1, -2, -2, -2, -2, -2] -horribly -2.4 0.66332 [-2, -2, -2, -2, -2, -4, -3, -3, -2, -2] -horrid -2.5 1.0247 [-2, -3, -3, -4, -4, -1, -2, -2, -3, -1] -horridly -1.4 1.49666 [-2, 0, -3, -2, 0, -3, 2, -2, -2, -2] -horridness -2.3 1.26886 [-3, -3, -2, 1, -3, -3, -3, -3, -1, -3] -horridnesses -3.0 1.09545 [-2, -3, -4, -4, -4, -4, -2, -2, -1, -4] -horrific -3.4 0.91652 [-2, -4, -4, -4, -2, -4, -2, -4, -4, -4] -horrifically -2.9 0.7 [-2, -3, -2, -4, -2, -4, -3, -3, -3, -3] -horrified -2.5 0.92195 [-2, -3, -2, -2, -1, -4, -2, -2, -3, -4] -horrifies -2.9 1.22066 [-1, -3, -2, -1, -4, -4, -4, -4, -2, -4] -horrify -2.5 0.67082 [-2, -2, -3, -2, -2, -2, -4, -2, -3, -3] -horrifying -2.7 0.9 [-3, -4, -3, -2, -3, -3, -4, -2, -2, -1] -horrifyingly -3.3 0.9 [-3, -3, -4, -4, -1, -4, -3, -3, -4, -4] -horror -2.7 1.1 [-3, -1, -4, -4, -4, -3, -1, -2, -3, -2] -horrors -2.7 0.64031 [-3, -3, -4, -3, -2, -2, -2, -3, -2, -3] -hostile -1.6 1.74356 [-4, -3, -3, -1, 1, -2, 2, -2, -2, -2] -hostilely -2.2 0.6 [-1, -3, -3, -2, -2, -2, -2, -2, -2, -3] -hostiles -1.3 1.9 [-3, -3, -3, -3, -1, 2, -3, -1, 1, 1] -hostilities -2.1 0.53852 [-2, -3, -2, -2, -2, -2, -1, -2, -3, -2] -hostility -2.5 0.80623 [-2, -2, -3, -3, -3, -2, -4, -2, -3, -1] -huckster -0.9 0.7 [-1, 0, -1, 0, -1, -2, -2, 0, -1, -1] -hug 2.1 1.04403 [1, 3, 2, 1, 1, 2, 3, 3, 1, 4] -huge 1.3 0.9 [0, 2, 2, 0, 0, 2, 2, 2, 1, 2] -huggable 1.6 0.66332 [2, 2, 1, 1, 1, 3, 1, 2, 2, 1] -hugged 1.7 0.78102 [2, 2, 2, 2, 3, 1, 1, 2, 0, 2] -hugger 1.6 0.91652 [3, 2, 2, 2, 3, 1, 1, 1, 0, 1] -huggers 1.8 0.6 [1, 3, 1, 2, 1, 2, 2, 2, 2, 2] -hugging 1.8 0.74833 [2, 1, 1, 3, 3, 2, 2, 1, 2, 1] -hugs 2.2 0.74833 [3, 2, 1, 2, 2, 2, 3, 1, 3, 3] -humerous 1.4 1.11355 [-1, 2, 2, 3, 1, 1, 2, 0, 2, 2] -humiliate -2.5 1.28452 [-3, -3, -3, -3, -2, -2, -4, -3, 1, -3] -humiliated -1.4 2.498 [3, -3, -4, -3, -3, -4, -3, 0, 1, 2] -humiliates -1.0 2.09762 [1, -2, -3, -3, -3, -2, -3, 1, 2, 2] -humiliating -1.2 1.8868 [-4, -1, -3, -1, 2, -1, 2, -3, -2, -1] -humiliatingly -2.6 0.4899 [-3, -3, -2, -2, -3, -3, -3, -3, -2, -2] -humiliation -2.7 0.78102 [-2, -3, -4, -2, -2, -2, -3, -2, -4, -3] -humiliations -2.4 0.66332 [-3, -2, -2, -2, -2, -2, -2, -3, -2, -4] -humor 1.1 0.53852 [1, 0, 2, 2, 1, 1, 1, 1, 1, 1] -humoral 0.6 1.0198 [2, 0, 0, 0, 0, 0, 3, 1, 0, 0] -humored 1.2 0.87178 [1, 1, 2, 2, 1, 1, 2, 1, 2, -1] -humoresque 1.2 0.6 [1, 1, 1, 2, 1, 2, 2, 1, 1, 0] -humoresques 0.9 1.04403 [1, 0, 2, 0, 0, 1, 2, 0, 3, 0] -humoring 2.1 0.7 [3, 2, 2, 2, 1, 2, 2, 1, 3, 3] -humorist 1.2 0.74833 [1, 2, 1, 1, 2, 1, 2, 0, 0, 2] -humoristic 1.5 0.80623 [3, 0, 2, 1, 2, 1, 2, 2, 1, 1] -humorists 1.3 0.78102 [2, 1, 1, 1, 0, 1, 2, 3, 1, 1] -humorless -1.3 0.45826 [-1, -2, -1, -1, -1, -1, -2, -1, -1, -2] -humorlessness -1.4 1.11355 [1, -3, -3, -1, -1, -2, -1, -1, -2, -1] -humorous 1.6 0.4899 [1, 2, 1, 2, 2, 1, 2, 2, 1, 2] -humorously 2.3 0.78102 [3, 3, 2, 2, 1, 3, 3, 1, 2, 3] -humorousness 2.4 0.66332 [1, 2, 3, 2, 3, 2, 3, 3, 2, 3] -humors 1.6 0.4899 [2, 1, 2, 2, 2, 2, 1, 2, 1, 1] -humour 2.1 0.9434 [1, 2, 2, 4, 2, 1, 1, 3, 3, 2] -humoured 1.1 0.53852 [1, 0, 1, 2, 2, 1, 1, 1, 1, 1] -humouring 1.7 0.78102 [2, 3, 1, 2, 1, 0, 2, 2, 2, 2] -humourous 2.0 0.7746 [1, 2, 3, 2, 2, 3, 3, 2, 1, 1] -hunger -1.0 1.67332 [-4, 0, 2, -2, -1, -2, 1, -2, 0, -2] -hurrah 2.6 0.8 [3, 2, 3, 3, 1, 3, 4, 2, 2, 3] -hurrahed 1.9 0.53852 [2, 2, 1, 1, 2, 2, 3, 2, 2, 2] -hurrahing 2.4 0.4899 [3, 2, 2, 2, 3, 2, 3, 3, 2, 2] -hurrahs 2.1 1.44568 [2, 3, 0, 3, 2, 3, -1, 2, 3, 4] -hurray 2.7 0.78102 [3, 2, 3, 3, 1, 3, 4, 2, 3, 3] -hurrayed 1.8 1.32665 [3, 3, 2, 3, 3, 3, 0, 0, 1, 0] -hurraying 1.2 1.66132 [2, -3, 2, 3, 0, 2, 2, 2, 0, 2] -hurrays 2.4 1.11355 [2, 3, 2, 4, 0, 3, 2, 2, 2, 4] -hurt -2.4 0.8 [-3, -3, -2, -2, -4, -3, -2, -1, -2, -2] -hurter -2.3 0.78102 [-2, -4, -1, -2, -3, -3, -2, -2, -2, -2] -hurters -1.9 1.04403 [-2, -3, -1, -2, -1, 0, -3, -3, -3, -1] -hurtful -2.4 1.0198 [-2, -4, -2, -2, -1, -3, -2, -3, -1, -4] -hurtfully -2.6 0.66332 [-3, -2, -3, -2, -2, -3, -4, -3, -2, -2] -hurtfulness -1.9 1.51327 [2, -2, -2, -2, -3, -1, -2, -3, -4, -2] -hurting -1.7 0.78102 [-3, -1, -1, -2, -1, -1, -3, -2, -2, -1] -hurtle -0.3 1.1 [-2, 1, 0, -1, -1, -1, 0, 2, 0, -1] -hurtled -0.6 0.8 [0, -2, 0, 0, 0, 0, -1, -1, -2, 0] -hurtles -1.0 0.63246 [-1, -2, 0, 0, -1, -1, -1, -1, -2, -1] -hurtless 0.3 1.55242 [-1, -3, 2, 1, 2, 1, 0, 0, -1, 2] -hurtling -1.4 0.8 [-3, -2, -1, -1, -1, -1, -1, -2, 0, -2] -hurts -2.1 0.83066 [-4, -2, -2, -2, -3, -1, -2, -2, -2, -1] -hypocritical -2.0 0.89443 [-4, -2, -1, -3, -2, -1, -2, -1, -2, -2] -hysteria -1.9 0.7 [-1, -3, -1, -2, -2, -2, -2, -2, -1, -3] -hysterical -0.1 1.97231 [2, 0, 0, 3, -2, -2, 3, -1, -2, -2] -hysterics -1.8 1.77764 [-3, -3, -3, -1, -3, -1, -2, 3, -3, -2] -ideal 2.4 1.2 [4, 3, 4, 4, 2, 2, 1, 2, 1, 1] -idealess -1.9 1.3 [-4, -2, -3, -2, -1, 0, -4, -1, -1, -1] -idealise 1.4 0.91652 [2, 2, 1, 0, 1, 3, 2, 0, 1, 2] -idealised 2.1 0.83066 [1, 4, 1, 3, 2, 2, 2, 2, 2, 2] -idealises 2.0 0.89443 [1, 4, 1, 2, 2, 2, 2, 3, 1, 2] -idealising 0.6 0.4899 [0, 1, 1, 1, 1, 1, 1, 0, 0, 0] -idealism 1.7 1.1 [1, 2, 0, 3, 3, 2, 1, 2, 3, 0] -idealisms 0.8 0.9798 [0, 2, 3, 1, 0, 0, 1, 0, 0, 1] -idealist 1.6 1.56205 [2, 3, -2, 1, 3, 3, 1, 0, 2, 3] -idealistic 1.8 0.9798 [2, 1, 0, 2, 4, 2, 2, 2, 1, 2] -idealistically 1.7 1.1 [0, 3, 3, 1, 2, 3, 0, 2, 1, 2] -idealists 0.7 1.1 [0, -2, 1, 2, 1, 1, 2, 0, 1, 1] -idealities 1.5 0.67082 [2, 1, 1, 2, 1, 0, 2, 2, 2, 2] -ideality 1.9 0.9434 [0, 1, 2, 3, 2, 1, 2, 3, 3, 2] -idealization 1.8 0.9798 [2, 2, 2, 1, 4, 2, 2, 0, 1, 2] -idealizations 1.4 0.66332 [2, 1, 1, 2, 1, 2, 1, 0, 2, 2] -idealize 1.2 0.9798 [1, 2, 2, 0, 0, 1, 3, 0, 2, 1] -idealized 1.8 0.74833 [2, 3, 1, 1, 2, 1, 3, 1, 2, 2] -idealizer 1.3 0.9 [1, 1, 1, 1, 1, 3, 0, 1, 3, 1] -idealizers 1.9 1.37477 [1, 4, 1, 2, 0, 2, 3, 2, 4, 0] -idealizes 2.0 1.0 [3, 2, 2, 1, 4, 2, 2, 0, 2, 2] -idealizing 1.4 1.0198 [1, 1, 2, 3, 0, 1, 3, 0, 2, 1] -idealless -1.7 1.00499 [-2, -2, -2, -2, -4, -1, 0, -1, -2, -1] -ideally 1.8 1.16619 [1, 0, 2, 2, 3, 2, 4, 0, 2, 2] -idealogues 0.5 0.92195 [1, 0, -1, 2, 0, 0, 2, 0, 1, 0] -idealogy 0.8 1.16619 [0, 3, 1, 0, 2, 0, 0, 1, 2, -1] -ideals 0.8 0.6 [0, 1, 0, 2, 1, 1, 1, 0, 1, 1] -idiot -2.3 0.64031 [-2, -3, -1, -3, -2, -3, -3, -2, -2, -2] -idiotic -2.6 0.91652 [-3, -4, -2, -3, -2, -2, -4, -1, -3, -2] -ignorable -1.0 0.63246 [-1, -1, -1, -2, 0, -1, 0, -1, -2, -1] -ignorami -1.9 0.83066 [-2, -2, -3, -2, 0, -1, -2, -2, -3, -2] -ignoramus -1.9 0.83066 [-1, -2, -1, -3, -1, -3, -1, -3, -2, -2] -ignoramuses -2.3 1.1 [-2, -2, -3, -4, 0, -1, -3, -2, -3, -3] -ignorance -1.5 1.20416 [-2, -2, -3, -2, 0, -2, -1, -3, -1, 1] -ignorances -1.2 0.9798 [0, -1, -2, -1, -2, -2, -1, 1, -2, -2] -ignorant -1.1 0.83066 [-1, -1, -1, -2, 1, -2, -1, -2, -1, -1] -ignorantly -1.6 0.91652 [-1, -2, -2, -2, -2, -2, -2, 1, -2, -2] -ignorantness -1.1 1.44568 [3, -1, -2, -1, -1, -2, -2, -2, -1, -2] -ignore -1.5 0.67082 [-1, -2, -1, -1, -1, -1, -2, -3, -2, -1] -ignored -1.3 0.45826 [-2, -1, -2, -1, -1, -2, -1, -1, -1, -1] -ignorer -1.3 0.45826 [-1, -1, -2, -1, -2, -1, -1, -1, -2, -1] -ignorers -0.7 1.00499 [-1, -2, -1, -1, -1, 1, 0, -2, 1, -1] -ignores -1.1 0.3 [-1, -1, -2, -1, -1, -1, -1, -1, -1, -1] -ignoring -1.7 0.64031 [-1, -1, -1, -2, -2, -3, -2, -1, -2, -2] -ill -1.8 0.9798 [-2, 0, -2, -1, -4, -2, -2, -2, -1, -2] -illegal -2.6 0.8 [-3, -4, -3, -2, -1, -2, -3, -3, -2, -3] -illiteracy -1.9 0.7 [-2, -1, -2, -2, -3, -2, -1, -2, -1, -3] -illness -1.7 0.64031 [-2, -1, -2, -2, -3, -2, -1, -2, -1, -1] -illnesses -2.2 0.74833 [-2, -2, -2, -4, -2, -3, -2, -1, -2, -2] -imbecile -2.2 0.9798 [-3, -2, -3, -3, -3, -1, -3, 0, -2, -2] -immobilized -1.2 0.87178 [-1, -3, 0, -1, -1, 0, -2, -1, -2, -1] -immoral -2.0 1.09545 [-4, -1, -1, -3, -2, -3, -3, -1, -1, -1] -immoralism -1.6 0.91652 [-2, -2, -2, -2, 1, -2, -2, -2, -1, -2] -immoralist -2.1 0.3 [-2, -2, -3, -2, -2, -2, -2, -2, -2, -2] -immoralists -1.7 0.78102 [-2, -2, -2, -3, -1, -1, -1, -1, -3, -1] -immoralities -1.1 1.51327 [-2, -1, -4, -3, 1, 1, -1, 0, -1, -1] -immorality -0.6 2.2891 [3, -3, 1, 2, 2, -2, -4, -1, -2, -2] -immorally -2.1 0.7 [-1, -1, -2, -2, -3, -2, -3, -2, -2, -3] -immortal 1.0 1.73205 [3, 3, 2, 2, -2, -2, 2, 1, 1, 0] -immune 1.2 0.74833 [2, 2, 0, 1, 2, 1, 2, 1, 1, 0] -impatience -1.8 0.4 [-2, -2, -1, -2, -2, -2, -2, -1, -2, -2] -impatiens -0.2 0.6 [0, 0, -1, 0, 0, 0, 1, -1, -1, 0] -impatient -1.2 0.4 [-1, -1, -1, -1, -1, -1, -2, -1, -1, -2] -impatiently -1.7 0.64031 [-1, -1, -2, -3, -1, -2, -1, -2, -2, -2] -imperfect -1.3 0.64031 [-1, -1, -1, -1, -1, -2, -3, -1, -1, -1] -impersonal -1.3 0.45826 [-2, -2, -1, -1, -2, -1, -1, -1, -1, -1] -impolite -1.6 0.66332 [-2, -1, -3, -1, -1, -1, -1, -2, -2, -2] -impolitely -1.8 0.6 [-2, -2, -1, -1, -2, -1, -2, -2, -3, -2] -impoliteness -1.8 0.87178 [-1, -3, -2, -3, -2, -3, -1, -1, -1, -1] -impolitenesses -2.3 0.78102 [-3, -2, -2, -1, -1, -3, -3, -2, -3, -3] -importance 1.5 0.80623 [2, 1, 2, 3, 1, 2, 1, 0, 2, 1] -importancies 0.4 1.42829 [0, 0, 1, 2, 0, 0, 2, 2, 0, -3] -importancy 1.4 0.66332 [2, 1, 2, 2, 1, 2, 1, 0, 2, 1] -important 0.8 1.07703 [0, 0, 0, 2, 1, 0, 0, 3, 2, 0] -importantly 1.3 0.78102 [2, 1, 2, 1, 2, 2, 0, 0, 1, 2] -impose -1.2 0.4 [-1, -1, -1, -1, -2, -1, -2, -1, -1, -1] -imposed -0.3 1.41774 [2, -1, -1, -1, 1, 0, -2, 2, -2, -1] -imposes -0.4 1.42829 [-2, -1, 1, -2, -1, -1, -2, 1, 2, 1] -imposing -0.4 1.0198 [1, -1, -2, -1, 1, 1, 0, -1, -1, -1] -impotent -1.1 0.3 [-1, -1, -1, -2, -1, -1, -1, -1, -1, -1] -impress 1.9 0.53852 [2, 2, 1, 2, 2, 2, 2, 1, 2, 3] -impressed 2.1 0.3 [2, 2, 2, 2, 2, 2, 3, 2, 2, 2] -impresses 2.1 0.3 [2, 2, 2, 2, 2, 2, 3, 2, 2, 2] -impressibility 1.2 1.249 [-1, 2, 0, 2, 0, 2, 2, 3, 2, 0] -impressible 0.8 1.16619 [2, -1, 1, 0, -1, 2, 1, 0, 2, 2] -impressing 2.5 0.92195 [3, 4, 1, 2, 3, 2, 3, 1, 3, 3] -impression 0.9 0.9434 [0, 1, 0, 0, 2, 2, 0, 2, 0, 2] -impressionable 0.2 1.07703 [0, 0, -1, 1, -1, -1, 0, 2, 0, 2] -impressionism 0.8 1.07703 [0, 2, 3, 0, 0, 2, 0, 0, 1, 0] -impressionisms 0.5 0.80623 [0, 0, 0, 0, 0, 2, 0, 1, 0, 2] -impressionist 1.0 1.09545 [0, 2, 3, 0, 0, 2, 2, 0, 1, 0] -impressionistic 1.5 1.20416 [2, 2, 0, 0, 1, 0, 2, 2, 4, 2] -impressionistically 1.6 0.8 [2, 0, 1, 1, 2, 2, 3, 2, 2, 1] -impressionists 0.5 1.43178 [2, 0, 0, 1, 1, 2, -2, 2, 1, -2] -impressions 0.9 1.13578 [2, 0, 0, 3, 0, 2, 0, 2, 0, 0] -impressive 2.3 0.78102 [1, 2, 3, 2, 3, 2, 3, 3, 3, 1] -impressively 2.0 0.89443 [3, 1, 1, 2, 2, 2, 2, 4, 2, 1] -impressiveness 1.7 0.64031 [2, 1, 2, 3, 1, 2, 2, 2, 1, 1] -impressment -0.4 1.85472 [-2, 1, 3, -2, -1, -3, 0, 0, 2, -2] -impressments 0.5 1.20416 [2, 0, 0, 1, 2, 2, 0, -2, 0, 0] -impressure 0.6 1.0198 [-1, 0, 0, 0, 0, 2, 0, 2, 1, 2] -imprisoned -2.0 1.0 [-4, -2, -3, -1, -3, -2, -1, -2, -1, -1] -improve 1.9 0.7 [2, 3, 3, 2, 1, 1, 2, 2, 1, 2] -improved 2.1 0.7 [3, 1, 2, 3, 2, 3, 1, 2, 2, 2] -improvement 2.0 0.63246 [2, 3, 3, 2, 1, 1, 2, 2, 2, 2] -improvements 1.3 0.64031 [0, 2, 2, 1, 2, 2, 1, 1, 1, 1] -improver 1.8 0.6 [2, 1, 2, 1, 2, 3, 1, 2, 2, 2] -improvers 1.3 0.78102 [1, 2, 2, 1, 2, 2, 0, 0, 1, 2] -improves 1.8 1.07703 [3, -1, 2, 2, 2, 3, 1, 2, 2, 2] -improving 1.8 0.4 [2, 2, 1, 1, 2, 2, 2, 2, 2, 2] -inability -1.7 0.9 [-2, -2, -3, 0, -2, -3, -2, -1, -1, -1] -inaction -1.0 0.63246 [-2, -1, 0, -1, -1, 0, -1, -2, -1, -1] -inadequacies -1.7 0.64031 [-1, -3, -2, -1, -2, -1, -2, -2, -1, -2] -inadequacy -1.7 0.78102 [-1, -3, -1, -1, -3, -2, -2, -1, -2, -1] -inadequate -1.7 0.64031 [-2, -1, -1, -3, -1, -1, -2, -2, -2, -2] -inadequately -1.0 1.26491 [-3, -1, -1, -2, 2, -1, -2, -1, 0, -1] -inadequateness -1.7 0.45826 [-2, -2, -1, -1, -1, -2, -2, -2, -2, -2] -inadequatenesses -1.6 0.91652 [-1, -1, -2, -1, -2, -4, -2, -1, -1, -1] -incapable -1.6 0.4899 [-1, -2, -1, -1, -2, -1, -2, -2, -2, -2] -incapacitated -1.9 0.9434 [-2, -2, -1, -1, -2, -4, -1, -1, -2, -3] -incensed -2.0 1.0 [-2, -1, -4, 0, -2, -2, -2, -3, -2, -2] -incentive 1.5 1.0247 [1, 2, 1, 2, 1, 0, 4, 2, 1, 1] -incentives 1.3 1.34536 [2, 2, 1, 1, 3, 1, -2, 3, 1, 1] -incompetence -2.3 0.45826 [-3, -2, -2, -3, -2, -3, -2, -2, -2, -2] -incompetent -2.1 0.83066 [-1, -1, -2, -2, -3, -3, -2, -3, -1, -3] -inconsiderate -1.9 0.7 [-2, -1, -1, -1, -2, -2, -2, -3, -3, -2] -inconvenience -1.5 0.5 [-1, -2, -1, -1, -1, -2, -2, -1, -2, -2] -inconvenient -1.4 0.4899 [-2, -2, -1, -2, -1, -2, -1, -1, -1, -1] -increase 1.3 0.64031 [1, 2, 2, 1, 2, 0, 1, 1, 2, 1] -increased 1.1 1.04403 [2, 0, 3, 2, 2, 1, 0, 1, 0, 0] -indecision -0.8 0.6 [-1, 0, -1, 0, -1, -1, -2, 0, -1, -1] -indecisions -1.1 0.53852 [-1, -1, -1, -1, -2, -1, -2, -1, 0, -1] -indecisive -1.0 0.44721 [0, -1, -1, -1, -1, -2, -1, -1, -1, -1] -indecisively -0.7 1.18743 [-2, -1, -1, -1, -1, -1, -2, 2, 1, -1] -indecisiveness -1.3 0.64031 [-1, -3, -1, -2, -1, -1, -1, -1, -1, -1] -indecisivenesses -0.9 0.53852 [-1, -1, 0, -1, -1, 0, -1, -2, -1, -1] -indestructible 0.6 1.85472 [3, 4, -1, -2, 1, 1, 2, 0, -1, -1] -indifference -0.2 0.74833 [0, -1, 0, 0, 0, 1, -2, 0, 0, 0] -indifferent -0.8 0.6 [-1, 0, 0, -1, -2, -1, -1, 0, -1, -1] -indignant -1.8 0.74833 [-1, -3, -2, -2, -2, -1, -1, -1, -3, -2] -indignation -2.4 0.8 [-2, -1, -2, -3, -3, -3, -1, -3, -3, -3] -indoctrinate -1.4 0.91652 [-1, -3, -1, 0, -2, -1, -2, -2, 0, -2] -indoctrinated -0.4 1.35647 [1, -2, -3, 1, -1, 1, 1, -1, -1, 0] -indoctrinates -0.6 1.2 [1, -1, -3, 1, -1, 1, -1, -1, -1, -1] -indoctrinating -0.7 1.41774 [-1, 0, -3, -1, -2, -1, 2, -2, 0, 1] -ineffective -0.5 1.74642 [-2, -1, -1, -1, -2, 2, -2, 1, 3, -2] -ineffectively -1.3 0.9 [-2, -2, -2, 1, -1, -1, -1, -2, -1, -2] -ineffectiveness -1.3 0.45826 [-1, -1, -2, -1, -1, -2, -1, -1, -2, -1] -ineffectual -1.2 0.4 [-1, -1, -1, -1, -1, -1, -1, -2, -2, -1] -ineffectuality -1.6 0.66332 [-2, -1, -1, -1, -2, -1, -3, -2, -2, -1] -ineffectually -1.1 0.9434 [-1, -2, -2, -1, 0, -1, -2, -1, 1, -2] -ineffectualness -1.3 0.45826 [-2, -1, -1, -1, -1, -2, -1, -1, -2, -1] -infatuated 0.2 1.72047 [3, 2, 0, 3, -1, -1, -2, 0, -1, -1] -infatuation 0.6 1.74356 [1, -1, -1, 2, -1, 1, 4, 2, 1, -2] -infected -2.2 0.6 [-3, -2, -2, -2, -2, -2, -3, -1, -2, -3] -inferior -1.7 0.78102 [-1, -2, -2, -1, -1, -3, -2, -1, -1, -3] -inferiorities -1.9 0.7 [-2, -3, -1, -2, -2, -3, -1, -1, -2, -2] -inferiority -1.1 1.7 [-2, -3, -2, -2, -2, -3, 2, 1, -1, 1] -inferiorly -2.0 0.63246 [-3, -2, -2, -2, -2, -3, -1, -2, -1, -2] -inferiors -0.5 1.43178 [-1, -1, -1, -2, -1, 0, 3, -1, 1, -2] -inflamed -1.4 1.28062 [-2, -2, -1, -2, -2, -1, 2, -3, -2, -1] -influential 1.9 1.04403 [3, 1, 2, 3, 4, 1, 1, 2, 1, 1] -infringement -2.1 0.83066 [-3, -1, -2, -1, -2, -1, -3, -3, -2, -3] -infuriate -2.2 0.87178 [-2, -1, -3, -3, -2, -3, -3, -1, -1, -3] -infuriated -3.0 0.7746 [-1, -4, -3, -3, -3, -3, -3, -3, -3, -4] -infuriates -2.6 0.8 [-4, -2, -1, -3, -3, -3, -2, -3, -3, -2] -infuriating -2.4 1.42829 [-1, -3, -3, -3, -3, -4, 0, 0, -4, -3] -inhibin -0.2 0.4 [-1, 0, 0, 0, 0, 0, 0, 0, -1, 0] -inhibit -1.6 0.4899 [-1, -2, -1, -2, -1, -2, -2, -2, -1, -2] -inhibited -0.4 0.4899 [0, 0, -1, 0, -1, -1, 0, -1, 0, 0] -inhibiting -0.4 1.42829 [1, -1, -1, -1, -2, -1, 2, -2, 2, -1] -inhibition -1.5 0.67082 [-1, -1, -1, -1, -2, -1, -1, -2, -2, -3] -inhibitions -0.8 0.74833 [-2, -1, -2, 0, 0, 0, 0, -1, -1, -1] -inhibitive -1.4 0.4899 [-2, -2, -1, -1, -2, -1, -2, -1, -1, -1] -inhibitor -0.3 1.00499 [-2, 1, 1, -1, 1, 0, -1, -1, 0, -1] -inhibitors -1.0 0.7746 [-1, 0, -2, -1, -2, -2, 0, 0, -1, -1] -inhibitory -1.0 0.7746 [0, -1, -2, -2, -1, -2, 0, 0, -1, -1] -inhibits -0.9 0.53852 [-1, -1, -2, -1, -1, 0, -1, -1, -1, 0] -injured -1.7 0.64031 [-2, -1, -1, -1, -2, -1, -2, -2, -3, -2] -injury -1.8 0.6 [-2, -2, -1, -2, -1, -1, -2, -3, -2, -2] -injustice -2.7 0.64031 [-3, -2, -3, -4, -3, -3, -2, -2, -3, -2] -innocence 1.6 0.91652 [3, 1, 1, 1, 2, 2, 0, 3, 2, 1] -innocency 1.9 0.83066 [3, 1, 2, 0, 2, 2, 2, 3, 2, 2] -innocent 1.4 1.2 [1, -1, 2, 2, 2, 0, 1, 3, 3, 1] -innocenter 0.9 1.37477 [1, 1, 1, 2, 2, 1, 1, -3, 1, 2] -innocently 1.4 0.8 [0, 2, 1, 1, 1, 1, 3, 2, 2, 1] -innocents 1.1 1.04403 [0, 0, 2, 2, 2, -1, 1, 1, 2, 2] -innovate 2.2 0.74833 [2, 4, 3, 2, 2, 1, 2, 2, 2, 2] -innovates 2.0 0.89443 [2, 2, 2, 0, 1, 3, 3, 2, 3, 2] -innovation 1.6 0.91652 [1, 0, 3, 2, 1, 2, 3, 2, 1, 1] -innovative 1.9 0.83066 [1, 1, 2, 1, 2, 4, 2, 2, 2, 2] -inquisition -1.2 1.249 [-2, 1, -1, 0, 0, -3, -1, -3, -2, -1] -inquisitive 0.7 1.18743 [2, 1, 1, 2, -2, -1, 1, 1, 1, 1] -insane -1.7 0.78102 [-2, 0, -2, -1, -2, -3, -2, -2, -1, -2] -insanity -2.7 1.00499 [-2, -4, -1, -1, -3, -4, -3, -3, -3, -3] -insecure -1.8 0.74833 [-1, -2, -2, -1, -3, -2, -3, -2, -1, -1] -insecurely -1.4 0.66332 [-3, -1, -1, -1, -2, -1, -2, -1, -1, -1] -insecureness -1.8 0.87178 [-1, -1, -1, -3, -3, -3, -2, -2, -1, -1] -insecurities -1.8 0.6 [-3, -2, -2, -2, -1, -2, -1, -1, -2, -2] -insecurity -1.8 0.74833 [-2, -2, -2, -1, -3, -3, -2, -1, -1, -1] -insensitive -0.9 1.81384 [2, -3, -2, -1, 2, -3, -2, 1, -1, -2] -insensitivity -1.8 0.6 [-2, -2, -1, -3, -2, -2, -1, -2, -1, -2] -insignificant -1.4 0.8 [-3, -2, -1, -2, -1, -2, 0, -1, -1, -1] -insincere -1.8 0.6 [-2, -1, -2, -1, -2, -2, -2, -2, -1, -3] -insincerely -1.9 0.7 [-2, -1, -2, -2, -1, -3, -2, -3, -1, -2] -insincerity -1.4 1.35647 [-1, -1, -3, -2, -1, 2, -2, -1, -2, -3] -insipid -2.0 0.7746 [-1, -2, -2, -1, -3, -3, -3, -2, -2, -1] -inspiration 2.4 0.8 [3, 3, 3, 3, 1, 3, 1, 3, 2, 2] -inspirational 2.3 0.64031 [2, 3, 2, 3, 2, 3, 2, 3, 1, 2] -inspirationally 2.3 0.64031 [3, 2, 2, 3, 3, 1, 2, 2, 3, 2] -inspirations 2.1 0.53852 [2, 2, 2, 2, 1, 2, 2, 3, 3, 2] -inspirator 1.9 1.22066 [2, 2, 3, 0, 3, 4, 0, 2, 1, 2] -inspirators 1.2 0.74833 [3, 1, 1, 2, 1, 1, 1, 1, 0, 1] -inspiratory 1.5 0.67082 [2, 2, 3, 1, 1, 1, 1, 1, 2, 1] -inspire 2.7 0.78102 [2, 3, 3, 3, 3, 3, 3, 1, 4, 2] -inspired 2.2 0.87178 [3, 2, 1, 3, 1, 1, 3, 2, 3, 3] -inspirer 2.2 1.07703 [3, 2, 2, 4, 0, 2, 3, 1, 3, 2] -inspirers 2.0 0.63246 [2, 2, 3, 2, 3, 2, 1, 2, 1, 2] -inspires 1.9 1.04403 [2, 2, 2, 4, 0, 2, 3, 1, 1, 2] -inspiring 1.8 1.07703 [2, 2, 2, -1, 2, 3, 2, 2, 1, 3] -inspiringly 2.6 0.4899 [2, 3, 3, 2, 3, 3, 2, 3, 2, 3] -inspirit 1.9 0.7 [1, 3, 2, 1, 2, 1, 3, 2, 2, 2] -inspirited 1.3 1.18743 [2, 2, 0, 0, 3, 0, 2, 0, 3, 1] -inspiriting 1.8 0.4 [1, 2, 1, 2, 2, 2, 2, 2, 2, 2] -inspiritingly 2.1 1.44568 [3, 2, 2, 2, 4, 1, -1, 3, 4, 1] -inspirits 0.8 1.46969 [3, 0, 3, -2, 0, 1, 1, 0, 2, 0] -insult -2.3 1.00499 [-2, -1, -2, -3, -4, -1, -3, -1, -3, -3] -insulted -2.3 0.45826 [-2, -2, -2, -2, -3, -2, -2, -2, -3, -3] -insulter -2.0 0.63246 [-2, -1, -2, -2, -1, -3, -3, -2, -2, -2] -insulters -2.0 0.44721 [-2, -3, -2, -2, -2, -2, -2, -1, -2, -2] -insulting -2.2 0.74833 [-3, -2, -3, -3, -2, -3, -1, -2, -2, -1] -insultingly -2.3 0.78102 [-3, -3, -1, -2, -2, -3, -2, -1, -3, -3] -insults -1.8 0.6 [-2, -3, -2, -2, -1, -1, -1, -2, -2, -2] -intact 0.8 0.6 [1, 1, 0, 0, 1, 1, 0, 1, 1, 2] -integrity 1.6 0.66332 [2, 1, 1, 1, 2, 1, 3, 1, 2, 2] -intellect 2.0 1.09545 [2, 1, 4, 2, 1, 3, 2, 3, 0, 2] -intellection 0.6 1.0198 [0, 0, 0, 1, 0, 0, 0, 0, 2, 3] -intellections 0.8 0.87178 [1, 0, 1, 0, 1, 1, 1, 0, 0, 3] -intellective 1.7 0.78102 [3, 2, 1, 2, 2, 1, 0, 2, 2, 2] -intellectively 0.8 0.9798 [0, 0, 1, 1, 0, 3, 0, 1, 2, 0] -intellects 1.8 0.87178 [1, 0, 2, 1, 3, 2, 2, 2, 3, 2] -intellectual 2.3 0.9 [3, 3, 1, 2, 3, 4, 2, 2, 1, 2] -intellectualism 2.2 1.07703 [4, 0, 3, 1, 3, 2, 2, 3, 2, 2] -intellectualist 2.0 1.0 [4, 0, 2, 1, 3, 2, 2, 2, 2, 2] -intellectualistic 1.3 1.73494 [1, 4, 0, 3, -2, 0, 2, 3, 0, 2] -intellectualists 0.8 0.74833 [0, 1, 1, 1, 0, 2, 0, 1, 2, 0] -intellectualities 1.7 1.34536 [3, 3, 0, 2, 1, 0, 0, 4, 2, 2] -intellectuality 1.7 1.1 [3, 2, 2, 1, 2, 1, 0, 3, 0, 3] -intellectualization 1.5 1.11803 [2, 1, 2, 1, 4, 2, 0, 0, 2, 1] -intellectualize 1.5 0.92195 [1, 2, 1, 1, 3, 2, 3, 0, 1, 1] -intellectualized 1.2 0.74833 [1, 0, 1, 1, 2, 0, 1, 2, 2, 2] -intellectualizes 1.8 0.87178 [2, 3, 2, 0, 2, 3, 2, 2, 1, 1] -intellectualizing 0.8 1.77764 [0, 1, 2, 1, 0, 2, 2, -4, 2, 2] -intellectually 1.4 0.8 [2, 0, 0, 1, 2, 2, 2, 2, 2, 1] -intellectualness 1.5 0.80623 [2, 2, 2, 2, 0, 0, 1, 2, 2, 2] -intellectuals 1.6 0.8 [0, 1, 2, 1, 3, 2, 1, 2, 2, 2] -intelligence 2.1 0.9434 [3, 2, 2, 1, 3, 3, 3, 2, 2, 0] -intelligencer 1.5 0.80623 [2, 0, 0, 2, 2, 2, 2, 1, 2, 2] -intelligencers 1.6 0.91652 [2, 2, 0, 2, 2, 0, 3, 2, 2, 1] -intelligences 1.6 0.91652 [3, 0, 0, 2, 2, 2, 2, 1, 2, 2] -intelligent 2.0 0.7746 [1, 2, 2, 1, 4, 2, 2, 2, 2, 2] -intelligential 1.9 0.9434 [3, 2, 2, 1, 3, 2, 2, 3, 0, 1] -intelligently 2.0 0.63246 [2, 3, 2, 3, 1, 2, 2, 1, 2, 2] -intelligentsia 1.5 1.20416 [0, 1, 2, 0, 4, 3, 2, 1, 1, 1] -intelligibility 1.5 0.80623 [2, 2, 0, 2, 2, 1, 2, 0, 2, 2] -intelligible 1.4 0.8 [1, 2, 2, 1, 0, 2, 1, 1, 3, 1] -intelligibleness 1.5 1.20416 [2, 1, 3, -1, 2, 2, 2, 0, 1, 3] -intelligibly 1.2 0.87178 [1, 2, 1, 2, 1, -1, 2, 2, 1, 1] -intense 0.3 0.45826 [0, 1, 1, 0, 0, 0, 0, 0, 1, 0] -interest 2.0 1.18322 [2, 3, 3, 1, 1, 3, 4, 1, 2, 0] -interested 1.7 0.45826 [2, 1, 2, 2, 1, 2, 2, 2, 1, 2] -interestedly 1.5 0.67082 [2, 2, 2, 1, 2, 1, 2, 1, 0, 2] -interesting 1.7 0.78102 [1, 2, 1, 3, 1, 1, 1, 3, 2, 2] -interestingly 1.7 0.45826 [2, 2, 2, 1, 2, 1, 1, 2, 2, 2] -interestingness 1.8 0.87178 [2, 3, 1, 3, 1, 3, 2, 1, 1, 1] -interests 1.0 0.89443 [1, 0, 1, 2, 0, 0, 1, 1, 1, 3] -interrogated -1.6 1.0198 [-3, -1, -1, -1, -2, -1, -3, -1, -3, 0] -interrupt -1.4 0.4899 [-2, -1, -1, -1, -2, -2, -1, -1, -2, -1] -interrupted -1.2 0.6 [-1, -2, -1, 0, -1, -1, -2, -1, -2, -1] -interrupter -1.1 0.53852 [-1, -2, -1, 0, -1, -1, -1, -1, -2, -1] -interrupters -1.3 0.45826 [-1, -2, -1, -1, -1, -1, -2, -1, -2, -1] -interruptible -1.3 1.00499 [-2, -1, 0, -2, 0, -3, -2, -1, 0, -2] -interrupting -1.2 0.4 [-2, -1, -1, -1, -1, -2, -1, -1, -1, -1] -interruption -1.5 0.67082 [-1, -1, -2, -3, -2, -1, -1, -1, -2, -1] -interruptions -1.7 0.45826 [-2, -2, -2, -2, -2, -1, -1, -1, -2, -2] -interruptive -1.4 0.66332 [-2, -2, -1, -2, -2, 0, -1, -1, -1, -2] -interruptor -1.3 0.64031 [-2, -1, -1, -1, 0, -2, -2, -2, -1, -1] -interrupts -1.3 0.64031 [-1, -1, -2, -1, -1, -1, -1, -1, -3, -1] -intimidate -0.8 1.46969 [-1, -2, -2, -2, -2, -1, 2, 1, 1, -2] -intimidated -1.9 0.7 [-2, -1, -3, -3, -1, -2, -2, -1, -2, -2] -intimidates -1.3 0.78102 [-2, -1, -1, -1, -3, -2, -1, -1, -1, 0] -intimidating -1.9 1.04403 [0, -2, -1, -3, -2, -1, -1, -3, -3, -3] -intimidatingly -1.1 1.64012 [2, -2, -3, -1, -2, -2, 2, -2, -1, -2] -intimidation -1.8 1.249 [1, -2, -3, -1, -2, -3, -1, -3, -1, -3] -intimidations -1.4 1.49666 [1, -2, -2, -2, -1, -1, -1, -4, 1, -3] -intimidator -1.6 0.4899 [-1, -1, -2, -2, -1, -2, -2, -1, -2, -2] -intimidators -1.6 0.8 [-1, -1, -3, -2, -1, -1, -3, -1, -2, -1] -intimidatory -1.1 1.22066 [-1, -2, -3, -1, -1, -1, -2, 2, -1, -1] -intricate 0.6 0.66332 [1, 0, 2, 1, 0, 1, 1, 0, 0, 0] -intrigues 0.9 0.9434 [2, -1, 2, 1, 2, 0, 1, 1, 0, 1] -invigorate 1.9 0.83066 [2, 2, 2, 0, 2, 3, 3, 2, 1, 2] -invigorated 0.8 1.8868 [-2, 3, 2, 2, -2, -2, 2, 2, 1, 2] -invigorates 2.1 0.53852 [3, 2, 3, 2, 1, 2, 2, 2, 2, 2] -invigorating 2.1 0.7 [2, 1, 1, 3, 3, 3, 2, 2, 2, 2] -invigoratingly 2.0 0.63246 [2, 2, 1, 2, 1, 3, 2, 2, 2, 3] -invigoration 1.5 1.36015 [2, 2, 1, -2, 1, 3, 3, 2, 1, 2] -invigorations 1.2 0.87178 [1, -1, 2, 2, 1, 1, 2, 1, 2, 1] -invigorator 1.1 1.3 [3, 1, 0, 2, 2, -2, 1, 1, 2, 1] -invigorators 1.2 0.87178 [1, 1, 1, 1, 3, 2, 0, 0, 1, 2] -invincible 2.2 1.77764 [4, 1, 3, 2, 4, 1, 4, -1, 0, 4] -invite 0.6 0.66332 [2, 1, 1, 0, 0, 0, 0, 1, 1, 0] -inviting 1.3 0.45826 [1, 1, 1, 2, 1, 2, 2, 1, 1, 1] -invulnerable 1.3 1.73494 [2, 3, 4, 2, 0, 3, 0, 1, -2, 0] -irate -2.9 0.53852 [-3, -3, -3, -2, -3, -4, -3, -3, -2, -3] -ironic -0.5 1.28452 [1, 0, 0, 0, 0, 0, -4, -1, -1, 0] -irony -0.2 1.07703 [-1, 0, -3, 0, 0, 0, 1, 0, 1, 0] -irrational -1.4 0.4899 [-1, -1, -1, -2, -2, -2, -1, -1, -2, -1] -irrationalism -1.5 0.5 [-1, -2, -1, -1, -2, -1, -2, -2, -1, -2] -irrationalist -2.1 0.9434 [-1, -4, -2, -2, -3, -3, -2, -1, -1, -2] -irrationalists -1.5 0.92195 [-2, -2, -1, -2, -2, 1, -1, -2, -2, -2] -irrationalities -1.5 0.80623 [-2, -2, 0, -1, -1, -1, -2, -3, -1, -2] -irrationality -1.7 0.9 [-3, -3, -1, -2, -1, -1, -1, -1, -3, -1] -irrationally -1.6 0.4899 [-1, -2, -1, -2, -1, -2, -2, -2, -1, -2] -irrationals -1.1 0.83066 [-2, 0, -1, 0, -1, -1, -3, -1, -1, -1] -irresistible 1.4 2.2 [2, 3, 2, 3, 4, 4, 1, -1, -2, -2] -irresolute -1.4 0.66332 [-2, -2, -1, -2, -1, -1, -1, -2, -2, 0] -irresponsible -1.9 0.3 [-2, -2, -2, -2, -2, -2, -1, -2, -2, -2] -irreversible -0.8 0.87178 [-2, -2, 0, -1, 0, 0, 0, -1, -2, 0] -irritabilities -1.7 0.64031 [-2, -2, -2, -1, -1, -1, -1, -2, -3, -2] -irritability -1.4 1.28062 [-2, -1, -2, -1, 2, -2, -2, -2, -1, -3] -irritable -2.1 0.7 [-2, -2, -3, -1, -2, -1, -3, -2, -3, -2] -irritableness -1.7 0.64031 [-2, -2, -2, -1, -2, -1, -1, -3, -1, -2] -irritably -1.8 0.6 [-2, -2, -1, -1, -3, -2, -1, -2, -2, -2] -irritant -2.3 0.78102 [-3, -3, -3, -3, -3, -1, -2, -2, -2, -1] -irritants -2.1 0.83066 [-2, -3, -1, -4, -2, -1, -2, -2, -2, -2] -irritate -1.8 0.6 [-3, -2, -2, -2, -1, -2, -1, -2, -1, -2] -irritated -2.0 0.63246 [-1, -2, -2, -2, -3, -2, -2, -3, -1, -2] -irritates -1.7 0.78102 [-1, -2, -1, -1, -3, -2, -2, -3, -1, -1] -irritating -2.0 0.63246 [-2, -2, -2, -1, -1, -3, -2, -2, -3, -2] -irritatingly -2.0 0.44721 [-2, -2, -2, -3, -1, -2, -2, -2, -2, -2] -irritation -2.3 0.78102 [-3, -2, -2, -2, -1, -3, -3, -1, -3, -3] -irritations -1.5 0.67082 [-2, -2, -1, -1, -1, -1, -1, -2, -3, -1] -irritative -2.0 0.63246 [-3, -2, -3, -2, -1, -2, -2, -2, -1, -2] -isolatable 0.2 1.249 [1, 0, -2, 0, -1, -1, 2, 0, 2, 1] -isolate -0.8 0.74833 [-1, -1, -1, 0, 0, 0, 0, -2, -1, -2] -isolated -1.3 0.64031 [-1, -1, -1, -1, -1, -1, -2, -1, -3, -1] -isolates -1.3 0.64031 [-1, -1, -1, -1, -2, -1, -3, -1, -1, -1] -isolation -1.7 0.78102 [-1, -3, -1, -2, -2, -1, -3, -1, -2, -1] -isolationism 0.4 1.62481 [2, 0, -1, -2, -1, 3, 0, 2, -1, 2] -isolationist 0.7 1.55242 [2, 0, 0, -1, -1, 3, 0, 2, -1, 3] -isolations -0.5 1.11803 [-1, -2, -2, -1, 1, 1, -1, 0, 1, -1] -isolator -0.4 0.66332 [0, 0, -1, 0, -1, 0, -2, 0, 0, 0] -isolators -0.4 1.42829 [-2, -1, -1, -2, 2, 2, -1, 1, -1, -1] -itchy -1.1 0.53852 [-1, -1, -1, -1, -2, 0, -1, -1, -2, -1] -jackass -1.8 1.07703 [-1, 0, -3, -2, -2, -3, 0, -2, -2, -3] -jackasses -2.8 0.9798 [-2, -2, -4, -3, -4, -4, -3, -1, -2, -3] -jaded -1.6 0.66332 [-1, -1, -1, -2, -2, -1, -2, -2, -1, -3] -jailed -2.2 0.87178 [-4, -3, -2, -2, -1, -2, -2, -3, -1, -2] -jaunty 1.2 0.6 [2, 1, 0, 2, 1, 1, 1, 2, 1, 1] -jealous -2.0 0.63246 [-2, -2, -3, -2, -3, -2, -1, -1, -2, -2] -jealousies -2.0 0.63246 [-2, -3, -2, -1, -2, -3, -2, -1, -2, -2] -jealously -2.0 0.89443 [-1, -3, -1, -4, -2, -2, -1, -2, -2, -2] -jealousness -1.7 0.45826 [-1, -2, -2, -2, -2, -1, -1, -2, -2, -2] -jealousy -1.3 1.73494 [-2, -3, -2, -2, -2, 2, -3, -1, 2, -2] -jeopardy -2.1 0.9434 [-3, -3, -3, -1, -1, -3, -2, -1, -1, -3] -jerk -1.4 0.8 [-1, -1, -1, -2, -3, 0, -2, -1, -1, -2] -jerked -0.8 0.74833 [0, -1, -1, 0, -2, -1, 0, -1, 0, -2] -jerks -1.1 1.51327 [-2, -2, -1, -2, -1, 0, -2, 3, -2, -2] -jewel 1.5 1.20416 [1, 3, 2, 0, 2, 1, 3, 0, 3, 0] -jewels 2.0 1.34164 [3, 1, 0, 0, 4, 3, 3, 2, 3, 1] -jocular 1.2 1.249 [0, 1, 2, -2, 1, 2, 2, 2, 2, 2] -join 1.2 0.74833 [2, 2, 1, 2, 1, 0, 1, 2, 0, 1] -joke 1.2 0.74833 [1, 1, 1, 1, 1, 1, 0, 2, 1, 3] -joked 1.3 0.64031 [1, 1, 2, 2, 0, 2, 1, 1, 2, 1] -joker 0.5 0.92195 [1, 1, -1, 1, 2, -1, 1, 1, 0, 0] -jokes 1.0 0.7746 [1, 1, -1, 1, 1, 2, 1, 1, 2, 1] -jokester 1.5 0.67082 [2, 2, 2, 2, 1, 1, 0, 1, 2, 2] -jokesters 0.9 0.83066 [0, 0, 2, 1, 1, 2, 2, 0, 1, 0] -jokey 1.1 0.3 [1, 1, 2, 1, 1, 1, 1, 1, 1, 1] -joking 0.9 0.53852 [1, 2, 1, 1, 1, 0, 1, 1, 0, 1] -jollied 2.4 0.66332 [3, 3, 2, 2, 3, 3, 2, 2, 1, 3] -jollier 2.4 0.4899 [2, 2, 3, 3, 2, 2, 2, 3, 2, 3] -jollies 2.0 0.63246 [1, 2, 3, 2, 2, 2, 1, 2, 2, 3] -jolliest 2.9 0.7 [3, 3, 2, 4, 3, 2, 3, 4, 2, 3] -jollification 2.2 0.74833 [2, 3, 3, 1, 2, 1, 3, 2, 3, 2] -jollifications 2.0 0.7746 [2, 3, 2, 2, 2, 2, 3, 2, 0, 2] -jollify 2.1 0.53852 [2, 3, 2, 2, 2, 2, 2, 3, 1, 2] -jollily 2.7 0.64031 [3, 3, 3, 3, 3, 3, 3, 1, 3, 2] -jolliness 2.5 0.67082 [3, 1, 2, 3, 2, 3, 3, 3, 2, 3] -jollities 1.7 0.64031 [2, 1, 2, 2, 1, 2, 2, 3, 1, 1] -jollity 1.8 1.6 [3, 2, 1, 1, 4, 3, 1, 2, 3, -2] -jolly 2.3 1.00499 [4, 3, 3, 1, 1, 1, 3, 2, 3, 2] -jollying 2.3 0.64031 [2, 3, 3, 1, 3, 3, 2, 2, 2, 2] -jovial 1.9 0.53852 [2, 2, 1, 2, 1, 2, 3, 2, 2, 2] -joy 2.8 0.74833 [3, 2, 3, 4, 3, 3, 3, 1, 3, 3] -joyance 2.3 0.9 [1, 3, 4, 2, 2, 1, 2, 3, 2, 3] -joyed 2.9 0.3 [3, 3, 3, 3, 3, 3, 3, 2, 3, 3] -joyful 2.9 0.53852 [3, 2, 3, 3, 2, 3, 4, 3, 3, 3] -joyfuller 2.4 0.66332 [2, 4, 3, 2, 2, 2, 3, 2, 2, 2] -joyfully 2.5 0.67082 [2, 2, 3, 3, 2, 2, 3, 4, 2, 2] -joyfulness 2.7 1.00499 [4, 3, 1, 3, 3, 3, 4, 2, 1, 3] -joying 2.5 0.67082 [2, 2, 1, 3, 3, 3, 3, 3, 3, 2] -joyless -2.5 0.67082 [-1, -2, -3, -3, -3, -3, -2, -2, -3, -3] -joylessly -1.7 1.1 [-2, -2, -3, -3, -2, -1, 1, -2, -1, -2] -joylessness -2.7 0.9 [-4, -3, -3, -3, -3, -3, -3, -1, -1, -3] -joyous 3.1 0.7 [3, 4, 3, 2, 4, 3, 3, 4, 2, 3] -joyously 2.9 0.7 [2, 3, 4, 3, 4, 2, 2, 3, 3, 3] -joyousness 2.8 0.74833 [3, 3, 1, 3, 3, 3, 4, 2, 3, 3] -joypop -0.2 1.93907 [-3, 1, 2, 2, -3, -1, -2, -1, 1, 2] -joypoppers -0.1 1.22066 [2, -1, 1, -1, -1, 1, 1, 0, -2, -1] -joyridden 0.6 1.8 [-2, -1, 4, 0, 0, 2, 1, -1, 0, 3] -joyride 1.1 1.22066 [-1, 1, 2, 0, 2, 0, 2, 2, 3, 0] -joyrider 0.7 1.26886 [2, -2, 1, 2, 0, 2, -1, 1, 1, 1] -joyriders 1.3 1.18743 [1, 0, 0, 1, 4, 3, 1, 1, 1, 1] -joyrides 0.8 1.32665 [2, -2, 1, 2, 0, 2, -1, 1, 2, 1] -joyriding 0.9 1.04403 [1, -1, 1, 1, 0, 2, 0, 1, 3, 1] -joyrode 1.0 1.48324 [4, 0, -2, 0, 2, 1, 2, 1, 1, 1] -joys 2.2 0.4 [2, 2, 2, 2, 2, 3, 2, 3, 2, 2] -joystick 0.7 0.78102 [1, 0, 2, 2, 0, 0, 1, 1, 0, 0] -joysticks 0.2 0.4 [0, 0, 0, 0, 1, 0, 0, 1, 0, 0] -jubilant 3.0 0.63246 [3, 3, 4, 3, 3, 2, 3, 4, 2, 3] -jumpy -1.0 0.63246 [0, 0, -2, -1, -1, -1, -1, -1, -2, -1] -justice 2.4 1.0198 [3, 2, 1, 2, 3, 2, 4, 4, 2, 1] -justifiably 1.0 0.7746 [0, 1, 0, 1, 1, 1, 0, 2, 2, 2] -justified 1.7 0.64031 [1, 2, 2, 3, 1, 1, 1, 2, 2, 2] -keen 1.5 0.67082 [1, 1, 3, 1, 2, 1, 1, 2, 2, 1] -keened 0.3 1.00499 [-2, 0, 1, 0, 1, 1, 0, 2, 0, 0] -keener 0.5 1.20416 [-1, -1, 0, -1, 2, 1, 2, 2, 1, 0] -keeners 0.6 0.4899 [1, 0, 0, 1, 1, 0, 1, 1, 0, 1] -keenest 1.9 0.83066 [3, 3, 1, 1, 3, 2, 2, 1, 2, 1] -keening -0.7 1.41774 [0, -3, -1, -1, -3, 1, -1, 1, 1, -1] -keenly 1.0 0.7746 [2, 1, 1, 0, 1, 0, 2, 1, 2, 0] -keenness 1.4 0.4899 [1, 1, 2, 2, 1, 1, 1, 2, 2, 1] -keens 0.1 1.22066 [1, -3, 0, 0, 0, 2, 1, 0, 0, 0] -kewl 1.3 0.45826 [2, 1, 1, 1, 2, 1, 2, 1, 1, 1] -kidding 0.4 0.8 [0, 1, 0, -1, 1, 1, 1, 1, -1, 1] -kill -3.7 0.45826 [-4, -4, -4, -4, -3, -4, -4, -4, -3, -3] -killdeer -1.1 1.04403 [-3, 0, 0, -1, -2, 0, -1, -2, -2, 0] -killdeers -0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 0, 0, -1] -killdees -0.6 0.66332 [-2, 0, 0, 0, -1, 0, -1, -1, -1, 0] -killed -3.5 0.67082 [-3, -3, -2, -4, -4, -4, -3, -4, -4, -4] -killer -3.3 0.64031 [-4, -4, -3, -3, -4, -4, -3, -3, -2, -3] -killers -3.3 0.45826 [-3, -3, -4, -3, -3, -3, -4, -3, -4, -3] -killick 0.1 0.3 [0, 1, 0, 0, 0, 0, 0, 0, 0, 0] -killie -0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 0, 0, -1] -killifish -0.1 0.7 [0, 0, 0, 0, -2, 0, 0, 0, 1, 0] -killifishes -0.1 0.3 [0, -1, 0, 0, 0, 0, 0, 0, 0, 0] -killing -3.4 1.2 [-4, 0, -4, -4, -4, -3, -4, -3, -4, -4] -killingly -2.6 1.0198 [-3, -2, -4, -2, -1, -3, -4, -3, -3, -1] -killings -3.5 0.67082 [-4, -3, -4, -4, -2, -3, -4, -4, -3, -4] -killjoy -2.1 0.83066 [-1, -2, -3, -2, -1, -3, -2, -1, -3, -3] -killjoys -1.7 0.9 [-1, -3, -3, -1, -2, -1, -2, 0, -2, -2] -killock -0.3 0.64031 [0, 0, 0, 0, -2, 0, 0, 0, -1, 0] -killocks -0.4 0.66332 [0, 0, 0, -2, -1, 0, -1, 0, 0, 0] -kills -2.5 0.92195 [-2, -3, -2, -3, -4, -1, -3, -3, -1, -3] -kind 2.4 0.66332 [2, 2, 3, 3, 2, 3, 3, 2, 1, 3] -kinder 2.2 0.6 [3, 3, 3, 2, 2, 2, 2, 1, 2, 2] -kindly 2.2 0.4 [2, 2, 2, 3, 2, 2, 2, 2, 2, 3] -kindness 2.0 0.63246 [2, 1, 3, 3, 2, 1, 2, 2, 2, 2] -kindnesses 2.3 0.64031 [3, 1, 3, 2, 3, 2, 3, 2, 2, 2] -kiss 1.8 1.6 [4, 0, 3, 3, 2, 0, 4, 2, 0, 0] -kissable 2.0 0.89443 [2, 2, 2, 2, 4, 2, 3, 1, 1, 1] -kissably 1.9 1.04403 [1, 3, 4, 1, 2, 1, 3, 2, 1, 1] -kissed 1.6 1.11355 [2, 4, 1, 1, 1, 2, 3, 0, 1, 1] -kisser 1.7 1.34536 [2, 4, 1, 2, -1, 2, 3, 0, 2, 2] -kissers 1.5 0.80623 [1, 1, 1, 0, 2, 2, 3, 2, 1, 2] -kisses 2.3 0.9 [2, 4, 2, 2, 1, 2, 4, 2, 2, 2] -kissing 2.7 0.78102 [3, 3, 4, 1, 3, 2, 2, 3, 3, 3] -kissy 1.8 0.6 [2, 2, 2, 3, 1, 1, 2, 2, 1, 2] -kudos 2.3 0.64031 [2, 4, 2, 3, 2, 2, 2, 2, 2, 2] -lack -1.3 0.45826 [-1, -1, -1, -1, -2, -1, -2, -1, -1, -2] -lackadaisical -1.6 0.66332 [-1, -1, -2, -1, -2, -2, -3, -1, -2, -1] -lag -1.4 0.66332 [-1, -1, -1, -1, -1, -3, -1, -2, -2, -1] -lagged -1.2 0.6 [-2, -2, -1, -2, -1, -1, 0, -1, -1, -1] -lagging -1.1 0.83066 [-2, -2, -2, -1, 0, 0, -1, 0, -1, -2] -lags -1.5 0.67082 [-2, -1, -1, -2, -1, -3, -1, -2, -1, -1] -laidback 0.5 1.28452 [1, -1, 1, -2, -1, 1, 2, 1, 1, 2] -lame -1.8 0.74833 [-1, -3, -1, -2, -2, -1, -2, -3, -1, -2] -lamebrain -1.6 0.91652 [-3, -2, -1, 0, -3, -1, -1, -2, -2, -1] -lamebrained -2.5 0.67082 [-3, -3, -2, -2, -2, -2, -4, -3, -2, -2] -lamebrains -1.2 1.46969 [-2, -1, -3, -1, 2, -2, 1, -2, -2, -2] -lamedh 0.1 0.53852 [0, 0, 0, 0, 0, 1, 1, -1, 0, 0] -lamella -0.1 0.3 [0, -1, 0, 0, 0, 0, 0, 0, 0, 0] -lamellae -0.1 0.3 [0, 0, 0, 0, 0, 0, -1, 0, 0, 0] -lamellas 0.1 0.53852 [0, 0, 0, 0, 0, 1, 0, 1, 0, -1] -lamellibranch 0.2 0.4 [0, 0, 0, 0, 0, 1, 0, 1, 0, 0] -lamellibranchs -0.1 0.3 [0, 0, -1, 0, 0, 0, 0, 0, 0, 0] -lamely -2.0 0.89443 [-2, -3, 0, -1, -2, -3, -2, -3, -2, -2] -lameness -0.8 1.07703 [-2, -2, -1, -1, -1, 0, 2, -1, -1, -1] -lament -2.0 1.26491 [-3, -3, 1, -1, -2, -2, -1, -3, -3, -3] -lamentable -1.5 1.0247 [-2, 0, -2, -1, 0, -2, -3, -1, -1, -3] -lamentableness -1.3 0.64031 [-2, -1, -1, 0, -2, -1, -1, -1, -2, -2] -lamentably -1.5 0.80623 [-2, 0, -3, -1, -1, -2, -2, -1, -1, -2] -lamentation -1.4 1.49666 [-3, -2, 0, -3, -1, -1, 2, -2, -1, -3] -lamentations -1.9 1.44568 [-2, -2, -2, -3, 2, -1, -3, -3, -2, -3] -lamented -1.4 0.91652 [-1, 0, -1, -2, -2, -1, -2, -3, -2, 0] -lamenter -1.2 0.87178 [-1, 0, -1, -1, -1, -1, -2, -3, -2, 0] -lamenters -0.5 0.67082 [-1, 0, 0, -1, -1, 0, 0, 0, -2, 0] -lamenting -2.0 1.09545 [0, -2, -1, -4, -1, -3, -2, -2, -3, -2] -laments -1.5 0.80623 [-1, -3, 0, -1, -2, -1, -2, -2, -2, -1] -lamer -1.4 0.4899 [-2, -1, -1, -2, -1, -1, -1, -2, -2, -1] -lames -1.2 0.6 [-2, -1, -1, -2, 0, -1, -1, -2, -1, -1] -lamest -1.5 1.28452 [-3, -2, -1, -4, 1, -1, -1, -1, -1, -2] -landmark 0.3 0.64031 [2, 0, 0, 0, 0, 0, 0, 0, 1, 0] -laugh 2.6 0.66332 [3, 2, 3, 1, 3, 3, 3, 3, 2, 3] -laughable 0.2 1.72047 [-2, -1, 3, -1, 2, 2, -1, -1, -1, 2] -laughableness 1.2 1.6 [2, 0, 3, 2, 2, 1, 3, -2, 2, -1] -laughably 1.2 1.249 [2, 1, 2, 1, 1, 1, 2, 3, -2, 1] -laughed 2.0 0.63246 [2, 2, 3, 1, 2, 1, 2, 2, 3, 2] -laugher 1.7 0.45826 [2, 2, 1, 1, 2, 1, 2, 2, 2, 2] -laughers 1.7 0.9 [1, 2, 4, 1, 2, 1, 2, 1, 1, 2] -laughing 2.2 0.87178 [2, 4, 1, 1, 3, 2, 2, 2, 2, 3] -laughingly 2.3 1.1 [2, 4, 0, 2, 3, 1, 3, 2, 3, 3] -laughings 1.9 0.7 [2, 1, 1, 1, 2, 3, 2, 2, 3, 2] -laughingstocks -1.3 1.26886 [-3, -2, 1, -2, -1, -1, 1, -2, -2, -2] -laughs 2.2 0.6 [1, 2, 2, 3, 3, 2, 3, 2, 2, 2] -laughter 2.2 0.6 [2, 3, 2, 2, 2, 2, 3, 1, 3, 2] -laughters 2.2 0.6 [3, 1, 2, 2, 2, 3, 3, 2, 2, 2] -launched 0.5 0.80623 [2, 0, 0, 0, 0, 0, 0, 1, 2, 0] -lawl 1.4 1.42829 [0, 2, 2, 1, 3, -2, 3, 1, 2, 2] -lawsuit -0.9 1.22066 [-2, -2, -1, -3, -1, 1, 0, 1, -1, -1] -lawsuits -0.6 1.68523 [-2, -1, 0, 3, 2, -1, -1, -2, -2, -2] -lazier -2.3 0.64031 [-3, -2, -3, -2, -1, -2, -2, -3, -2, -3] -laziest -2.7 0.64031 [-2, -2, -3, -4, -3, -3, -2, -2, -3, -3] -lazy -1.5 1.36015 [-3, -1, -3, -2, 2, -1, -1, -2, -2, -2] -leak -1.4 0.66332 [-1, -2, -1, -1, -1, -1, -1, -2, -3, -1] -leaked -1.3 0.78102 [-2, -2, -1, -3, -1, 0, -1, -1, -1, -1] -leave -0.2 0.9798 [1, -1, -1, 0, 0, -1, 2, -1, 0, -1] -leet 1.3 1.48661 [2, 4, 2, 2, 0, 1, -2, 2, 1, 1] -legal 0.5 0.80623 [0, 0, 0, 2, 0, 1, 0, 0, 2, 0] -legally 0.4 0.8 [1, 0, 0, 0, 1, 0, 2, 1, 0, -1] -lenient 1.1 1.04403 [1, 3, 1, 2, 1, 1, 2, -1, 0, 1] -lethargic -1.2 0.74833 [-2, -1, -2, -2, 0, -1, -1, -2, 0, -1] -lethargy -1.4 0.91652 [-1, 0, -2, -1, -2, 0, -2, -1, -3, -2] -liabilities -0.8 0.9798 [-1, 2, -1, -1, -1, -1, -1, -1, -2, -1] -liability -0.8 1.83303 [-2, -3, -1, -1, 3, -3, -1, -1, 2, -1] -liar -2.3 0.78102 [-1, -2, -3, -3, -2, -2, -3, -1, -3, -3] -liards -0.4 0.91652 [-2, 0, -1, 0, 0, 1, 0, 0, -2, 0] -liars -2.4 0.66332 [-3, -2, -2, -3, -2, -1, -3, -3, -2, -3] -libelous -2.1 1.3 [-3, -1, -1, -2, 1, -3, -3, -3, -3, -3] -libertarian 0.9 0.9434 [1, 2, 0, 1, 0, 0, 0, 3, 1, 1] -libertarianism 0.4 0.8 [0, 0, 2, 0, 2, 0, 0, 0, 0, 0] -libertarianisms 0.1 1.13578 [0, 0, 0, 2, 2, 0, -2, 0, -1, 0] -libertarians 0.1 0.83066 [0, 0, 1, 0, 0, -1, -1, 0, 2, 0] -liberties 2.3 0.78102 [2, 4, 3, 2, 2, 1, 2, 3, 2, 2] -libertinage 0.2 1.53623 [-1, -1, 0, 0, 4, 0, -2, 1, 1, 0] -libertine -0.9 1.44568 [0, -1, 0, 0, -1, -3, 2, -2, -1, -3] -libertines 0.4 1.35647 [-1, 3, -1, -1, 1, 1, 1, 2, 0, -1] -libertinisms 1.2 1.249 [0, 0, 3, 1, 1, 1, 4, 0, 1, 1] -liberty 2.4 0.91652 [2, 2, 3, 3, 3, 3, 2, 4, 1, 1] -lied -1.6 1.2 [-3, 0, -3, 1, -2, -1, -2, -2, -2, -2] -lies -1.8 0.9798 [-1, -1, -1, 0, -2, -3, -3, -2, -3, -2] -lifesaver 2.8 0.74833 [3, 3, 4, 2, 3, 1, 3, 3, 3, 3] -lighthearted 1.8 0.4 [2, 2, 2, 2, 1, 2, 2, 1, 2, 2] -like 1.5 0.67082 [1, 2, 2, 2, 1, 3, 1, 1, 1, 1] -likeable 2.0 0.63246 [1, 3, 2, 2, 2, 3, 2, 1, 2, 2] -liked 1.8 0.6 [2, 2, 1, 2, 2, 1, 3, 1, 2, 2] -likes 1.8 0.6 [2, 2, 1, 2, 2, 2, 3, 1, 1, 2] -liking 1.7 0.78102 [3, 1, 2, 1, 1, 2, 3, 1, 2, 1] -limitation -1.2 0.6 [-2, -1, 0, -1, -1, -2, -1, -2, -1, -1] -limited -0.9 0.53852 [-1, -1, 0, -2, -1, 0, -1, -1, -1, -1] -litigation -0.8 0.6 [0, -2, -1, 0, -1, -1, -1, -1, 0, -1] -litigious -0.8 0.9798 [-2, -1, 0, -2, 0, -2, 1, -1, 0, -1] -livelier 1.7 0.78102 [2, 2, 1, 3, 1, 3, 2, 1, 1, 1] -liveliest 2.1 0.9434 [2, 1, 2, 3, 1, 1, 2, 4, 3, 2] -livelihood 0.8 1.07703 [0, 3, 1, 0, 2, 2, 0, 0, 0, 0] -livelihoods 0.9 1.13578 [0, 0, 0, 3, 2, 2, 0, 2, 0, 0] -livelily 1.8 0.6 [2, 2, 2, 3, 1, 2, 1, 2, 2, 1] -liveliness 1.6 0.8 [1, 3, 0, 2, 2, 2, 2, 2, 1, 1] -livelong 1.7 0.78102 [3, 0, 1, 1, 2, 2, 2, 2, 2, 2] -lively 1.9 0.7 [2, 2, 3, 1, 1, 2, 3, 1, 2, 2] -livid -2.5 0.92195 [-2, -3, -1, -2, -4, -3, -1, -3, -3, -3] -lmao 2.9 0.9434 [3, 4, 3, 1, 2, 4, 3, 3, 2, 4] -loathe -2.2 2.08806 [-1, -4, -3, -2, -4, 2, 1, -3, -4, -4] -loathed -2.1 1.44568 [-4, -3, -3, -3, -1, 1, -1, -1, -3, -3] -loathes -1.9 1.13578 [-1, -4, -1, -3, -3, -1, -1, -3, -1, -1] -loathing -2.7 0.78102 [-3, -3, -3, -1, -4, -2, -3, -3, -2, -3] -lobby 0.1 0.53852 [0, 0, 0, 1, 0, 1, 0, -1, 0, 0] -lobbying -0.3 0.45826 [0, -1, 0, 0, 0, 0, 0, -1, -1, 0] -lol 1.8 1.46969 [1, 3, 4, 1, 2, 4, 1, 2, -1, 1] -lone -1.1 0.3 [-1, -1, -1, -1, -1, -1, -2, -1, -1, -1] -lonelier -1.4 0.66332 [-2, -1, -2, -2, 0, -2, -1, -1, -1, -2] -loneliest -2.4 0.8 [-3, -1, -2, -4, -2, -2, -3, -3, -2, -2] -loneliness -1.8 0.6 [-2, -2, -1, -3, -2, -2, -1, -2, -1, -2] -lonelinesses -1.5 1.36015 [-2, -2, -1, -1, 2, -1, -3, -2, -3, -2] -lonely -1.5 0.5 [-1, -2, -2, -1, -1, -1, -1, -2, -2, -2] -loneness -1.1 0.83066 [-1, -2, -1, -2, -1, -1, -2, 1, -1, -1] -loner -1.3 0.45826 [-1, -2, -1, -1, -1, -1, -1, -2, -2, -1] -loners -0.9 0.53852 [-1, -1, -2, -1, -1, -1, 0, 0, -1, -1] -lonesome -1.5 0.67082 [-2, -1, -2, -1, -2, -1, -2, 0, -2, -2] -lonesomely -1.3 1.00499 [-2, -2, -2, -2, -1, -2, 0, -2, -1, 1] -lonesomeness -1.8 0.6 [-2, -2, -1, -3, -1, -2, -2, -2, -1, -2] -lonesomes -1.4 0.4899 [-2, -1, -1, -1, -1, -1, -2, -2, -2, -1] -longing -0.1 0.9434 [0, -1, 0, -1, -1, 0, 2, -1, 1, 0] -longingly 0.7 0.45826 [1, 0, 1, 0, 1, 1, 1, 0, 1, 1] -longings 0.4 1.2 [2, 0, -1, -1, 0, 1, 3, 0, 0, 0] -loom -0.9 0.53852 [-1, -1, -1, -1, -1, -2, 0, -1, -1, 0] -loomed -1.1 1.04403 [-2, -2, -1, -1, -1, -1, 0, -1, -3, 1] -looming -0.5 1.5 [-2, -1, -1, 0, -2, -2, 3, -1, 0, 1] -looms -0.6 1.0198 [-1, -2, -1, -1, 0, 0, 1, -2, 1, -1] -loose -1.3 1.18743 [-2, -1, 0, -2, 0, -1, 0, -2, -4, -1] -looses -0.6 0.91652 [0, -1, 0, -1, 0, 0, 0, 0, -3, -1] -lose -1.7 0.45826 [-1, -2, -1, -2, -1, -2, -2, -2, -2, -2] -loser -2.4 0.66332 [-3, -2, -2, -2, -2, -3, -3, -1, -3, -3] -losers -2.4 0.8 [-3, -1, -2, -2, -4, -2, -3, -3, -2, -2] -loses -1.3 1.00499 [0, -1, -1, -1, -1, -4, -1, -1, -2, -1] -losing -1.6 0.8 [-1, -1, -1, -2, -1, -2, -3, -3, -1, -1] -loss -1.3 0.45826 [-1, -2, -1, -1, -1, -2, -2, -1, -1, -1] -losses -1.7 0.9 [-2, -1, -2, -3, 0, -1, -3, -1, -2, -2] -lossy -1.2 0.87178 [-2, -2, -1, -2, 0, 0, 0, -1, -2, -2] -lost -1.3 0.45826 [-1, -1, -2, -1, -1, -2, -2, -1, -1, -1] -louse -1.6 1.2 [-1, -1, -3, -4, 0, -3, -1, -1, -1, -1] -loused -1.0 0.7746 [-1, -1, -1, -1, 0, 0, -2, 0, -2, -2] -louses -1.3 0.78102 [-2, -1, -2, -1, -1, 0, -2, 0, -2, -2] -lousewort 0.1 1.3 [-2, -2, 1, 0, 0, 0, 0, 2, 2, 0] -louseworts -0.6 0.66332 [0, 0, 0, -2, 0, -1, 0, -1, -1, -1] -lousier -2.2 0.4 [-2, -3, -2, -2, -3, -2, -2, -2, -2, -2] -lousiest -2.6 0.8 [-4, -2, -3, -3, -1, -2, -3, -3, -2, -3] -lousily -1.2 0.9798 [-1, -1, -2, -2, -2, -2, 0, -1, 1, -2] -lousiness -1.7 0.64031 [-2, -2, -1, -1, -2, -2, -3, -2, -1, -1] -lousing -1.1 0.9434 [-3, 0, 0, 0, -1, -2, -1, -2, -1, -1] -lousy -2.5 0.67082 [-2, -4, -2, -3, -2, -3, -2, -2, -3, -2] -lovable 3.0 0.63246 [3, 3, 3, 4, 3, 2, 3, 3, 2, 4] -love 3.2 0.4 [3, 3, 3, 3, 3, 3, 3, 4, 4, 3] -loved 2.9 0.7 [3, 3, 4, 2, 2, 4, 3, 2, 3, 3] 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-1, 0, 0, 0, 0, 0, 0, 0] -lowlander -0.4 0.66332 [0, 0, 0, 0, 0, 0, -1, -1, -2, 0] -lowlanders -0.3 0.64031 [0, 0, 0, -2, 0, -1, 0, 0, 0, 0] -lowlands -0.1 0.7 [0, -1, -1, 0, -1, 1, 0, 1, 0, 0] -lowlier -1.7 0.78102 [-2, -2, -2, -3, -1, -2, -2, -1, 0, -2] -lowliest -1.8 1.6 [-1, -3, -3, -4, -2, -1, -1, 0, 1, -4] -lowlife -1.5 0.67082 [-2, -2, -2, -1, -1, -2, -1, 0, -2, -2] -lowlifes -2.2 1.249 [-3, -2, -3, -4, -2, 1, -2, -3, -2, -2] -lowlight -2.0 1.26491 [-3, -2, -1, -3, 1, -2, -1, -3, -3, -3] -lowlights -0.3 0.78102 [0, 0, -1, 1, -2, -1, 0, 0, 0, 0] -lowlihead -0.3 1.34536 [-1, -1, 1, -3, 0, 0, 1, -1, 2, -1] -lowliness -1.1 0.53852 [-1, -2, -1, -2, -1, -1, -1, 0, -1, -1] -lowlinesses -1.2 1.07703 [-3, -1, -2, -2, 0, -1, -1, -1, -2, 1] -lowlives -2.1 0.7 [-2, -3, -3, -2, -1, -2, -3, -2, -1, -2] -lowly -1.0 1.34164 [-1, -2, -1, -2, 2, -2, -1, 1, -2, -2] -lown 0.9 1.13578 [2, 2, 1, -1, 0, 1, 2, -1, 1, 2] -lowness -1.3 0.45826 [-1, -2, -2, -1, -1, -2, -1, -1, -1, -1] -lowrider -0.2 0.4 [0, 0, 0, -1, -1, 0, 0, 0, 0, 0] -lowriders 0.1 0.53852 [0, 0, 0, 0, 1, 0, -1, 0, 1, 0] -lows -0.8 0.9798 [0, -1, -1, -1, 0, 1, -3, -1, -1, -1] -lowse -0.7 0.78102 [0, -1, 1, -1, -1, -1, 0, -1, -2, -1] -loyal 2.1 0.7 [3, 2, 1, 1, 2, 2, 3, 2, 3, 2] -loyalism 1.0 0.89443 [1, 2, 1, -1, 0, 1, 2, 1, 1, 2] -loyalisms 0.9 0.83066 [2, 0, 0, 1, 1, 0, 2, 2, 1, 0] -loyalist 1.5 0.92195 [1, 0, 2, 2, 3, 0, 2, 2, 1, 2] -loyalists 1.1 0.83066 [1, 1, 1, 3, 0, 2, 1, 0, 1, 1] -loyally 2.1 0.7 [3, 2, 2, 2, 1, 3, 1, 2, 3, 2] -loyalties 1.9 0.7 [3, 1, 2, 2, 2, 3, 2, 1, 1, 2] -loyalty 2.5 0.67082 [1, 3, 3, 3, 3, 2, 2, 2, 3, 3] -luck 2.0 0.63246 [2, 2, 1, 3, 3, 2, 1, 2, 2, 2] -lucked 1.9 0.7 [2, 2, 2, 1, 1, 2, 3, 3, 1, 2] -luckie 1.6 0.66332 [1, 1, 1, 2, 2, 1, 1, 2, 2, 3] -luckier 1.9 0.7 [1, 3, 1, 2, 2, 1, 2, 3, 2, 2] -luckiest 2.9 0.7 [3, 3, 4, 2, 2, 4, 3, 3, 2, 3] -luckily 2.3 0.45826 [2, 2, 3, 2, 2, 3, 2, 2, 2, 3] -luckiness 1.0 1.61245 [2, 2, 1, -2, 3, 1, 1, 2, 2, -2] -lucking 1.2 0.6 [2, 1, 1, 0, 1, 1, 1, 2, 2, 1] -luckless -1.3 0.45826 [-2, -1, -2, -1, -1, -1, -2, -1, -1, -1] -lucks 1.6 0.91652 [0, 3, 1, 1, 3, 2, 2, 1, 2, 1] -lucky 1.8 0.74833 [2, 1, 1, 1, 3, 2, 1, 2, 2, 3] -ludicrous -1.5 1.36015 [2, -2, -2, -1, -1, -1, -3, -3, -2, -2] -ludicrously -0.2 1.83303 [3, -1, 0, -2, -1, 0, 3, -3, -1, 0] -ludicrousness -1.9 1.57797 [-1, 2, -2, -3, -2, -2, -3, -4, -1, -3] -lugubrious -2.1 1.37477 [-3, -2, -3, -3, -3, 1, -2, -3, 0, -3] -lulz 2.0 1.0 [2, 2, 2, 3, 4, 1, 3, 1, 1, 1] -lunatic -2.2 1.32665 [-2, -3, -4, -2, -3, -2, -1, -3, 1, -3] -lunatics -1.6 1.95959 [-4, -2, -3, -4, -2, 2, -1, -3, 1, 0] -lurk -0.8 0.87178 [-1, -1, 0, -3, -1, 0, -1, 0, -1, 0] -lurking -0.5 1.11803 [1, -1, -1, 0, -1, -2, 1, -2, 1, -1] -lurks -0.9 1.04403 [-1, -1, -1, -2, -2, -1, -1, -1, 2, -1] -lying -2.4 0.8 [-2, -4, -3, -1, -2, -2, -3, -2, -2, -3] -mad -2.2 0.74833 [-3, -3, -1, -1, -2, -3, -2, -2, -3, -2] -maddening -2.2 0.74833 [-3, -3, -1, -1, -3, -2, -2, -3, -2, -2] -madder -1.2 1.16619 [-2, 0, -3, 0, 0, -1, -3, -1, -2, 0] -maddest -2.8 1.16619 [-4, -4, -4, -4, -1, -3, -2, -1, -2, -3] -madly -1.7 1.1 [-2, 0, -2, -2, -2, -1, -4, -2, 0, -2] -madness -1.9 0.53852 [-1, -2, -1, -3, -2, -2, -2, -2, -2, -2] -magnific 2.3 1.1 [2, 2, 0, 2, 4, 4, 2, 2, 3, 2] -magnifical 2.4 1.28062 [1, 4, 1, 2, 4, 3, 1, 1, 4, 3] -magnifically 2.4 1.2 [3, 3, 3, 2, 4, 0, 1, 2, 2, 4] -magnification 1.0 0.89443 [2, 3, 1, 0, 0, 1, 1, 1, 0, 1] -magnifications 1.2 1.249 [-1, 0, 0, 2, 2, 2, 0, 2, 3, 2] -magnificence 2.4 1.0198 [3, 2, 1, 3, 2, 1, 4, 4, 2, 2] -magnificences 2.3 0.9 [3, 4, 3, 1, 3, 2, 1, 2, 2, 2] -magnificent 2.9 0.7 [2, 4, 2, 4, 3, 3, 3, 3, 2, 3] -magnificently 3.4 0.66332 [3, 3, 3, 4, 4, 2, 4, 4, 3, 4] -magnifico 1.8 0.87178 [2, 1, 1, 2, 1, 1, 3, 3, 3, 1] -magnificoes 1.4 0.8 [2, 2, 0, 2, 1, 1, 3, 1, 1, 1] -mandatory 0.3 0.9 [1, 0, -1, 0, -1, 0, 1, 2, 0, 1] -maniac -2.1 0.7 [-1, -2, -2, -2, -3, -3, -1, -2, -2, -3] -maniacal -0.3 1.73494 [2, -1, -3, -3, 0, 2, -1, 1, 1, -1] -maniacally -1.7 0.78102 [-1, -2, -1, -2, -3, -2, -1, -3, -1, -1] -maniacs -1.2 1.8868 [-3, 1, -2, 1, -3, -2, 0, 2, -3, -3] -manipulated -1.6 0.4899 [-2, -1, -1, -2, -1, -2, -2, -1, -2, -2] -manipulating -1.5 0.80623 [-1, -1, -1, -2, -2, -1, -2, -2, -3, 0] -manipulation -1.2 1.72047 [2, -3, -2, -3, -1, -1, -2, 2, -2, -2] -marvel 1.8 0.6 [2, 1, 1, 2, 1, 2, 3, 2, 2, 2] -marvelous 2.9 0.7 [2, 2, 3, 2, 3, 3, 4, 3, 4, 3] -marvels 2.0 0.89443 [3, 1, 1, 3, 1, 2, 1, 2, 3, 3] -masochism -1.6 1.11355 [-1, 0, -2, -2, -2, -2, 0, -4, -1, -2] -masochisms -1.1 1.57797 [3, -3, -2, -2, -1, -1, -2, -1, 0, -2] -masochist -1.7 0.9 [-1, 0, -3, -1, -2, -2, -2, -2, -1, -3] -masochistic -2.2 1.16619 [-1, -1, -1, -2, -3, -2, -4, -3, -4, -1] -masochistically -1.6 1.35647 [-1, -1, -3, -3, -3, -3, 0, -2, 1, -1] -masochists -1.2 1.07703 [1, -2, 0, -2, -3, -1, -2, -1, -1, -1] -masterpiece 3.1 0.83066 [3, 4, 4, 4, 2, 2, 2, 4, 3, 3] -masterpieces 2.5 0.67082 [2, 2, 3, 2, 2, 2, 4, 3, 3, 2] -matter 0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 1, 0, 0] -matters 0.1 0.3 [0, 0, 0, 0, 1, 0, 0, 0, 0, 0] -mature 1.8 0.4 [2, 2, 2, 2, 2, 1, 2, 2, 1, 2] -meaningful 1.3 0.9 [0, 0, 2, 1, 1, 3, 1, 2, 2, 1] -meaningless -1.9 0.7 [-1, -2, -2, -2, -1, -1, -2, -3, -3, -2] -medal 2.1 1.22066 [2, 4, 3, 1, 0, 2, 2, 2, 1, 4] -mediocrity -0.3 1.1 [-1, 0, -2, 0, -1, 2, -1, -1, 0, 1] -meditative 1.4 0.66332 [2, 0, 1, 2, 2, 1, 2, 1, 2, 1] -meh -0.3 0.78102 [-1, 0, -1, 0, -1, -1, 1, 0, 1, -1] -melancholia -0.5 1.28452 [0, -2, -2, 0, 1, -1, 2, -2, 0, -1] -melancholiac -2.0 0.63246 [-2, -2, -3, -2, -2, -3, -1, -1, -2, -2] -melancholias -1.6 0.8 [-1, -2, -3, -2, 0, -2, -1, -1, -2, -2] -melancholic -0.3 1.18743 [0, 2, -2, 0, 1, -1, 0, -2, 0, -1] -melancholics -1.0 1.0 [0, -1, -3, 1, -1, -2, -1, -1, -1, -1] -melancholies -1.1 0.83066 [-1, 0, -1, 0, -3, -1, -2, -1, -1, -1] -melancholy -1.9 1.13578 [-3, -2, -3, -2, -3, -2, -2, 1, -1, -2] -menace -2.2 0.87178 [-3, -3, -2, -1, -1, -2, -3, -1, -3, -3] -menaced -1.7 1.48661 [-3, -2, -2, -3, -3, -1, 1, -3, 1, -2] -mercy 1.5 0.67082 [1, 2, 1, 1, 1, 3, 2, 2, 1, 1] -merit 1.8 0.74833 [2, 2, 2, 2, 0, 2, 3, 2, 2, 1] -merited 1.4 0.4899 [1, 2, 2, 1, 1, 1, 2, 1, 2, 1] -meriting 1.1 1.13578 [1, 2, 1, -2, 1, 1, 2, 2, 1, 2] -meritocracy 0.6 1.35647 [2, 4, 0, 0, 1, -1, 0, 0, 0, 0] -meritocrat 0.4 0.8 [0, 0, 0, 1, -1, 0, 0, 1, 2, 1] -meritocrats 1.1 1.13578 [2, 1, 1, 0, 0, 1, 1, 4, 0, 1] -meritorious 2.1 0.53852 [3, 2, 2, 2, 2, 2, 2, 2, 3, 1] -meritoriously 1.3 1.95192 [3, -1, 3, -2, 2, 0, -1, 3, 3, 3] -meritoriousness 1.7 1.18743 [4, 1, 2, 1, 2, 0, 3, 2, 2, 0] -merits 1.7 0.78102 [1, 3, 1, 1, 2, 2, 1, 1, 3, 2] -merrier 1.7 1.41774 [3, 2, 2, 3, 2, 2, -1, -1, 3, 2] -merriest 2.7 1.41774 [3, 4, 4, 4, 2, 3, -1, 2, 3, 3] -merrily 2.4 0.66332 [3, 3, 2, 2, 2, 3, 2, 3, 1, 3] -merriment 2.4 1.35647 [1, 3, 3, 4, 2, -1, 3, 3, 3, 3] -merriments 2.0 0.89443 [2, 2, 3, 3, 0, 2, 2, 1, 2, 3] -merriness 2.2 0.74833 [2, 1, 2, 3, 2, 2, 3, 3, 1, 3] -merry 2.5 0.80623 [2, 4, 2, 2, 3, 3, 3, 3, 2, 1] -merrymaker 2.2 1.4 [3, 1, 3, 3, 3, -1, 2, 1, 3, 4] -merrymakers 1.7 1.34536 [1, 4, 1, 3, 1, 3, -1, 2, 1, 2] -merrymaking 2.2 0.6 [3, 2, 2, 2, 2, 1, 3, 3, 2, 2] -merrymakings 2.4 1.11355 [3, 3, 2, 3, 4, 2, 0, 3, 1, 3] -merrythought 1.1 0.9434 [1, 1, 3, 0, 2, 0, 0, 1, 2, 1] -merrythoughts 1.6 1.11355 [1, 3, 2, 1, 2, 1, 0, 3, 3, 0] -mess -1.5 0.92195 [-1, -3, -1, -1, -3, -1, -2, -1, 0, -2] -messed -1.4 0.8 [-2, -1, -1, -3, 0, -2, -2, -1, -1, -1] -messy -1.5 0.80623 [-1, -2, -2, -2, -1, -1, -2, 0, -1, -3] -methodical 0.6 0.8 [0, 0, 0, 2, 2, 0, 1, 1, 0, 0] -mindless -1.9 0.7 [-2, -1, -2, -1, -1, -2, -3, -3, -2, -2] -miracle 2.8 0.87178 [4, 4, 3, 2, 3, 4, 2, 2, 2, 2] -mirth 2.6 0.66332 [3, 3, 3, 2, 3, 3, 3, 2, 1, 3] -mirthful 2.7 0.45826 [3, 3, 3, 2, 3, 3, 3, 2, 3, 2] -mirthfully 2.0 1.48324 [2, 3, 4, 3, 0, -1, 2, 1, 3, 3] -misbehave -1.9 0.7 [-3, -3, -1, -2, -2, -1, -1, -2, -2, -2] -misbehaved -1.6 0.4899 [-1, -2, -1, -2, -2, -2, -1, -2, -1, -2] -misbehaves -1.6 0.4899 [-1, -2, -2, -1, -2, -2, -1, -2, -1, -2] -misbehaving -1.7 0.64031 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0] -numbed -0.9 0.53852 [-1, -1, -1, -1, 0, 0, -2, -1, -1, -1] -number 0.3 0.64031 [0, 0, 1, 0, 0, 2, 0, 0, 0, 0] -numberable 0.6 0.91652 [0, 2, 0, 0, 0, 2, 2, 0, 0, 0] -numbest -1.0 0.89443 [-2, -1, 0, 0, -3, -1, -1, -1, 0, -1] -numbfish -0.4 0.66332 [-1, 0, 0, 0, -2, 0, 0, -1, 0, 0] -numbfishes -0.7 0.9 [0, -1, 0, -1, -1, 0, -1, 0, 0, -3] -numbing -1.1 0.83066 [-1, 0, -1, -1, -2, -1, -3, -1, 0, -1] -numbingly -1.3 0.45826 [-1, -1, -2, -1, -1, -1, -2, -1, -2, -1] -numbles 0.4 0.66332 [0, 0, 0, 0, 1, 2, 0, 0, 1, 0] -numbly -1.4 1.0198 [-3, -2, 0, -1, -1, -3, -1, -2, -1, 0] -numbness -1.1 0.7 [-1, -1, -2, -1, -1, -2, -1, 0, -2, 0] -numbs -0.7 1.00499 [-1, 0, -1, 0, 1, 0, -3, -1, -1, -1] -numbskull -2.3 1.41774 [-2, -4, -3, 0, -2, -2, -4, -4, 0, -2] -numbskulls -2.2 1.07703 [-2, -2, -4, -2, -2, -1, -3, -3, 0, -3] -nurtural 1.5 0.80623 [2, 1, 2, 2, 1, 3, 0, 1, 2, 1] -nurturance 1.6 0.8 [1, 2, 1, 1, 3, 0, 2, 2, 2, 2] -nurturances 1.3 1.55242 [0, -2, 3, 1, 1, 2, 3, 0, 2, 3] -nurturant 1.7 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0.87178 [2, 3, 3, 2, 1, 2, 4, 2, 2, 1] -optimized 2.0 0.44721 [1, 3, 2, 2, 2, 2, 2, 2, 2, 2] -optimizer 1.5 0.67082 [1, 3, 1, 1, 2, 2, 1, 2, 1, 1] -optimizers 2.1 0.7 [3, 3, 1, 3, 2, 2, 1, 2, 2, 2] -optimizes 1.8 0.6 [1, 3, 2, 1, 2, 2, 1, 2, 2, 2] -optimizing 2.0 0.7746 [1, 1, 2, 2, 1, 3, 3, 3, 2, 2] -optionless -1.7 0.64031 [-2, -1, -2, -3, -1, -2, -2, -2, -1, -1] -original 1.3 0.9 [0, 2, 0, 2, 2, 0, 2, 1, 2, 2] -outcry -2.3 0.64031 [-3, -2, -2, -3, -2, -1, -3, -2, -2, -3] -outgoing 1.2 1.16619 [1, 1, 1, 2, -1, 1, 3, 3, 0, 1] -outmaneuvered 0.5 1.36015 [-2, 2, 0, 0, 3, 1, 1, 0, 1, -1] -outrage -2.3 1.00499 [-2, -2, -4, -3, -1, -3, -3, -1, -1, -3] -outraged -2.5 0.92195 [-3, -2, -2, -1, -3, -3, -1, -4, -3, -3] -outrageous -2.0 1.34164 [-3, 0, -2, -1, -3, 0, -3, -3, -4, -1] -outrageously -1.2 1.32665 [-1, -1, -3, -3, -2, -1, 2, -1, -1, -1] -outrageousness -1.2 1.249 [-2, 0, 1, -2, -1, -1, -3, 0, -1, -3] -outrageousnesses -1.3 1.67631 [-1, -3, -2, 1, 0, 1, 0, -3, -2, -4] -outrages -2.3 1.00499 [-3, -2, -2, -1, -3, -3, -1, -4, -1, -3] -outraging -2.0 1.18322 [-4, -1, -2, -3, -1, 0, -1, -3, -3, -2] -outreach 1.1 0.7 [2, 1, 0, 0, 2, 1, 1, 1, 2, 1] -outstanding 3.0 0.89443 [3, 1, 3, 3, 4, 4, 2, 3, 4, 3] -overjoyed 2.7 0.78102 [4, 3, 3, 4, 2, 2, 2, 2, 3, 2] -overload -1.5 0.67082 [-2, 0, -1, -2, -2, -1, -1, -2, -2, -2] -overlooked -0.1 1.44568 [-1, -2, -1, -1, 2, 0, -1, 2, -1, 2] -overreact -1.0 1.73205 [-2, -2, -2, -2, 0, -3, 1, 3, -1, -2] -overreacted -1.7 0.64031 [-2, -2, -2, -1, -1, -1, -1, -3, -2, -2] -overreaction -0.7 1.34536 [-2, -1, 0, -1, -1, 3, -2, -1, -1, -1] -overreacts -2.2 0.87178 [-2, -2, -2, -3, -4, -1, -3, -1, -2, -2] -oversell -0.9 0.7 [0, -1, -1, 0, -2, -1, -1, -1, -2, 0] -overselling -0.8 1.16619 [0, -1, 0, -1, -2, -1, -1, -2, -2, 2] -oversells 0.3 1.26886 [-1, -1, 0, 0, 2, 2, 2, -1, 1, -1] -oversimplification 0.2 1.53623 [-1, 1, -1, -1, 1, -1, -2, 1, 2, 3] -oversimplifies 0.1 1.37477 [3, 0, 0, -1, 1, -1, 2, -1, -1, -1] -oversimplify -0.6 1.35647 [-3, -1, 0, -2, 0, 1, 2, -1, -1, -1] -overstatement -1.1 0.7 [-2, 0, -1, -2, -1, 0, -1, -1, -2, -1] -overstatements -0.7 1.34536 [-1, -1, -3, -1, 2, 0, -1, -1, -2, 1] -overweight -1.5 0.67082 [-3, -2, -1, -1, -1, -2, -1, -2, -1, -1] -overwhelm -0.7 1.26886 [-1, 2, -1, -1, -2, -2, 1, 0, -1, -2] -overwhelmed 0.2 1.53623 [-2, -1, 2, -2, 2, 1, -1, 2, 1, 0] -overwhelmingly -0.5 1.28452 [0, -2, -1, 0, -2, -1, -2, 0, 1, 2] -overwhelms -0.8 1.249 [-2, -2, -1, -1, -1, -2, 2, 1, -1, -1] -oxymoron -0.5 0.80623 [0, 0, -1, -1, -1, -2, 1, 0, 0, -1] -pain -2.3 0.64031 [-2, -3, -2, -2, -2, -2, -2, -2, -2, -4] -pained -1.8 0.6 [-1, -2, -3, -2, -2, -2, -2, -1, -1, -2] -painful -1.9 0.9434 [-2, -1, -1, -3, -4, -1, -1, -2, -2, -2] -painfuller -1.7 1.34536 [-2, -2, -2, 2, -1, -3, -2, -2, -3, -2] -painfully -2.4 0.4899 [-2, -3, -2, -3, -3, -2, -2, -2, -2, -3] -painfulness -2.7 0.64031 [-3, -4, -3, -2, -3, -3, -3, -2, -2, -2] -paining -1.7 0.45826 [-1, -2, -2, -2, -2, -2, -1, -2, -1, -2] -painless 1.2 0.87178 [1, 2, -1, 1, 2, 1, 2, 1, 2, 1] -painlessly 1.1 0.3 [1, 1, 1, 1, 1, 1, 1, 1, 1, 2] -painlessness 0.4 1.0198 [1, 1, 1, 1, -1, 1, -2, 0, 1, 1] -pains -1.8 0.6 [-2, -2, -1, -1, -1, -2, -2, -2, -3, -2] -palatable 1.6 0.8 [2, 1, 2, 1, 2, 1, 3, 0, 2, 2] -palatableness 0.8 0.87178 [2, 1, 1, 0, -1, 2, 0, 1, 1, 1] -palatably 1.1 0.83066 [2, 1, 2, 1, 1, 1, 2, -1, 1, 1] -panic -2.3 0.64031 [-3, -2, -1, -2, -2, -2, -3, -3, -2, -3] -panicked -2.0 1.61245 [-2, -4, -3, -3, -3, 1, -2, -2, 1, -3] -panicking -1.9 0.53852 [-2, -2, -3, -2, -2, -2, -2, -2, -1, -1] -panicky -1.5 0.67082 [-2, -2, -1, -1, -1, -1, -1, -2, -3, -1] -panicle 0.5 0.67082 [2, 0, 0, 0, 0, 0, 0, 1, 1, 1] -panicled 0.1 0.83066 [2, 0, 0, 0, 0, -1, 0, -1, 1, 0] -panicles -0.2 0.6 [1, 0, 0, 0, 0, -1, 0, -1, -1, 0] -panics -1.9 1.3 [-2, -3, -2, -3, -1, -2, 1, -4, -1, -2] -paniculate 0.1 0.3 [0, 0, 0, 1, 0, 0, 0, 0, 0, 0] -panicums -0.1 0.3 [0, 0, 0, 0, -1, 0, 0, 0, 0, 0] -paradise 3.2 0.9798 [4, 1, 4, 2, 4, 4, 3, 3, 3, 4] -paradox -0.4 0.66332 [-1, -1, 0, 0, -1, 0, -1, 0, 1, -1] -paranoia -1.0 1.48324 [1, -2, -2, -3, -1, 0, -2, -1, -2, 2] -paranoiac -1.3 1.61555 [-2, -3, -2, -2, 1, -3, 2, -2, 0, -2] -paranoiacs -0.7 1.18743 [-1, 0, -1, -1, -3, 1, -2, 0, 1, -1] -paranoias -1.5 1.0247 [-2, -3, -2, 0, -1, -3, 0, -1, -1, -2] -paranoid -1.0 1.41421 [0, -3, -3, -2, -1, -1, 0, 1, -2, 1] -paranoids -1.6 0.91652 [-2, -1, -1, -2, -2, -1, -1, -1, -4, -1] -pardon 1.3 0.45826 [1, 2, 1, 2, 1, 2, 1, 1, 1, 1] -pardoned 0.9 0.9434 [1, 1, 1, 1, 1, 1, 1, 0, 3, -1] -pardoning 1.7 0.78102 [3, 2, 2, 2, 1, 1, 2, 2, 0, 2] -pardons 1.2 0.6 [2, 1, 1, 1, 1, 2, 1, 2, 0, 1] -parley -0.4 0.66332 [0, -2, 0, 0, -1, -1, 0, 0, 0, 0] -partied 1.4 1.11355 [2, 3, 1, 1, 1, 2, 3, -1, 1, 1] -partier 1.4 0.8 [2, 2, 1, 1, 0, 2, 3, 1, 1, 1] -partiers 0.7 1.00499 [0, 0, 3, 0, 0, 0, 2, 1, 0, 1] -parties 1.7 0.78102 [2, 3, 1, 1, 1, 2, 3, 1, 2, 1] -party 1.7 0.78102 [3, 2, 2, 1, 3, 2, 1, 1, 1, 1] -partyer 1.2 1.07703 [1, 3, 1, 0, 1, 0, 2, 1, 3, 0] -partyers 1.1 0.83066 [1, 2, 0, 3, 1, 1, 1, 0, 1, 1] -partying 1.6 1.11355 [0, 3, 1, 0, 3, 2, 3, 1, 2, 1] -passion 2.0 0.44721 [2, 2, 1, 3, 2, 2, 2, 2, 2, 2] -passional 1.6 0.8 [2, 1, 3, 0, 2, 1, 1, 2, 2, 2] -passionate 2.4 1.35647 [0, 4, 3, 3, 4, 2, 0, 2, 3, 3] -passionately 2.4 0.91652 [3, 0, 3, 3, 2, 3, 2, 3, 2, 3] -passionateness 2.3 0.64031 [1, 3, 2, 3, 2, 3, 2, 3, 2, 2] -passionflower 0.3 0.45826 [0, 0, 0, 0, 1, 0, 1, 1, 0, 0] -passionflowers 0.4 0.66332 [0, 0, 0, 0, 2, 1, 1, 0, 0, 0] -passionless -1.9 0.7 [-3, -2, -2, -2, -1, -1, -1, -3, -2, -2] -passions 2.2 0.6 [3, 3, 3, 2, 2, 1, 2, 2, 2, 2] -passive 0.8 1.46969 [4, 1, 1, 0, -2, 0, 1, 1, 2, 0] -passively -0.7 0.64031 [0, -1, 0, 0, -1, -2, 0, -1, -1, -1] -pathetic -2.7 1.48661 [-3, -4, -3, -4, -2, 1, -2, -2, -4, -4] -pathetical -1.2 1.249 [-2, -1, -2, -1, -2, 1, -3, 1, -1, -2] -pathetically -1.8 1.72047 [-3, -4, -2, 0, -3, -2, -3, -3, 1, 1] -pay -0.4 0.91652 [0, 0, -3, 0, 0, 0, 0, 0, -1, 0] -peace 2.5 1.0247 [3, 2, 1, 4, 2, 3, 4, 1, 3, 2] -peaceable 1.7 0.45826 [2, 2, 1, 2, 1, 2, 2, 1, 2, 2] -peaceableness 1.8 1.16619 [2, 2, 4, 2, 2, 2, 2, 1, 2, -1] -peaceably 2.0 0.63246 [2, 3, 2, 2, 1, 2, 3, 1, 2, 2] -peaceful 2.2 0.74833 [4, 2, 1, 2, 2, 2, 3, 2, 2, 2] -peacefuller 1.9 0.7 [2, 2, 2, 1, 3, 3, 2, 2, 1, 1] -peacefullest 3.1 0.7 [3, 3, 2, 3, 4, 2, 4, 3, 4, 3] -peacefully 2.4 0.66332 [3, 2, 2, 2, 4, 2, 2, 3, 2, 2] -peacefulness 2.1 0.83066 [3, 2, 1, 2, 3, 1, 3, 3, 1, 2] -peacekeeper 1.6 1.11355 [1, 1, 0, 2, 1, 1, 4, 3, 2, 1] -peacekeepers 1.6 1.11355 [4, 1, 1, 2, 1, 1, 2, 3, 0, 1] -peacekeeping 2.0 0.63246 [2, 1, 1, 2, 3, 3, 2, 2, 2, 2] -peacekeepings 1.6 0.8 [0, 1, 1, 2, 2, 3, 2, 2, 2, 1] -peacemaker 2.0 0.89443 [2, 1, 2, 4, 2, 2, 1, 3, 1, 2] -peacemakers 2.4 1.0198 [0, 3, 4, 2, 3, 2, 3, 3, 2, 2] -peacemaking 1.7 0.78102 [1, 1, 1, 3, 3, 1, 2, 2, 2, 1] -peacenik 0.8 0.87178 [1, 1, 0, 1, 2, 0, 1, 1, -1, 2] -peaceniks 0.7 1.00499 [2, 0, 0, 1, 0, 2, 1, -1, 2, 0] -peaces 2.1 0.83066 [2, 2, 2, 2, 3, 0, 3, 3, 2, 2] -peacetime 2.2 1.16619 [3, 1, 4, 2, 4, 3, 1, 1, 2, 1] -peacetimes 2.1 0.83066 [3, 2, 2, 4, 1, 2, 2, 2, 1, 2] -peculiar 0.6 1.2 [-1, 0, -1, 1, 2, -1, 2, 1, 2, 1] -peculiarities 0.1 1.37477 [-1, -1, 0, -1, -1, 1, 3, 2, -1, 0] -peculiarity 0.6 1.2 [-1, 1, -1, 0, 2, -1, 1, 2, 2, 1] -peculiarly -0.4 1.2 [-1, 2, -2, -1, 0, 0, -2, 1, -1, 0] -penalty -2.0 0.63246 [-2, -3, -2, -2, -1, -2, -3, -2, -2, -1] -pensive 0.3 1.1 [1, 0, 0, 1, 0, -1, 3, 0, -1, 0] -perfect 2.7 0.78102 [2, 4, 2, 3, 4, 2, 3, 2, 3, 2] -perfecta 1.4 1.42829 [1, 0, 0, 3, 1, 0, 0, 4, 3, 2] -perfectas 0.6 1.11355 [0, 0, -1, 1, 0, 2, 3, 0, 1, 0] -perfected 2.7 0.78102 [1, 3, 3, 4, 2, 3, 3, 2, 3, 3] -perfecter 1.8 0.9798 [2, 1, 3, 1, 2, 1, 2, 4, 1, 1] -perfecters 1.4 1.11355 [2, 1, 3, 0, 0, 3, 2, 0, 1, 2] -perfectest 3.1 1.04403 [2, 4, 4, 4, 3, 2, 1, 3, 4, 4] -perfectibilities 2.1 1.04403 [3, 2, 2, 3, 4, 1, 2, 2, 0, 2] -perfectibility 1.8 1.249 [4, 3, 3, 0, 1, 0, 1, 2, 2, 2] -perfectible 1.5 0.67082 [1, 2, 1, 1, 2, 1, 1, 3, 2, 1] -perfecting 2.3 0.9 [1, 2, 3, 3, 1, 2, 2, 4, 2, 3] -perfection 2.7 1.1 [3, 3, 3, 1, 2, 4, 4, 1, 2, 4] -perfectionism 1.3 1.26886 [3, -1, 2, 1, 2, 2, 2, -1, 1, 2] -perfectionist 1.5 1.20416 [3, -1, 3, 1, 2, 2, 2, 0, 1, 2] -perfectionistic 0.7 1.67631 [-1, 0, 2, 0, 1, 0, 3, -1, 4, -1] -perfectionists 0.1 1.22066 [1, -1, 1, -1, 0, 0, -1, 0, 3, -1] -perfections 2.5 1.43178 [2, 4, 4, 3, 3, 4, -1, 2, 2, 2] -perfective 1.2 0.87178 [1, 0, 1, 1, 3, 2, 2, 0, 1, 1] -perfectively 2.1 1.13578 [3, 3, 1, 4, 0, 2, 1, 2, 2, 3] -perfectiveness 0.9 1.51327 [-2, 3, -1, 0, 2, 0, 2, 2, 2, 1] -perfectives 0.9 0.83066 [0, 2, 1, 1, 1, 0, 2, 0, 2, 0] -perfectivity 2.2 0.9798 [3, 2, 0, 3, 1, 2, 3, 3, 2, 3] -perfectly 3.2 0.4 [3, 4, 4, 3, 3, 3, 3, 3, 3, 3] -perfectness 3.0 0.63246 [4, 3, 3, 3, 3, 2, 4, 2, 3, 3] -perfecto 1.3 1.34536 [1, 0, 0, 2, 0, 0, 1, 4, 3, 2] -perfects 1.6 1.11355 [1, 1, 1, 2, 1, 0, 1, 4, 3, 2] -peril -1.7 1.67631 [-3, -2, -2, 3, -3, -2, -3, -2, -1, -2] -perjury -1.9 0.9434 [-3, -2, -3, -2, -2, 0, -1, -2, -3, -1] -perpetrator -2.2 0.74833 [-2, -3, -2, -2, -2, -2, -4, -2, -1, -2] -perpetrators -1.0 1.67332 [-1, -2, -2, -2, -2, 2, 0, -4, 1, 0] -perplexed -1.3 0.64031 [-1, -1, -2, -1, -1, -1, 0, -2, -2, -2] -persecute -2.1 1.37477 [-2, -3, -2, 1, -1, -4, -2, -2, -2, -4] -persecuted -1.3 1.61555 [-2, -1, -2, -1, -2, 2, -4, 1, -2, -2] -persecutes -1.2 1.4 [-2, -1, -2, 0, -2, 1, -3, 1, -1, -3] -persecuting -1.5 1.62788 [-3, -2, -2, 0, -4, -3, -2, -1, 1, 1] -perturbed -1.4 0.8 [-2, -1, -1, 0, -2, -2, -2, 0, -2, -2] -perverse -1.8 1.8868 [-2, -4, -3, 1, -2, -4, 1, 0, -1, -4] -perversely -2.2 0.87178 [-1, -2, -2, -2, -1, -3, -2, -3, -4, -2] -perverseness -2.1 1.22066 [-3, -3, 1, -2, -3, -2, -3, -2, -1, -3] -perversenesses -0.5 1.74642 [-2, 3, -1, -2, 1, 0, 1, 0, -2, -3] -perversion -1.3 1.34536 [-3, -2, -2, 1, 1, -3, -1, -2, -1, -1] -perversions -1.2 1.83303 [-2, 0, -4, -2, -3, -3, 0, 1, -1, 2] -perversities -1.1 1.22066 [-2, -1, -2, 0, -2, -2, -2, 1, 1, -2] -perversity -2.6 0.8 [-2, -3, -2, -2, -4, -3, -3, -1, -3, -3] -perversive -2.1 0.7 [-3, -1, -3, -2, -2, -2, -2, -1, -3, -2] -pervert -2.3 0.9 [-2, -2, -1, -3, -4, -2, -3, -1, -3, -2] -perverted -2.5 1.56525 [-2, -4, -2, -4, -3, -4, 1, -2, -1, -4] -pervertedly -1.2 1.77764 [-3, -2, -1, -2, 2, -3, 1, -3, 1, -2] -pervertedness -1.2 1.46969 [1, -2, -3, -2, 0, -2, -3, 1, 0, -2] -perverter -1.7 1.48661 [-3, -4, -2, -2, -1, -1, 2, -2, -2, -2] -perverters -0.6 1.68523 [-2, -2, -1, 0, -1, 2, -3, 1, 2, -2] -perverting -1.0 2.09762 [4, -2, -2, -4, -2, 1, 0, -1, -2, -2] -perverts -2.8 0.6 [-3, -3, -2, -3, -3, -2, -2, -4, -3, -3] -pesky -1.2 0.4 [-1, -2, -1, -1, -1, -1, -2, -1, -1, -1] -pessimism -1.5 1.36015 [-2, -3, 1, -2, -2, -1, 1, -3, -2, -2] -pessimisms -2.0 1.0 [-3, -1, -2, -2, -3, -1, 0, -2, -3, -3] -pessimist -1.5 1.36015 [-1, -3, 1, -2, -2, -2, 1, -3, -2, -2] -pessimistic -1.5 1.43178 [-3, -1, -1, 1, -3, -3, -2, -2, -2, 1] -pessimistically -2.0 1.0 [-1, -1, -3, -4, -2, -1, -1, -3, -2, -2] -pessimists -1.0 1.26491 [-1, 1, -1, 0, -2, -2, -2, -3, -1, 1] -petrifaction -1.9 1.3 [-3, -2, -1, -4, -3, 0, -1, 0, -2, -3] -petrifactions -0.3 1.00499 [0, -1, 0, 0, 0, 0, 0, 0, -3, 1] -petrification -0.1 1.44568 [-1, 2, -1, -1, 0, 2, 2, -2, -1, -1] -petrifications -0.4 0.8 [0, 0, -2, 0, 0, 0, 0, 0, -2, 0] -petrified -2.5 0.92195 [-4, -3, -2, -1, -2, -3, -2, -2, -2, -4] -petrifies -2.3 1.00499 [-4, -3, -2, -1, -2, -2, -1, -2, -2, -4] -petrify -1.7 0.9 [-2, -3, -1, -2, -1, -1, -2, -3, 0, -2] -petrifying -2.6 0.8 [-2, -3, -3, -2, -4, -2, -3, -1, -3, -3] -pettier -0.3 1.41774 [-1, -1, -1, -1, 2, 0, 2, -2, 1, -2] -pettiest -1.3 1.95192 [1, -3, -3, -3, -2, -1, 2, -1, 1, -4] -petty -0.8 1.32665 [1, -3, -2, -1, -1, -1, -1, -1, 2, -1] -phobia -1.6 1.0198 [-2, -2, 1, -2, -3, -1, -1, -2, -2, -2] -phobias -2.0 1.0 [-3, -2, -2, -3, -3, 0, -1, -2, -1, -3] -phobic -1.2 1.16619 [-2, -2, 1, -1, -2, -1, 1, -2, -2, -2] -phobics -1.3 0.64031 [-1, -1, -1, -2, -2, -1, 0, -2, -2, -1] -picturesque 1.6 1.11355 [4, 1, 1, 2, 1, 2, 1, 0, 3, 1] -pileup -1.1 1.13578 [-2, 1, 0, -1, 0, -1, -3, -2, -2, -1] -pique -1.1 1.13578 [-2, -2, -2, 0, 0, -1, 1, -1, -1, -3] -piqued 0.1 1.04403 [0, -2, 0, 1, 1, 1, -1, 1, -1, 1] -piss -1.7 0.9 [-2, -1, -1, -2, -1, -3, -3, 0, -2, -2] -pissant -1.5 1.5 [-1, -3, -3, 1, -3, -1, -1, -2, 1, -3] -pissants -2.5 0.80623 [-4, -3, -3, -2, -3, -1, -2, -3, -2, -2] -pissed -3.2 0.6 [-3, -3, -4, -3, -2, -4, -4, -3, -3, -3] -pisser -2.0 1.09545 [-2, -4, -1, -3, -2, -3, -1, -2, -2, 0] -pissers -1.4 2.00998 [-1, -1, -4, -2, -3, 4, -2, -1, -2, -2] -pisses -1.4 0.8 [-2, -2, -1, -3, -1, -1, -1, -2, -1, 0] -pissing -1.7 1.26886 [0, 0, -2, -2, -3, 0, -3, -1, -3, -3] -pissoir -0.8 1.4 [-2, 0, 0, -2, -1, -3, 0, -2, 0, 2] -piteous -1.2 1.46969 [-2, -1, -2, -2, -2, -1, 3, -1, -2, -2] -pitiable -1.1 1.22066 [-1, 0, -1, -1, 1, -2, -4, -1, -1, -1] -pitiableness -1.1 1.64012 [-2, -1, -1, -2, -4, 2, 1, 0, -2, -2] -pitiably -1.1 0.9434 [-1, 0, 0, -2, 0, -2, -3, -1, -1, -1] -pitied -1.3 1.1 [-2, -1, -3, -1, 1, 0, -2, -2, -1, -2] -pitier -1.2 1.32665 [-3, -1, -2, -3, -1, -1, 1, 1, -2, -1] -pitiers -1.3 0.9 [0, -1, -2, -2, -1, -1, -1, -3, -2, 0] -pities -1.2 1.249 [-2, -1, -2, -3, -1, -1, 1, 1, -2, -2] -pitiful -2.2 0.9798 [-3, -2, -1, -3, -2, -2, -3, -3, -3, 0] -pitifuller -1.8 1.07703 [-1, -1, -2, -3, -4, 0, -2, -2, -1, -2] -pitifullest -1.1 2.11896 [-2, 1, -1, -4, -4, -1, -3, -1, 2, 2] -pitifully -1.2 1.249 [-2, -1, -3, -2, -1, -1, -2, -1, 2, -1] -pitifulness -1.2 1.77764 [-3, -2, -1, -3, -2, -1, 3, 1, -2, -2] -pitiless -1.8 0.87178 [-2, 0, -2, -2, -2, -3, -1, -3, -1, -2] -pitilessly -2.1 0.7 [-2, -2, -1, -3, -3, -1, -3, -2, -2, -2] -pitilessness -0.5 1.62788 [1, 3, 1, -3, -2, -1, -1, -1, -1, -1] -pity -1.2 0.4 [-2, -2, -1, -1, -1, -1, -1, -1, -1, -1] -pitying -1.4 0.91652 [-1, -3, -1, -3, -2, -1, 0, -1, -1, -1] -pityingly -1.0 1.26491 [-2, -2, -1, -2, -2, 0, 0, -1, 2, -2] -pityriasis -0.8 0.87178 [-2, 0, 0, 0, -1, 0, -2, -1, -2, 0] -play 1.4 1.0198 [2, 0, 1, 1, 1, 2, 1, 4, 1, 1] -played 1.4 1.42829 [2, 1, 1, 1, 4, 0, 1, 0, 4, 0] -playful 1.9 0.83066 [4, 2, 2, 2, 1, 1, 1, 2, 2, 2] -playfully 1.6 0.4899 [2, 1, 1, 2, 1, 2, 2, 2, 1, 2] -playfulness 1.2 0.87178 [2, 1, 2, -1, 1, 2, 1, 2, 1, 1] -playing 0.8 0.87178 [0, 2, 2, 1, 0, 0, 2, 0, 0, 1] -plays 1.0 1.09545 [0, 2, 0, 2, 0, 1, 0, 2, 3, 0] -pleasant 2.3 0.64031 [2, 3, 3, 3, 2, 1, 2, 2, 3, 2] -pleasanter 1.5 0.67082 [2, 2, 2, 1, 0, 1, 1, 2, 2, 2] -pleasantest 2.6 0.8 [3, 3, 3, 1, 2, 4, 3, 2, 2, 3] -pleasantly 2.1 0.53852 [1, 2, 3, 2, 2, 2, 2, 2, 3, 2] -pleasantness 2.3 0.9 [3, 2, 3, 3, 3, 1, 1, 3, 1, 3] -pleasantnesses 2.3 0.78102 [3, 1, 2, 3, 1, 2, 3, 3, 2, 3] -pleasantries 1.3 0.45826 [1, 1, 1, 1, 1, 2, 1, 2, 2, 1] -pleasantry 2.0 0.7746 [2, 2, 1, 1, 4, 2, 2, 2, 2, 2] -please 1.3 0.78102 [2, 1, 2, 2, 2, 0, 2, 1, 0, 1] -pleased 1.9 0.53852 [2, 2, 2, 2, 1, 1, 2, 3, 2, 2] -pleaser 1.7 0.45826 [2, 2, 2, 2, 1, 1, 1, 2, 2, 2] -pleasers 1.0 1.0 [1, 1, 2, 0, 1, 3, 1, 1, -1, 1] -pleases 1.7 0.45826 [2, 1, 2, 2, 1, 1, 2, 2, 2, 2] -pleasing 2.4 0.91652 [2, 3, 2, 2, 2, 2, 4, 4, 1, 2] -pleasurability 1.9 0.83066 [1, 2, 2, 2, 2, 0, 2, 3, 3, 2] -pleasurable 2.4 0.4899 [2, 3, 3, 2, 3, 3, 2, 2, 2, 2] -pleasurableness 2.4 0.91652 [2, 3, 2, 1, 2, 3, 4, 3, 1, 3] -pleasurably 2.6 0.4899 [2, 2, 2, 3, 3, 3, 3, 2, 3, 3] -pleasure 2.7 0.9 [4, 4, 3, 2, 2, 3, 2, 1, 3, 3] -pleasured 2.3 0.64031 [3, 2, 3, 2, 3, 3, 1, 2, 2, 2] -pleasureless -1.6 0.8 [-1, -1, -1, -1, -2, -3, -3, -2, -1, -1] -pleasures 1.9 1.37477 [3, -2, 3, 2, 3, 2, 2, 2, 2, 2] -pleasuring 2.8 0.4 [3, 2, 3, 3, 3, 3, 3, 2, 3, 3] -poised 1.0 0.44721 [1, 1, 1, 1, 1, 1, 0, 1, 1, 2] -poison -2.5 0.92195 [-4, -3, -2, -4, -2, -2, -2, -3, -1, -2] -poisoned -2.2 0.9798 [-4, -1, -4, -1, -2, -2, -2, -2, -2, -2] -poisoner -2.7 0.78102 [-2, -3, -3, -4, -4, -2, -2, -2, -2, -3] -poisoners -3.1 0.83066 [-3, -4, -3, -4, -3, -4, -3, -3, -1, -3] -poisoning -2.8 1.249 [-4, -4, -2, 0, -2, -3, -4, -3, -2, -4] -poisonings -2.4 1.11355 [-2, 0, -2, -1, -4, -3, -3, -3, -3, -3] -poisonous -2.7 0.78102 [-3, -3, -4, -2, -1, -3, -3, -3, -3, -2] -poisonously -2.9 0.53852 [-3, -2, -3, -3, -2, -3, -3, -4, -3, -3] -poisons -2.7 0.9 [-3, -4, -3, -1, -2, -3, -3, -2, -2, -4] -poisonwood -1.0 0.89443 [0, -2, 0, 0, 0, -1, -2, -2, -2, -1] -pollute -2.3 0.64031 [-3, -2, -2, -2, -2, -3, -3, -1, -3, -2] -polluted -2.0 0.44721 [-2, -2, -1, -2, -2, -2, -2, -2, -3, -2] -polluter -1.8 0.6 [-2, -1, -2, -1, -2, -2, -3, -1, -2, -2] -polluters -2.0 0.44721 [-2, -2, -2, -2, -2, -3, -2, -1, -2, -2] -pollutes -2.2 0.87178 [-2, -1, -2, -1, -3, -1, -3, -3, -3, -3] -poor -2.1 1.13578 [-2, -2, -1, -4, -2, 0, -2, -4, -2, -2] -poorer -1.5 1.56525 [-2, -3, -2, -2, -2, -2, 3, -2, -1, -2] -poorest -2.5 0.80623 [-2, -3, -3, -1, -2, -3, -3, -4, -2, -2] -popular 1.8 0.74833 [2, 3, 1, 2, 2, 1, 3, 1, 2, 1] -popularise 1.6 0.66332 [1, 1, 2, 2, 3, 2, 1, 2, 1, 1] -popularised 1.1 0.9434 [1, 1, 0, 0, 3, 2, 1, 2, 1, 0] -popularises 0.5 0.67082 [1, 0, 0, 0, 0, 1, 1, 2, 0, 0] -popularising 1.2 0.6 [1, 0, 2, 2, 1, 1, 1, 2, 1, 1] 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-positivism 1.6 1.35647 [3, 0, 2, 1, 2, 0, 3, 4, 1, 0] -positivisms 1.8 0.9798 [4, 1, 2, 2, 2, 0, 2, 2, 1, 2] -positivist 2.0 1.0 [3, 1, 2, 2, 2, 0, 2, 4, 2, 2] -positivistic 1.9 0.83066 [2, 3, 1, 3, 1, 1, 3, 2, 1, 2] -positivists 1.7 1.1 [1, 2, 1, 4, 2, 1, 3, 0, 1, 2] -positivities 2.6 0.91652 [2, 2, 4, 3, 2, 3, 4, 3, 1, 2] -positivity 2.3 0.9 [2, 2, 2, 3, 3, 3, 3, 0, 3, 2] -possessive -0.9 1.22066 [-1, -1, -2, -2, 0, -1, 0, -2, 2, -2] -postpone -0.9 0.83066 [1, -1, -2, -1, -1, -2, -1, -1, 0, -1] -postponed -0.8 0.4 [-1, -1, 0, 0, -1, -1, -1, -1, -1, -1] -postpones -1.1 0.83066 [-1, -1, -1, 0, -1, 0, -2, -1, -3, -1] -postponing -0.5 0.5 [0, -1, 0, -1, 0, 0, 0, -1, -1, -1] -poverty -2.3 1.00499 [-2, -4, -2, -4, -3, -1, -2, -2, -1, -2] -powerful 1.8 0.9798 [4, 0, 2, 1, 2, 2, 2, 2, 1, 2] -powerless -2.2 0.6 [-2, -3, -2, -2, -3, -2, -3, -2, -1, -2] -praise 2.6 0.8 [2, 4, 3, 3, 2, 1, 3, 3, 2, 3] -praised 2.2 0.6 [3, 2, 2, 2, 2, 3, 1, 3, 2, 2] -praiser 2.0 0.89443 [3, 1, 3, 1, 1, 2, 1, 3, 2, 3] -praisers 2.0 0.63246 [2, 2, 1, 3, 3, 2, 1, 2, 2, 2] -praises 2.4 0.4899 [3, 2, 2, 3, 2, 3, 2, 3, 2, 2] -praiseworthily 1.9 0.7 [2, 1, 1, 3, 2, 2, 2, 3, 1, 2] -praiseworthiness 2.4 0.8 [1, 3, 2, 4, 2, 2, 3, 2, 3, 2] -praiseworthy 2.6 0.4899 [3, 3, 3, 3, 2, 2, 3, 2, 3, 2] -praising 2.5 0.67082 [2, 3, 3, 2, 2, 3, 3, 3, 1, 3] -pray 1.3 1.18743 [0, 3, 2, 1, 1, 1, -1, 3, 1, 2] -praying 1.5 0.92195 [2, 2, 0, 3, 1, 3, 1, 1, 1, 1] -prays 1.4 1.0198 [2, 0, 2, 0, 1, 1, 3, 1, 3, 1] -prblm -1.6 0.8 [-1, -1, -1, -1, -1, -3, -3, -2, -2, -1] -prblms -2.3 1.00499 [-2, -2, -2, -2, -4, -4, -3, -1, -2, -1] -precious 2.7 0.64031 [3, 3, 3, 3, 3, 1, 3, 3, 2, 3] -preciously 2.2 0.74833 [3, 3, 3, 2, 2, 1, 1, 3, 2, 2] -preciousness 1.9 0.83066 [2, 4, 2, 2, 2, 1, 1, 1, 2, 2] -prejudice -2.3 0.78102 [-2, -1, -2, -2, -3, -2, -2, -3, -4, -2] -prejudiced -1.9 0.53852 [-2, -3, -1, -2, -1, -2, -2, -2, -2, -2] -prejudices -1.8 0.74833 [-2, -3, -1, -2, -1, -3, -2, -1, -1, -2] -prejudicial -2.6 0.8 [-3, -3, -2, -2, -3, -4, -2, -1, -3, -3] -prejudicially -1.5 1.74642 [-3, -1, -1, -3, -3, -1, -3, 1, 2, -3] -prejudicialness -2.4 1.42829 [-2, -3, 1, -3, -2, -4, -4, -3, -1, -3] -prejudicing -1.8 1.07703 [-2, -2, -2, -3, -2, -1, 1, -3, -2, -2] -prepared 0.9 0.3 [1, 1, 1, 1, 1, 0, 1, 1, 1, 1] -pressure -1.2 0.6 [-1, -1, -1, -1, -2, -2, -1, -2, 0, -1] -pressured -0.9 1.04403 [-2, -1, -2, -1, 2, -1, -1, -1, -1, -1] -pressureless 1.0 1.26491 [2, 0, 1, -1, -1, 2, 1, 2, 1, 3] -pressures -1.3 0.64031 [-2, -1, -1, -1, -3, -1, -1, -1, -1, -1] -pressuring -1.4 0.91652 [-3, -1, -1, -1, -1, -1, -1, -3, -2, 0] -pressurise -0.6 1.0198 [0, -2, 0, 1, 0, -2, 0, -2, 0, -1] -pressurised -0.4 0.66332 [0, 0, 0, -1, 0, -1, 0, -2, 0, 0] -pressurises -0.8 0.6 [-1, -1, -1, 0, -1, -1, 0, -1, 0, -2] -pressurising -0.6 1.28062 [-1, 0, 0, 2, -1, -1, -3, 0, -2, 0] -pressurizations -0.3 1.00499 [0, 0, 1, -2, 0, 0, -1, -2, 0, 1] -pressurize -0.7 1.34536 [0, -2, -2, 0, 0, -1, -3, 2, -1, 0] -pressurized 0.1 0.83066 [0, 0, 0, 2, 0, 0, -1, -1, 0, 1] -pressurizer 0.1 0.83066 [0, 0, 0, 1, 0, 0, -1, -1, 0, 2] -pressurizers -0.7 0.9 [-1, 0, -2, -1, -2, -1, 0, 0, 1, -1] -pressurizes -0.2 0.87178 [0, 0, -1, 1, 0, 0, -1, -2, 0, 1] -pressurizing -0.2 0.9798 [1, 0, -1, -1, -1, 0, -1, 2, 0, -1] -pretend -0.4 0.91652 [0, 1, -1, -1, -2, 0, -1, -1, 1, 0] -pretending 0.4 1.49666 [2, 0, -1, -1, 0, 3, -2, 1, 0, 2] -pretends -0.4 0.66332 [0, -1, 0, -1, 1, 0, 0, -1, -1, -1] -prettied 1.6 0.66332 [2, 1, 1, 1, 1, 2, 3, 2, 1, 2] -prettier 2.1 0.53852 [2, 2, 2, 2, 2, 2, 3, 1, 2, 3] -pretties 1.7 0.78102 [2, 1, 1, 2, 1, 2, 3, 1, 1, 3] -prettiest 2.7 0.78102 [4, 3, 4, 2, 2, 2, 3, 2, 2, 3] -pretty 2.2 0.6 [3, 2, 2, 2, 3, 1, 2, 2, 2, 3] -prevent 0.1 1.22066 [-2, 1, 0, 0, -1, 2, -1, 2, 0, 0] -prevented 0.1 0.7 [0, -1, 0, 2, 0, 0, 0, 0, 0, 0] -preventing -0.1 1.51327 [-2, 0, -2, 3, 0, 0, -1, -1, 2, 0] -prevents 0.3 1.34536 [0, -2, 0, 0, 0, 2, 0, -1, 3, 1] -prick -1.4 1.42829 [-2, -2, -2, -1, 1, -1, -4, -2, 1, -2] -pricked -0.6 1.0198 [-1, -1, -2, 1, 0, -1, -2, -1, 1, 0] -pricker -0.3 0.9 [-1, -1, 0, 2, 0, -1, -1, -1, 0, 0] -prickers -0.2 0.87178 [1, -1, -1, 0, 1, -1, 0, 1, -1, -1] -pricket -0.5 0.67082 [0, -1, -1, -2, 0, 0, 0, 0, -1, 0] -prickets 0.3 0.64031 [0, 2, 0, 0, 0, 1, 0, 0, 0, 0] -pricking -0.9 1.22066 [-2, -1, -2, 2, -2, -2, -1, 0, -1, 0] -prickle -1.0 0.44721 [-1, -1, -1, -1, -1, -1, -2, 0, -1, -1] -prickled -0.2 1.53623 [-1, -1, 3, -1, -2, 2, 0, 0, 0, -2] -prickles -0.8 0.74833 [0, -1, -1, -1, -2, -1, 0, 0, 0, -2] -pricklier -1.6 0.8 [-1, -2, -2, -2, -2, -1, -2, -1, 0, -3] -prickliest -1.4 1.35647 [-4, -2, -1, 0, -3, -1, -1, 1, -2, -1] -prickliness -0.6 0.91652 [-2, -1, -1, -1, -1, 1, -1, 1, 0, -1] -prickling -0.8 0.6 [-2, -1, 0, -1, 0, 0, -1, -1, -1, -1] -prickly -0.9 1.04403 [-2, -1, -1, -2, -1, 1, -2, -1, 1, -1] -pricks -0.9 1.04403 [-2, 0, -1, -3, -1, 1, 0, -1, -1, -1] -pricky -0.6 1.2 [-2, 1, -1, -2, -1, 2, 0, -1, -1, -1] -pride 1.4 1.11355 [0, 2, 2, 2, 3, 1, -1, 2, 2, 1] -prison -2.3 0.64031 [-3, -3, -2, -2, -1, -2, -3, -3, -2, -2] -prisoner -2.5 1.0247 [-3, -1, -4, -4, -3, -2, -3, -2, -1, -2] -prisoners -2.3 0.78102 [-3, -2, -3, -3, -1, -3, -2, -1, -2, -3] -privilege 1.5 0.80623 [2, 1, 0, 1, 3, 1, 2, 2, 2, 1] -privileged 1.9 0.9434 [2, 3, 3, 2, 3, 1, 1, 2, 0, 2] -privileges 1.6 1.2 [2, 1, 3, 1, 2, 2, 0, 0, 4, 1] -privileging 0.7 1.1 [1, 1, 2, 2, -1, 2, 1, 0, 0, -1] -prize 2.3 1.1 [2, 2, 0, 4, 4, 3, 2, 2, 2, 2] -prized 2.4 0.8 [3, 3, 3, 2, 3, 2, 1, 3, 1, 3] -prizefight -0.1 1.13578 [-2, 2, 0, 0, 0, -2, 0, 1, 0, 0] -prizefighter 1.0 1.0 [0, 2, 0, 0, 0, 2, 0, 2, 2, 2] -prizefighters -0.1 1.04403 [0, 0, -3, 0, 0, 0, 0, 1, 1, 0] -prizefighting 0.4 0.91652 [0, 0, 0, 1, 0, 3, 0, 0, 0, 0] -prizefights 0.3 0.78102 [1, 2, 0, 0, -1, 0, 0, 1, 0, 0] -prizer 1.0 1.0 [0, 3, 0, 0, 2, 1, 2, 1, 0, 1] -prizers 0.8 0.9798 [2, 0, 0, 1, 3, 1, 0, 1, 0, 0] -prizes 2.0 1.09545 [3, 3, 2, 0, 2, 1, 2, 4, 1, 2] -prizewinner 2.3 1.00499 [3, 0, 3, 3, 2, 2, 2, 4, 2, 2] -prizewinners 2.4 1.11355 [4, 2, 2, 2, 0, 4, 2, 3, 3, 2] -prizewinning 3.0 0.7746 [3, 3, 3, 3, 3, 4, 3, 1, 3, 4] -proactive 1.8 0.87178 [2, 3, 3, 1, 1, 1, 1, 3, 1, 2] -problem -1.7 0.64031 [-2, -2, -1, -1, -1, -3, -1, -2, -2, -2] -problematic -1.9 0.53852 [-1, -2, -2, -2, -2, -3, -2, -1, -2, -2] -problematical -1.8 0.6 [-3, -1, -1, -2, -2, -2, -2, -2, -1, -2] -problematically -2.0 1.0 [-2, -1, -3, -1, -1, -2, -4, -3, -1, -2] -problematics -1.3 1.1 [0, -1, -1, 0, -2, -1, -4, -1, -2, -1] -problems -1.7 0.78102 [-2, -1, -1, -3, -2, -1, -3, -1, -1, -2] -profit 1.9 0.7 [2, 3, 2, 1, 2, 1, 3, 1, 2, 2] -profitabilities 1.1 0.7 [1, 1, 3, 1, 1, 1, 1, 0, 1, 1] -profitability 1.1 1.44568 [1, 1, -2, 2, 0, 3, 1, 3, 2, 0] -profitable 1.9 0.9434 [2, 3, 0, 3, 1, 2, 1, 3, 2, 2] -profitableness 2.4 1.11355 [1, 4, 2, 4, 2, 2, 4, 2, 1, 2] -profitably 1.6 0.91652 [1, 2, 0, 3, 1, 3, 1, 1, 2, 2] -profited 1.3 1.00499 [2, 2, 2, 1, 0, 0, 1, 3, 0, 2] -profiteer 0.8 1.6 [2, -2, -1, 3, -1, 2, 1, 2, 0, 2] -profiteered -0.5 1.9105 [0, 0, 2, -2, -3, -2, 3, 0, -3, 0] -profiteering -0.6 2.05913 [-1, 2, -2, -4, -2, 2, 1, -2, 2, -2] -profiteers 0.5 1.5 [-2, 1, -1, -1, 1, -1, 2, 2, 2, 2] -profiter 0.7 1.55242 [2, 2, 2, 1, -1, 1, -1, 3, 0, -2] -profiterole 0.4 0.66332 [0, 0, 0, 0, 0, 1, 0, 1, 2, 0] -profiteroles 0.5 0.92195 [0, 0, -1, 2, 2, 0, 0, 1, 0, 1] -profiting 1.6 0.91652 [1, 0, 3, 2, 1, 2, 3, 1, 1, 2] -profitless -1.5 0.92195 [-2, -2, -3, -1, -1, -1, 0, -1, -1, -3] -profits 1.9 1.04403 [2, 2, 1, 0, 2, 1, 2, 4, 3, 2] -profitwise 0.9 0.83066 [1, 2, 0, 0, 1, 2, 2, 0, 1, 0] -progress 1.8 0.74833 [3, 2, 1, 2, 3, 1, 1, 2, 2, 1] -prominent 1.3 0.45826 [2, 1, 1, 2, 1, 1, 1, 2, 1, 1] -promiscuities -0.8 1.32665 [-1, 0, -2, -2, -1, 2, -3, -1, 0, 0] -promiscuity -1.8 1.07703 [-1, -2, -4, -2, -3, -1, 0, -2, -1, -2] -promiscuous -0.3 1.34536 [2, -3, -1, -1, 0, -1, 0, -1, 1, 1] -promiscuously -1.5 1.28452 [-2, -1, -3, 2, -2, -2, -1, -2, -2, -2] -promiscuousness -0.9 1.37477 [-3, -1, 1, -2, -2, 1, 1, -1, -2, -1] -promise 1.3 0.64031 [1, 0, 1, 1, 2, 2, 1, 1, 2, 2] -promised 1.5 0.92195 [2, 1, 1, 0, 0, 2, 2, 3, 2, 2] -promisee 0.8 0.87178 [2, 1, 0, 0, 0, 2, 0, 2, 1, 0] -promisees 1.1 0.9434 [2, 0, 1, 0, 0, 0, 2, 2, 2, 2] -promiser 1.3 0.9 [2, 1, 1, 0, 0, 2, 2, 3, 1, 1] -promisers 1.6 0.4899 [2, 1, 2, 1, 2, 1, 2, 1, 2, 2] -promises 1.6 0.8 [2, 1, 1, 0, 2, 1, 3, 2, 2, 2] -promising 1.7 0.45826 [1, 2, 2, 1, 2, 2, 1, 2, 2, 2] -promisingly 1.2 0.6 [2, 2, 1, 1, 1, 2, 1, 0, 1, 1] -promisor 1.0 0.63246 [2, 2, 0, 1, 1, 1, 0, 1, 1, 1] -promisors 0.4 0.8 [0, 0, 0, 2, 0, 2, 0, 0, 0, 0] -promissory 0.9 1.13578 [2, 0, 0, 3, 0, 2, 2, 0, 0, 0] -promote 1.6 0.8 [2, 1, 2, 3, 0, 1, 2, 2, 1, 2] -promoted 1.8 0.74833 [2, 2, 1, 1, 1, 2, 2, 1, 3, 3] -promotes 1.4 0.91652 [1, 2, 0, 0, 1, 2, 2, 1, 3, 2] -promoting 1.5 0.67082 [1, 2, 2, 1, 2, 1, 2, 0, 2, 2] -propaganda -1.0 1.54919 [-2, -3, -2, -3, -2, 1, -1, 1, 0, 1] -prosecute -1.7 1.00499 [-2, -2, -2, -1, -1, -2, 0, -1, -4, -2] -prosecuted -1.6 1.95959 [-2, -2, -2, -3, -3, -3, -4, 2, 2, -1] -prosecutes -1.8 1.53623 [-2, -2, -2, -3, -2, -2, -4, 1, 1, -3] -prosecution -2.2 1.07703 [-4, -1, -2, -2, -3, -2, -1, -4, -1, -2] -prospect 1.2 0.87178 [1, 3, 1, 0, 2, 2, 1, 0, 1, 1] -prospects 1.2 0.6 [2, 1, 1, 1, 1, 0, 1, 2, 2, 1] -prosperous 2.1 1.86815 [-3, 3, 3, 2, 4, 2, 3, 3, 3, 1] -protect 1.6 0.8 [1, 3, 1, 1, 1, 1, 3, 2, 1, 2] -protected 1.9 0.7 [1, 1, 2, 3, 2, 2, 2, 1, 3, 2] -protects 1.3 0.78102 [2, 2, 0, 2, 1, 1, 0, 2, 2, 1] -protest -1.0 1.34164 [-2, -1, -1, -2, -1, -2, 1, -2, 2, -2] -protested -0.5 1.62788 [-2, -3, -1, -1, 0, 2, 2, -2, 1, -1] -protesters -0.9 0.7 [0, 0, 0, -1, -2, -2, -1, -1, -1, -1] -protesting -1.8 0.74833 [-2, -2, -1, -2, -1, -1, -2, -1, -3, -3] -protests -0.9 1.57797 [-2, -2, 2, 0, -1, -2, -2, -2, 2, -2] -proud 2.1 0.3 [2, 3, 2, 2, 2, 2, 2, 2, 2, 2] -prouder 2.2 1.16619 [2, 3, 3, 4, 0, 1, 1, 3, 2, 3] -proudest 2.6 0.66332 [4, 2, 2, 2, 2, 3, 2, 3, 3, 3] -proudful 1.9 1.51327 [3, 3, 0, 1, -1, 1, 4, 3, 2, 3] -proudhearted 1.4 0.91652 [2, -1, 1, 2, 2, 1, 2, 2, 2, 1] -proudly 2.6 0.4899 [2, 2, 3, 3, 2, 3, 3, 3, 2, 3] -provoke -1.7 0.64031 [-2, -2, -1, -1, -1, -2, -2, -1, -3, -2] -provoked -1.1 0.83066 [-1, -1, 0, -2, -2, -2, -2, 0, 0, -1] -provokes -1.3 0.78102 [-2, -2, -1, -2, -1, -2, -2, 0, 0, -1] -provoking -0.8 1.249 [-2, -2, -1, -2, 1, -1, 1, 1, -1, -2] -pseudoscience -1.2 1.32665 [-1, -1, -3, -4, 0, 0, -2, 0, 0, -1] -puke -2.4 1.0198 [-1, -3, -3, -2, -4, -4, -2, -1, -2, -2] -puked -1.8 0.6 [-1, -2, -2, -3, -1, -1, -2, -2, -2, -2] -pukes -1.9 0.7 [-1, -2, -3, -3, -1, -1, -2, -2, -2, -2] -puking -1.8 1.46969 [0, -2, -4, -3, -2, -3, 1, -1, -1, -3] -pukka 2.8 0.4 [3, 2, 3, 3, 3, 2, 3, 3, 3, 3] -punish -2.4 0.91652 [-1, -3, -3, -4, -3, -1, -2, -2, -2, -3] -punishabilities -1.7 0.78102 [0, -2, -3, -2, -1, -2, -2, -1, -2, -2] -punishability -1.6 1.49666 [-2, -2, -1, -1, -2, -2, -3, 2, -4, -1] -punishable -1.9 0.7 [-3, -1, -1, -2, -2, -1, -3, -2, -2, -2] -punished -2.0 0.44721 [-2, -2, -1, -2, -2, -2, -2, -2, -3, -2] -punisher -1.9 0.53852 [-3, -1, -2, -2, -2, -2, -2, -1, -2, -2] -punishers -2.6 0.8 [-3, -3, -3, -3, -2, -2, -4, -2, -1, -3] -punishes -2.1 0.7 [-3, -2, -3, -2, -1, -2, -2, -3, -1, -2] -punishing -2.6 0.8 [-2, -3, -3, -3, -4, -1, -3, -2, -2, -3] -punishment -2.2 0.6 [-2, -1, -2, -2, -3, -3, -2, -2, -2, -3] -punishments -1.8 0.6 [-2, -2, -2, -1, -1, -2, -2, -3, -1, -2] -punitive -2.3 0.78102 [-4, -2, -3, -1, -2, -2, -2, -2, -3, -2] -pushy -1.1 0.83066 [-2, -2, -1, -1, -1, 1, -1, -2, -1, -1] -puzzled -0.7 0.45826 [0, 0, -1, -1, 0, -1, -1, -1, -1, -1] -quaking -1.5 0.67082 [-1, -2, -2, -2, -1, 0, -2, -1, -2, -2] -questionable -1.2 0.4 [-1, -1, -1, -1, -1, -1, -1, -2, -2, -1] -questioned -0.4 1.0198 [-2, 0, 0, -1, -1, 2, 0, 0, -1, -1] -questioning -0.4 0.66332 [0, -1, -1, 0, 0, 0, -2, 0, 0, 0] -racism -3.1 0.9434 [-4, -4, -4, -2, -3, -4, -2, -2, -2, -4] -racist -3.0 0.89443 [-1, -3, -3, -4, -3, -4, -4, -2, -3, -3] -racists -2.5 0.92195 [-3, 0, -3, -2, -2, -3, -3, -3, -3, -3] -radian 0.4 0.66332 [0, 0, 0, 0, 0, 0, 1, 2, 0, 1] -radiance 1.4 1.11355 [3, 1, 2, 3, 1, 1, -1, 1, 2, 1] -radiances 1.1 0.53852 [1, 2, 2, 1, 1, 1, 0, 1, 1, 1] -radiancies 0.8 1.16619 [-1, 0, 3, 1, 1, 1, 1, 2, -1, 1] -radiancy 1.4 0.66332 [2, 1, 1, 3, 1, 1, 1, 1, 2, 1] -radians 0.2 0.6 [0, 2, 0, 0, 0, 0, 0, 0, 0, 0] -radiant 2.1 0.83066 [4, 2, 2, 2, 2, 1, 1, 3, 2, 2] -radiantly 1.3 0.78102 [3, 2, 1, 1, 1, 1, 1, 0, 1, 2] -radiants 1.2 0.6 [2, 1, 0, 2, 1, 1, 1, 2, 1, 1] -rage -2.6 0.8 [-3, -2, -2, -3, -3, -4, -1, -2, -3, -3] -raged -2.0 0.63246 [-2, -1, -1, -3, -3, -2, -2, -2, -2, -2] -ragee -0.4 1.42829 [-2, -1, 0, 3, 0, -2, -2, 0, 0, 0] -rageful -2.8 0.6 [-3, -3, -3, -3, -2, -4, -2, -3, -2, -3] -rages -2.1 0.7 [-3, -1, -1, -3, -3, -2, -2, -2, -2, -2] -raging -2.4 1.0198 [-1, -3, -3, -1, -3, -3, -1, -4, -2, -3] -rainy -0.3 0.64031 [-1, 0, 1, 0, 0, 0, -1, 0, -1, -1] -rancid -2.5 1.11803 [-3, -3, -3, -2, -3, 0, -3, -1, -4, -3] -rancidity -2.6 0.8 [-4, -3, -3, -2, -2, -2, -2, -2, -2, -4] -rancidly -2.5 1.20416 [-2, -1, -4, -3, -4, -1, -2, -3, -4, -1] -rancidness -2.6 0.91652 [-3, -4, -2, -3, -4, -2, -3, -1, -2, -2] -rancidnesses -1.6 0.4899 [-2, -1, -2, -1, -1, -2, -2, -2, -1, -2] -rant -1.4 0.66332 [-1, -2, -2, -1, -2, -2, -2, -1, 0, -1] -ranter -1.2 1.16619 [-1, -2, -2, -2, -1, -1, -1, -2, 2, -2] -ranters -1.2 0.87178 [-1, -1, -1, 0, -1, -1, -3, -2, 0, -2] -rants -1.3 0.45826 [-1, -1, -1, -2, -1, -1, -1, -2, -2, -1] -rape -3.7 0.64031 [-4, -2, -4, -4, -4, -4, -4, -4, -3, -4] -raped -3.6 0.4899 [-3, -3, -4, -4, -3, -4, -4, -4, -3, -4] -raper -3.4 0.66332 [-3, -3, -4, -4, -3, -3, -4, -4, -2, -4] -rapers -3.6 0.66332 [-2, -4, -4, -3, -4, -3, -4, -4, -4, -4] -rapes -3.5 0.67082 [-4, -3, -4, -4, -3, -4, -4, -3, -2, -4] -rapeseeds -0.5 1.20416 [0, 0, 0, 0, 0, -4, 0, 0, -1, 0] -raping -3.8 0.4 [-3, -4, -4, -4, -4, -4, -4, -4, -3, -4] -rapist -3.9 0.3 [-4, -4, -4, -4, -4, -4, -3, -4, -4, -4] -rapists -3.3 0.64031 [-3, -3, -4, -3, -4, -3, -4, -2, -4, -3] -rapture 0.6 2.2891 [-2, 2, -2, 3, 3, 4, -1, -1, 2, -2] -raptured 0.9 1.97231 [0, -2, 0, 2, 4, -1, 4, -1, 1, 2] -raptures 0.7 2.05183 [0, -2, 0, 2, 4, -2, 4, -1, 1, 1] -rapturous 1.7 1.95192 [3, 4, 0, 3, 2, 2, 4, -2, -1, 2] -rash -1.7 0.78102 [-2, -1, -1, -3, -2, -2, -1, -1, -1, -3] -ratified 0.6 0.4899 [1, 0, 0, 1, 1, 0, 1, 1, 0, 1] -reach 0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 1, 0, 0] -reached 0.4 0.4899 [1, 0, 0, 0, 1, 1, 0, 1, 0, 0] -reaches 0.2 0.4 [0, 0, 0, 1, 0, 1, 0, 0, 0, 0] -reaching 0.8 0.6 [1, 0, 2, 0, 1, 0, 1, 1, 1, 1] -readiness 1.0 0.63246 [1, 1, 1, 1, 0, 1, 2, 1, 2, 0] -ready 1.5 1.0247 [2, 1, 1, 0, 2, 2, 1, 1, 1, 4] -reassurance 1.5 0.5 [1, 1, 1, 1, 2, 1, 2, 2, 2, 2] -reassurances 1.4 0.8 [0, 1, 1, 2, 1, 1, 1, 2, 3, 2] -reassure 1.4 0.4899 [2, 2, 1, 1, 2, 1, 2, 1, 1, 1] -reassured 1.7 0.45826 [2, 1, 1, 1, 2, 2, 2, 2, 2, 2] -reassures 1.5 0.92195 [2, 1, 1, 2, 2, 2, -1, 2, 2, 2] -reassuring 1.7 1.48661 [3, 3, 2, -2, 1, 3, 3, 2, 1, 1] -reassuringly 1.8 0.87178 [1, 3, 2, 1, 2, 3, 3, 1, 1, 1] -rebel -0.6 1.49666 [-2, -1, -1, 0, -2, -1, 2, 1, 1, -3] -rebeldom -1.5 1.0247 [-2, -2, -1, -3, -2, -2, -1, 1, -1, -2] -rebelled -1.0 1.26491 [-2, -2, 0, -2, 0, -2, -2, -1, -1, 2] -rebelling -1.1 1.51327 [-3, -1, -2, -1, -2, -1, -1, -3, 2, 1] -rebellion -0.5 1.80278 [-2, -2, -1, -1, 3, -1, 1, -3, 2, -1] -rebellions -1.1 1.57797 [-2, -4, -3, 0, 0, -1, 1, -2, -1, 1] -rebellious -1.2 1.249 [-2, -1, -3, -1, -2, -2, 1, -1, 1, -2] -rebelliously -1.8 0.87178 [-3, 0, -2, -2, -1, -2, -3, -1, -2, -2] -rebelliousness -1.2 1.16619 [0, -3, -1, -2, 1, -1, -2, 0, -2, -2] -rebels -0.8 1.07703 [-1, 0, 0, -2, 0, -3, 0, 0, 0, -2] -recession -1.8 1.07703 [-3, -1, -4, -2, -1, -1, -1, -1, -3, -1] -reckless -1.7 0.64031 [-2, -1, -1, -3, -1, -2, -1, -2, -2, -2] -recommend 1.5 0.67082 [1, 1, 1, 1, 2, 3, 2, 2, 1, 1] -recommended 0.8 1.07703 [1, 1, 0, -2, 1, 2, 1, 2, 1, 1] -recommends 0.9 0.9434 [1, 1, 2, 0, 0, 2, 1, -1, 2, 1] -redeemed 1.3 0.9 [2, 1, 2, 2, 1, -1, 2, 1, 2, 1] -reek -2.4 0.66332 [-3, -3, -2, -3, -3, -2, -2, -2, -1, -3] -reeked -2.0 1.09545 [-4, -3, -2, -3, -1, -2, 0, -1, -2, -2] -reeker -1.7 1.1 [0, -2, -1, 0, -3, -3, -2, -1, -3, -2] -reekers -1.5 1.0247 [-3, 0, 0, 0, -2, -2, -2, -2, -2, -2] -reeking -2.0 1.48324 [2, -2, -2, -3, -3, -3, -1, -3, -3, -2] -refuse -1.2 0.4 [-1, -1, -1, -1, -1, -1, -1, -2, -2, -1] -refused -1.2 0.74833 [0, -1, -1, -1, -1, -1, -2, -1, -3, -1] -refusing -1.7 0.64031 [-1, -1, -1, -2, -2, -2, -3, -1, -2, -2] -regret -1.8 0.6 [-2, -2, -2, -2, -1, -3, -1, -1, -2, -2] -regretful -1.9 0.83066 [-1, -2, -1, -2, -1, -2, -1, -3, -3, -3] -regretfully -1.9 0.83066 [-1, -1, -1, -3, -2, -3, -1, -3, -2, -2] -regretfulness -1.6 0.66332 [-1, -3, -1, -1, -1, -2, -1, -2, -2, -2] -regrets -1.5 0.5 [-2, -2, -2, -1, -2, -1, -1, -2, -1, -1] -regrettable -2.3 0.78102 [-3, -1, -2, -1, -3, -2, -3, -3, -2, -3] -regrettably -2.0 0.63246 [-2, -3, -1, -3, -2, -1, -2, -2, -2, -2] -regretted -1.6 0.4899 [-2, -1, -2, -2, -2, -2, -1, -1, -1, -2] -regretter -1.6 0.66332 [-2, -1, -2, -2, -3, -2, -1, -1, -1, -1] -regretters -2.0 0.89443 [-1, -2, -2, -2, -4, -3, -1, -1, -2, -2] -regretting -1.7 0.78102 [-3, -2, -2, -1, -3, -1, -1, -1, -2, -1] -reinvigorate 2.3 0.78102 [3, 3, 3, 2, 3, 1, 2, 1, 2, 3] -reinvigorated 1.9 1.13578 [2, 2, 3, 1, 2, 3, 3, -1, 2, 2] -reinvigorates 1.8 0.9798 [2, 2, 3, 0, 2, 2, 3, 0, 2, 2] -reinvigorating 1.7 0.64031 [1, 2, 1, 1, 2, 2, 2, 1, 3, 2] -reinvigoration 2.2 0.4 [2, 2, 2, 3, 2, 3, 2, 2, 2, 2] -reject -1.7 0.64031 [-1, -2, -2, -2, -1, -3, -1, -1, -2, -2] -rejected -2.3 0.45826 [-3, -2, -3, -3, -2, -2, -2, -2, -2, -2] -rejectee -2.3 0.45826 [-3, -2, -2, -3, -2, -3, -2, -2, -2, -2] -rejectees -1.8 0.4 [-2, -2, -1, -2, -2, -2, -2, -2, -2, -1] -rejecter -1.6 0.66332 [-2, -1, -1, -3, -2, -2, -1, -1, -1, -2] -rejecters -1.8 0.6 [-2, -3, -1, -1, -2, -1, -2, -2, -2, -2] -rejecting -2.0 0.7746 [-1, -2, -3, -1, -2, -3, -2, -1, -3, -2] -rejectingly -1.7 0.64031 [-1, -2, -2, -2, -1, -2, -2, -1, -3, -1] -rejection -2.5 0.67082 [-3, -3, -2, -4, -3, -2, -2, -2, -2, -2] -rejections -2.1 0.53852 [-3, -2, -2, -2, -1, -2, -3, -2, -2, -2] -rejective -1.8 0.6 [-3, -2, -2, -2, -1, -1, -2, -2, -1, -2] -rejector -1.8 0.74833 [-2, -1, -2, -3, -1, -2, -1, -2, -3, -1] -rejects -2.2 0.4 [-3, -2, -2, -2, -2, -3, -2, -2, -2, -2] -rejoice 1.9 0.9434 [2, 3, 1, 3, 1, 3, 1, 3, 1, 1] -rejoiced 2.0 0.63246 [2, 1, 2, 3, 2, 2, 3, 1, 2, 2] -rejoices 2.1 0.7 [2, 1, 2, 3, 2, 3, 3, 2, 2, 1] -rejoicing 2.8 0.4 [3, 3, 2, 3, 3, 3, 2, 3, 3, 3] -relax 1.9 1.13578 [2, 1, 1, 1, 4, 4, 2, 1, 1, 2] -relaxant 1.0 0.89443 [2, 1, 0, 0, 1, 0, 1, 3, 1, 1] -relaxants 0.7 0.9 [0, 1, 1, 0, -1, 2, 1, 2, 1, 0] -relaxation 2.4 0.4899 [3, 2, 3, 2, 2, 3, 3, 2, 2, 2] -relaxations 1.0 0.89443 [-1, 0, 2, 1, 1, 2, 1, 2, 1, 1] -relaxed 2.2 0.87178 [2, 3, 1, 3, 3, 3, 1, 2, 1, 3] -relaxedly 1.5 0.5 [2, 2, 1, 1, 2, 1, 2, 2, 1, 1] -relaxedness 2.0 0.63246 [2, 2, 3, 1, 3, 2, 2, 2, 1, 2] -relaxer 1.6 0.8 [0, 2, 1, 2, 1, 3, 1, 2, 2, 2] -relaxers 1.4 0.4899 [2, 1, 1, 1, 2, 2, 2, 1, 1, 1] -relaxes 1.5 0.5 [2, 1, 1, 1, 1, 2, 2, 2, 1, 2] -relaxin 1.7 0.64031 [2, 2, 1, 2, 0, 2, 2, 2, 2, 2] -relaxing 2.2 0.6 [1, 2, 2, 2, 2, 3, 3, 3, 2, 2] -relaxins 1.2 1.4 [1, 3, 2, 1, 0, 1, -2, 3, 2, 1] -relentless 0.2 1.07703 [3, -1, 0, -1, 0, 1, 0, 0, 0, 0] -reliant 0.5 1.20416 [0, 2, -1, 1, 0, 1, 2, -1, 2, -1] -relief 2.1 0.53852 [2, 2, 2, 3, 2, 3, 2, 1, 2, 2] -reliefs 1.3 0.78102 [1, 2, 2, 2, 2, 2, 0, 0, 1, 1] -relievable 1.1 1.22066 [1, -2, 1, 1, 1, 1, 3, 2, 1, 2] -relieve 1.5 0.5 [1, 2, 1, 2, 1, 1, 2, 2, 1, 2] -relieved 1.6 0.66332 [2, 1, 2, 1, 1, 3, 2, 1, 1, 2] -relievedly 1.4 0.4899 [1, 2, 1, 1, 1, 2, 2, 2, 1, 1] -reliever 1.5 0.80623 [2, 1, 2, 2, 1, 2, 0, 1, 1, 3] -relievers 1.0 0.63246 [1, 1, 1, 1, 2, 0, 2, 0, 1, 1] -relieves 1.5 0.80623 [2, 1, 2, 2, 1, 2, 0, 1, 1, 3] -relieving 1.5 1.0247 [2, 2, 1, 2, 3, -1, 2, 1, 1, 2] -relievo 1.3 1.00499 [0, 2, 1, 2, 2, -1, 2, 2, 2, 1] -relishing 1.6 0.8 [1, 2, 1, 3, 2, 3, 1, 1, 1, 1] -reluctance -1.4 0.4899 [-2, -2, -1, -1, -1, -1, -2, -1, -2, -1] -reluctancy -1.6 0.8 [-3, -2, -1, -1, -1, -1, -2, -1, -3, -1] -reluctant -1.0 0.7746 [0, -1, 0, -1, -1, 0, -1, -2, -2, -2] -reluctantly -0.4 1.42829 [-1, 2, -1, -2, -2, -1, 1, -1, 2, -1] -remarkable 2.6 1.0198 [3, 4, 3, 2, 2, 3, 3, 0, 3, 3] -remorse -1.1 1.51327 [-3, -1, -3, 1, 2, -2, -1, -1, -2, -1] -remorseful -0.9 2.07123 [-1, 1, -2, -3, 2, -1, -3, -2, 3, -3] -remorsefully -0.7 1.34536 [-1, -1, 0, -1, -2, -1, -1, 1, -3, 2] -remorsefulness -0.7 1.61555 [-1, -2, 2, -2, -2, -1, 0, -3, 2, 0] -remorseless -2.3 0.64031 [-4, -2, -2, -2, -3, -2, -2, -2, -2, -2] -remorselessly -2.0 1.09545 [-3, -3, -3, -2, -1, -1, -4, -1, -1, -1] -remorselessness -2.8 1.16619 [-3, -4, -2, -2, -3, -4, -1, -1, -4, -4] -repetitive -1.0 0.06325 [-1, -1, 0, -2, -1, -2, -1, -1, 0, -1] -repress -1.4 0.66332 [-1, -1, -3, -2, -1, -1, -2, -1, -1, -1] -repressed -1.3 0.78102 [-1, 0, -3, -1, -1, -2, -1, -1, -2, -1] -represses -1.3 1.00499 [-1, 0, -3, -1, 0, -3, -1, -1, -2, -1] -repressible -1.5 0.92195 [-1, -2, -3, -1, 0, -1, -3, -1, -2, -1] -repressing -1.8 0.6 [-1, -2, -2, -2, -1, -3, -2, -1, -2, -2] -repression -1.6 0.91652 [-2, -2, -1, -1, -1, -1, -4, -1, -2, -1] -repressions -1.7 1.00499 [-2, -3, -1, -2, -2, -3, -2, 0, 0, -2] -repressive -1.4 1.11355 [-3, -1, -1, -2, -1, -3, 1, -2, -1, -1] -repressively -1.7 0.45826 [-2, -1, -2, -2, -2, -2, -2, -2, -1, -1] -repressiveness -1.0 1.73205 [-2, -1, -2, -3, -1, -1, 1, -3, 3, -1] -repressor -1.4 1.28062 [-1, 0, -3, -1, -2, -4, 0, -1, 0, -2] -repressors -2.2 1.66132 [-2, -4, 0, -2, -1, -3, -4, -3, 1, -4] -repressurize -0.3 0.64031 [0, 0, 0, 0, 0, 0, -2, 0, -1, 0] -repressurized 0.1 0.3 [0, 0, 0, 0, 1, 0, 0, 0, 0, 0] -repressurizes 0.1 0.3 [0, 0, 0, 0, 1, 0, 0, 0, 0, 0] -repressurizing -0.1 0.3 [0, 0, 0, 0, -1, 0, 0, 0, 0, 0] -repulse -2.8 0.4 [-3, -3, -3, -3, -2, -3, -3, -3, -2, -3] -repulsed -2.2 0.9798 [0, -2, -2, -2, -3, -3, -1, -3, -3, -3] -rescue 2.3 0.78102 [1, 3, 1, 3, 2, 3, 3, 2, 2, 3] -rescued 1.8 1.53623 [3, 2, 2, -2, 3, 2, 1, 4, 1, 2] -rescues 1.3 0.78102 [3, 2, 0, 2, 1, 1, 1, 1, 1, 1] -resent -0.7 1.26886 [-2, -2, 0, -1, -1, -1, -2, 1, 2, -1] -resented -1.6 1.35647 [-2, -3, -2, -2, -1, -1, 2, -3, -2, -2] -resentence -1.0 0.7746 [-1, 0, -1, -1, 0, -2, -1, 0, -2, -2] -resentenced -0.8 0.9798 [0, -2, -1, 0, -1, 0, 0, 0, -3, -1] -resentences -0.6 0.8 [0, -2, -1, 0, -1, 0, 0, 0, -2, 0] -resentencing 0.2 0.87178 [-1, -1, 0, 1, 0, 0, 1, 2, 0, 0] -resentful -2.1 0.83066 [-3, -1, -2, -3, -1, -1, -3, -2, -2, -3] -resentfully -1.4 1.11355 [-1, -2, -1, -1, -3, 1, -1, -3, -1, -2] -resentfulness -2.0 0.7746 [-2, -2, -3, -3, -2, -3, -2, -1, -1, -1] -resenting -1.2 1.72047 [-2, -1, -2, -2, -1, -3, -3, 2, 2, -2] -resentment -1.9 0.83066 [-1, -3, -2, -3, -2, -3, -1, -1, -1, -2] -resentments -1.9 0.7 [-2, -1, -2, -3, -1, -2, -2, -2, -1, -3] -resents -1.2 1.32665 [-2, -1, -1, -3, 1, -1, 1, -3, -2, -1] -resign -1.4 0.66332 [-2, -1, -3, -1, -1, -1, -1, -2, -1, -1] -resignation -1.2 0.4 [-1, -1, -1, -2, -1, -1, -1, -1, -2, -1] -resignations -1.2 0.6 [0, -1, -1, -2, -2, -2, -1, -1, -1, -1] -resigned -1.0 0.63246 [-2, -1, 0, -1, -2, -1, -1, -1, 0, -1] -resignedly -0.7 1.26886 [-3, -1, -1, -1, -1, 1, 1, 1, -2, -1] -resignedness -0.8 1.07703 [-1, -2, 1, -2, -1, -1, 0, -2, -1, 1] -resigner -1.2 0.6 [-2, -1, 0, -1, -2, -2, -1, -1, -1, -1] -resigners -1.0 1.09545 [-1, 0, -1, -3, -1, 0, 0, -1, -3, 0] -resigning -0.9 1.22066 [-1, -1, -1, -1, -1, 0, -1, -3, -2, 2] -resigns -1.3 0.9 [0, -1, -1, 0, -2, -1, -3, -1, -2, -2] -resolute 1.1 0.53852 [2, 1, 0, 1, 1, 1, 2, 1, 1, 1] -resolvable 1.0 0.0 [1, 1, 1, 1, 1, 1, 1, 1, 1, 1] -resolve 1.6 0.66332 [2, 1, 1, 2, 2, 1, 3, 1, 1, 2] -resolved 0.7 0.78102 [1, 2, 0, 1, 1, 0, 2, 0, 0, 0] -resolvent 0.7 0.78102 [1, 0, 1, 2, 0, -1, 1, 1, 1, 1] -resolvents 0.4 0.66332 [2, 0, 0, 1, 0, 0, 1, 0, 0, 0] -resolver 0.7 0.78102 [1, 2, 0, 1, 1, 0, 2, 0, 0, 0] -resolvers 1.4 0.4899 [2, 1, 2, 1, 1, 1, 2, 1, 2, 1] -resolves 0.7 0.78102 [1, 2, 0, 1, 1, 0, 2, 0, 0, 0] -resolving 1.6 0.4899 [2, 2, 1, 2, 2, 1, 1, 1, 2, 2] -respect 2.1 0.53852 [2, 2, 2, 2, 3, 3, 2, 2, 1, 2] -respectabilities 1.8 0.4 [2, 2, 2, 1, 2, 2, 2, 1, 2, 2] -respectability 2.4 0.8 [4, 1, 3, 2, 3, 3, 2, 2, 2, 2] -respectable 1.9 0.7 [2, 2, 2, 2, 1, 3, 3, 1, 1, 2] -respectableness 1.2 1.32665 [2, 1, 1, 0, 3, 2, -2, 2, 2, 1] -respectably 1.7 0.78102 [2, 2, 1, 3, 1, 3, 2, 1, 1, 1] -respected 2.1 0.7 [2, 2, 1, 2, 3, 1, 2, 3, 3, 2] -respecter 2.1 0.53852 [3, 2, 2, 2, 2, 2, 1, 3, 2, 2] -respecters 1.6 0.8 [2, 1, 2, 2, 3, 1, 2, 2, 0, 1] -respectful 2.0 0.7746 [1, 1, 3, 2, 2, 3, 1, 2, 3, 2] -respectfully 1.7 0.64031 [1, 2, 1, 2, 2, 2, 1, 3, 1, 2] -respectfulness 1.9 1.37477 [4, 2, 2, 1, 2, 4, -1, 1, 2, 2] -respectfulnesses 1.3 1.18743 [1, 1, 2, 2, 2, 2, 2, 1, -2, 2] -respecting 2.2 0.6 [1, 3, 2, 3, 2, 2, 3, 2, 2, 2] -respective 1.8 1.16619 [2, 2, 3, 0, 1, 3, 3, 1, 0, 3] -respectively 1.4 0.91652 [0, 0, 2, 2, 0, 2, 2, 2, 2, 2] -respectiveness 1.1 1.04403 [0, 2, 1, 0, 1, 0, 2, 2, 0, 3] -respects 1.3 1.00499 [2, 0, 0, 0, 2, 1, 2, 1, 2, 3] -responsible 1.3 1.1 [1, 1, 0, 4, 2, 2, 1, 0, 1, 1] -responsive 1.5 0.92195 [3, 1, 1, 0, 1, 1, 2, 3, 2, 1] -restful 1.5 0.67082 [1, 1, 1, 1, 2, 1, 2, 1, 2, 3] -restless -1.1 0.3 [-1, -1, -1, -1, -1, -1, -2, -1, -1, -1] -restlessly -1.4 0.91652 [-1, -4, -1, -1, -1, -2, -1, -1, -1, -1] -restlessness -1.2 0.74833 [-3, -1, -1, 0, -1, -2, -1, -1, -1, -1] -restore 1.2 0.9798 [1, 1, 2, 2, 2, 2, 1, -1, 0, 2] -restored 1.4 0.91652 [2, 2, 1, 2, 1, 2, 2, 1, -1, 2] -restores 1.2 0.6 [2, 1, 1, 2, 1, 0, 1, 1, 2, 1] -restoring 1.2 0.4 [2, 1, 1, 1, 1, 2, 1, 1, 1, 1] -restrict -1.6 0.8 [-3, -1, -1, -1, -3, -1, -2, -1, -1, -2] -restricted -1.6 0.4899 [-1, -2, -1, -1, -1, -2, -2, -2, -2, -2] -restricting -1.6 0.4899 [-2, -2, -2, -2, -1, -2, -1, -1, -2, -1] -restriction -1.1 0.9434 [-1, -1, -1, -1, -3, 1, -2, -1, -1, -1] -restricts -1.3 1.1 [-2, -2, -3, -1, -1, -2, 1, -1, -2, 0] -retained 0.1 0.7 [-1, 1, 1, 1, 0, -1, 0, 0, 0, 0] -retard -2.4 0.8 [-2, -2, -2, -1, -3, -2, -4, -3, -3, -2] -retarded -2.7 1.26886 [-4, -1, -3, -3, -4, -4, -2, -1, -1, -4] -retreat 0.8 1.07703 [2, 2, 0, 0, -1, 1, 2, 0, 2, 0] -revenge -2.4 0.66332 [-2, -3, -2, -3, -3, -3, -2, -1, -2, -3] -revenged -0.9 1.37477 [-2, -3, -2, -1, -1, 2, -1, 1, -1, -1] -revengeful -2.4 0.4899 [-2, -2, -2, -3, -3, -2, -3, -3, -2, -2] -revengefully -1.4 2.00998 [-3, -2, -2, -2, 3, 2, -3, -3, -2, -2] -revengefulness -2.2 0.87178 [-2, -3, -3, -2, -2, -2, -1, -4, -1, -2] -revenger -2.1 0.83066 [-2, -3, -2, -1, -1, -2, -3, -3, -1, -3] -revengers -2.0 0.44721 [-2, -2, -3, -2, -2, -2, -1, -2, -2, -2] -revenges -1.9 0.7 [-2, -3, -2, -1, -1, -2, -3, -2, -1, -2] -revered 2.3 1.1 [3, 3, 1, 3, 3, 3, 0, 3, 3, 1] -revive 1.4 1.11355 [4, 0, 2, 1, 1, 0, 2, 2, 1, 1] -revives 1.6 0.4899 [1, 1, 2, 2, 1, 2, 2, 2, 1, 2] -reward 2.7 0.78102 [3, 4, 1, 2, 3, 3, 2, 3, 3, 3] -rewardable 2.0 1.0 [3, 1, 4, 3, 1, 2, 1, 2, 2, 1] -rewarded 2.2 0.74833 [1, 2, 3, 2, 2, 4, 2, 2, 2, 2] -rewarder 1.6 0.8 [1, 2, 3, 1, 1, 3, 2, 1, 1, 1] -rewarders 1.9 0.83066 [1, 2, 2, 1, 3, 3, 1, 2, 1, 3] -rewarding 2.4 0.8 [3, 4, 2, 2, 1, 3, 3, 2, 2, 2] -rewardingly 2.4 0.8 [3, 2, 3, 4, 3, 2, 2, 2, 1, 2] -rewards 2.1 0.83066 [2, 1, 3, 4, 2, 2, 2, 2, 1, 2] -rich 2.6 0.8 [2, 3, 2, 4, 4, 3, 2, 2, 2, 2] -richened 1.9 0.83066 [3, 2, 2, 1, 3, 1, 2, 3, 1, 1] -richening 1.0 1.34164 [2, 2, 0, 0, -1, 1, 2, 3, -1, 2] -richens 0.8 0.9798 [1, 0, 3, 0, 0, 0, 1, 2, 1, 0] -richer 2.4 1.2 [1, 4, 2, 1, 2, 4, 4, 1, 3, 2] -riches 2.4 1.0198 [2, 4, 1, 1, 2, 4, 3, 2, 3, 2] -richest 2.4 1.11355 [4, 4, 2, 2, 3, 0, 2, 2, 3, 2] -richly 1.9 0.53852 [2, 2, 2, 2, 3, 1, 2, 2, 1, 2] -richness 2.2 0.74833 [2, 3, 2, 2, 2, 2, 2, 1, 4, 2] -richnesses 2.1 0.9434 [2, 1, 2, 2, 3, 1, 3, 1, 4, 2] -richweed 0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 1, 0, 0] -richweeds -0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 0, 0, -1] -ridicule -2.0 0.63246 [-2, -2, -2, -2, -3, -2, -1, -2, -1, -3] -ridiculed -1.5 0.5 [-1, -1, -1, -2, -2, -2, -1, -2, -1, -2] -ridiculer -1.6 0.91652 [-1, -1, -1, -2, -2, 0, -1, -3, -2, -3] -ridiculers -1.6 0.66332 [-2, -1, -1, -2, -3, -2, -1, -2, -1, -1] -ridicules -1.8 0.6 [-1, -1, -2, -2, -2, -2, -1, -2, -2, -3] -ridiculing -1.8 0.6 [-2, -3, -2, -1, -1, -2, -2, -1, -2, -2] -ridiculous -1.5 0.67082 [-3, -2, -1, -1, -2, -1, -2, -1, -1, -1] -ridiculously -1.4 0.8 [-1, -2, -1, 0, -2, -1, -1, -3, -1, -2] -ridiculousness -1.1 1.51327 [-1, -1, -1, -2, -1, 3, -3, -2, -1, -2] -ridiculousnesses -1.6 1.11355 [-3, 0, -2, -2, -1, -1, -1, -4, -1, -1] -rig -0.5 1.0247 [0, 0, 0, 0, -2, 0, 0, 0, -3, 0] -rigged -1.5 1.0247 [-2, -3, -2, -1, -1, -2, 1, -1, -2, -2] -rigid -0.5 0.67082 [-2, -1, 0, 0, 0, 0, 0, -1, -1, 0] -rigidification -1.1 0.9434 [-1, -2, 0, 0, 0, -2, -2, -2, 0, -2] -rigidifications -0.8 0.9798 [-2, -1, 0, 0, -2, -1, 0, 1, -2, -1] -rigidified -0.7 1.00499 [0, -1, 0, 0, 0, 0, -2, 0, -1, -3] -rigidifies -0.6 0.8 [0, -1, 0, 0, 0, 0, -2, 0, -1, -2] -rigidify -0.3 0.64031 [0, 0, 0, 0, -1, 0, 0, 0, -2, 0] -rigidities -0.7 0.78102 [0, -1, 0, 0, 0, 0, -2, -1, -1, -2] -rigidity -0.7 0.64031 [-1, 0, -1, 0, -1, 0, -2, 0, -1, -1] -rigidly -0.7 0.45826 [-1, -1, -1, -1, 0, 0, -1, 0, -1, -1] -rigidness -0.3 1.00499 [0, -1, -1, 0, 2, -1, -1, -1, 1, -1] -rigorous -1.1 1.51327 [-2, -3, 1, 0, 1, 0, -1, -1, -3, -3] -rigorously -0.4 1.28062 [0, 2, 1, 0, -1, 0, -1, -1, -3, -1] -riot -2.6 1.0198 [-3, 0, -3, -2, -3, -3, -3, -4, -3, -2] -riots -2.3 0.78102 [-2, -3, -3, -2, -1, -1, -3, -2, -3, -3] -risk -1.1 0.7 [-1, -1, 0, -2, -1, 0, -2, -2, -1, -1] -risked -0.9 0.7 [-1, -2, 0, 0, -1, 0, -2, -1, -1, -1] -risker -0.8 0.4 [-1, -1, -1, 0, -1, 0, -1, -1, -1, -1] -riskier -1.4 0.91652 [0, -3, -1, 0, -1, -2, -1, -2, -2, -2] -riskiest -1.5 1.0247 [-2, -3, -1, -1, -3, 0, -1, -2, 0, -2] -riskily -0.7 1.34536 [-1, -2, -1, -1, 3, 0, -1, -1, -1, -2] -riskiness -1.3 1.00499 [-3, -1, -1, 0, -1, 0, -1, -3, -2, -1] -riskinesses -1.6 0.91652 [-2, -1, -1, 0, -3, -1, -2, -1, -3, -2] -risking -1.3 1.1 [0, 0, -2, 0, -1, -3, -3, -1, -2, -1] -riskless 1.3 0.9 [2, 1, 0, 1, 1, 1, 2, 3, 0, 2] -risks -1.1 0.9434 [-1, 0, -1, -1, 0, 0, -2, -1, -3, -2] -risky -0.8 0.9798 [-1, 1, -1, -1, -1, 0, 0, -1, -3, -1] -rob -2.6 0.8 [-2, -4, -3, -2, -3, -4, -2, -2, -2, -2] -robber -2.6 1.0198 [-4, -1, -2, -3, -2, -1, -4, -3, -3, -3] -robed -0.7 0.9 [-2, 0, 0, 0, 0, -2, 0, -2, -1, 0] -robing -1.5 1.56525 [0, 0, 0, 0, -2, -3, -3, -4, -3, 0] -robs -2.0 1.0 [-2, -1, -3, -2, -2, -1, -4, -3, -1, -1] -robust 1.4 1.42829 [1, 0, 0, 1, 4, 0, 2, 3, 3, 0] -roflcopter 2.1 0.53852 [2, 2, 2, 1, 3, 2, 3, 2, 2, 2] -romance 2.6 0.66332 [2, 3, 4, 2, 3, 2, 3, 2, 3, 2] -romanced 2.2 0.87178 [2, 3, 2, 4, 2, 1, 2, 3, 1, 2] -romancer 1.3 1.1 [0, 0, 2, 2, 2, 2, 3, 2, 0, 0] -romancers 1.7 1.00499 [0, 2, 2, 2, 2, 2, 1, 3, 0, 3] -romances 1.3 0.9 [0, 1, 2, 2, 2, 2, 2, 2, 0, 0] -romancing 2.0 0.89443 [4, 1, 1, 2, 2, 2, 2, 1, 3, 2] -romantic 1.7 0.78102 [2, 2, 2, 1, 2, 3, 2, 2, 0, 1] -romantically 1.8 0.87178 [3, 1, 2, 0, 1, 2, 2, 2, 3, 2] -romanticise 1.7 1.61555 [-1, 4, 2, 1, 3, 1, 3, 3, 2, -1] -romanticised 1.7 0.9 [2, 2, 2, 2, 2, 2, 3, 0, 2, 0] -romanticises 1.3 1.1 [2, 2, 1, 1, 1, 2, 3, -1, 2, 0] -romanticising 2.7 0.78102 [3, 3, 3, 2, 1, 3, 2, 3, 4, 3] -romanticism 2.2 1.32665 [1, 4, 2, 1, 3, 1, 3, 3, 4, 0] -romanticisms 2.1 0.9434 [2, 3, 2, 1, 2, 3, 3, 2, 3, 0] -romanticist 1.9 1.3 [1, 4, 2, 0, 3, 1, 2, 3, 3, 0] -romanticists 1.3 1.00499 [2, 0, 0, 1, 3, 3, 1, 1, 1, 1] -romanticization 1.5 1.36015 [1, 3, 2, 2, -1, 2, 0, 1, 4, 1] -romanticizations 2.0 1.0 [4, 1, 3, 1, 2, 3, 1, 2, 2, 1] -romanticize 1.8 0.9798 [2, 2, 1, 1, 2, 1, 3, 3, 3, 0] -romanticized 0.9 1.22066 [0, 1, 1, 3, -1, 0, 1, 1, 3, 0] -romanticizes 1.8 0.87178 [2, 3, 2, 1, 2, 3, 0, 1, 2, 2] -romanticizing 1.2 1.07703 [0, 1, 2, 1, 3, 0, 1, 1, 0, 3] -romantics 1.9 0.83066 [2, 3, 2, 1, 0, 2, 3, 2, 2, 2] -rotten -2.3 0.78102 [-2, -3, -1, -3, -3, -1, -3, -2, -3, -2] -rude -2.0 0.44721 [-2, -1, -3, -2, -2, -2, -2, -2, -2, -2] -rudely -2.2 0.87178 [-3, -2, -3, -1, -2, -4, -2, -2, -1, -2] -rudeness -1.5 0.67082 [-2, -1, -1, -1, -1, -3, -2, -2, -1, -1] -ruder -2.1 0.83066 [-2, -1, -4, -2, -3, -1, -2, -2, -2, -2] -ruderal -0.8 1.46969 [-3, 0, -1, -2, 0, -1, -3, 0, 2, 0] -ruderals -0.4 0.66332 [0, -1, 0, -2, 0, -1, 0, 0, 0, 0] -rudesby -2.0 0.7746 [-2, -3, -2, -2, -1, -3, -1, -1, -2, -3] -rudest -2.5 0.5 [-3, -2, -3, -3, -2, -2, -2, -3, -2, -3] -ruin -2.8 0.87178 [-3, -3, -1, -4, -4, -3, -3, -2, -2, -3] -ruinable -1.6 0.8 [-1, -2, -1, -3, -1, -3, -1, -1, -2, -1] -ruinate -2.8 0.87178 [-4, -4, -3, -3, -1, -3, -3, -3, -2, -2] -ruinated -1.5 1.56525 [0, -4, 0, -4, -1, -2, 0, -1, -3, 0] -ruinates -1.5 1.56525 [0, -4, 0, -4, -1, -2, 0, -1, -3, 0] -ruinating -1.5 1.20416 [-2, -2, -2, -3, 0, -1, 1, -3, -1, -2] -ruination -2.7 1.00499 [-4, -4, -3, -3, -2, -1, -3, -3, -3, -1] -ruinations -1.6 1.35647 [-2, -2, -3, -4, 0, -1, 1, -2, -1, -2] -ruined -2.1 0.7 [-3, -2, -2, -1, -2, -2, -3, -3, -1, -2] -ruiner -2.0 0.63246 [-1, -3, -2, -2, -1, -2, -3, -2, -2, -2] -ruing -1.6 0.91652 [-2, -1, -2, -1, -1, -1, -3, 0, -3, -2] -ruining -1.0 1.94936 [-3, -3, 0, -2, 1, -3, 2, -2, 2, -2] -ruinous -2.7 0.78102 [-2, -3, -3, -3, -3, -4, -2, -3, -1, -3] -ruinously -2.6 0.8 [-3, -2, -2, -3, -1, -3, -4, -2, -3, -3] -ruinousness -1.0 1.09545 [-1, -2, -3, -1, -1, -2, 1, 0, -1, 0] -ruins -1.9 0.9434 [-1, -2, -1, -2, -1, -2, -4, -1, -3, -2] -sabotage -2.4 0.91652 [-3, -3, -3, -2, -2, -4, -2, -3, -1, -1] -sad -2.1 0.9434 [-1, -1, -2, -2, -3, -2, -3, -2, -4, -1] -sadden -2.6 0.4899 [-2, -3, -2, -3, -2, -3, -2, -3, -3, -3] -saddened -2.4 0.4899 [-3, -2, -3, -2, -3, -3, -2, -2, -2, -2] -saddening -2.2 0.4 [-3, -2, -2, -2, -2, -2, -3, -2, -2, -2] -saddens -1.9 0.7 [-3, -1, -1, -1, -2, -2, -2, -2, -3, -2] -sadder -2.4 0.91652 [-2, -2, -3, -4, -3, -1, -3, -1, -2, -3] -saddest -3.0 0.63246 [-4, -3, -2, -3, -3, -2, -3, -4, -3, -3] -sadly -1.8 0.6 [-2, -2, -2, -1, -2, -3, -2, -1, -1, -2] -sadness -1.9 0.3 [-2, -1, -2, -2, -2, -2, -2, -2, -2, -2] -safe 1.9 0.3 [2, 1, 2, 2, 2, 2, 2, 2, 2, 2] -safecracker -0.7 1.61555 [-3, -2, 0, -3, 0, -2, 0, 1, 2, 0] -safecrackers -0.9 1.04403 [-1, 0, -2, 0, -1, 0, 0, -3, 0, -2] -safecracking -0.9 0.9434 [0, 0, 0, 0, -2, 0, -1, -2, -2, -2] -safecrackings -0.7 1.67631 [-2, -1, -2, -4, 2, -1, -1, 0, 1, 1] -safeguard 1.6 0.4899 [2, 2, 1, 1, 1, 2, 2, 2, 2, 1] -safeguarded 1.5 0.92195 [1, 2, 2, 0, 2, 0, 3, 1, 2, 2] -safeguarding 1.1 0.7 [2, 1, 1, 0, 1, 0, 2, 1, 1, 2] -safeguards 1.4 0.66332 [1, 2, 1, 1, 0, 2, 2, 2, 2, 1] -safekeeping 1.4 0.66332 [3, 1, 1, 2, 1, 1, 2, 1, 1, 1] -safelight 1.1 1.22066 [0, 3, 0, 2, 0, 3, 0, 2, 1, 0] -safelights 0.8 1.07703 [0, 3, 1, 0, 0, 2, 0, 2, 0, 0] -safely 2.2 0.74833 [2, 2, 2, 3, 4, 2, 2, 1, 2, 2] -safeness 1.5 0.67082 [1, 1, 1, 1, 3, 1, 2, 2, 2, 1] -safer 1.8 0.6 [2, 1, 2, 3, 2, 2, 1, 1, 2, 2] -safes 0.4 0.8 [0, 0, 2, 0, 0, 0, 0, 0, 2, 0] -safest 1.7 1.61555 [2, 2, 2, 2, -3, 3, 3, 2, 2, 2] -safeties 1.5 1.0247 [2, 0, 1, 3, 2, 1, 3, 1, 0, 2] -safety 1.8 0.6 [2, 2, 2, 2, 1, 1, 2, 3, 1, 2] -safetyman 0.3 0.64031 [0, 0, 0, 0, 2, 0, 1, 0, 0, 0] -salient 1.1 1.22066 [1, 3, 0, -1, 0, 1, 2, 1, 1, 3] -sappy -1.0 1.18322 [-2, -1, 2, -2, -2, 0, -1, -1, -2, -1] -sarcasm -0.9 0.7 [0, -2, -1, -1, 0, 0, -1, -1, -2, -1] -sarcasms -0.9 0.7 [0, -1, 0, -1, -1, -2, 0, -1, -1, -2] -sarcastic -1.0 0.7746 [-1, -1, -1, -1, -1, -1, -1, -2, 1, -2] -sarcastically -1.1 1.37477 [-1, -4, 1, -1, -1, -2, 1, -2, -1, -1] -satisfaction 1.9 0.9434 [1, 3, 2, 4, 2, 1, 1, 1, 2, 2] -satisfactions 2.1 0.7 [3, 3, 3, 1, 2, 2, 1, 2, 2, 2] -satisfactorily 1.6 1.11355 [1, 2, 2, -1, 2, 1, 3, 3, 1, 2] -satisfactoriness 1.5 0.5 [1, 2, 1, 2, 2, 1, 2, 1, 2, 1] -satisfactory 1.5 0.67082 [2, 3, 1, 1, 1, 2, 2, 1, 1, 1] -satisfiable 1.9 0.83066 [3, 1, 2, 1, 2, 3, 1, 2, 3, 1] -satisfied 1.8 0.6 [2, 2, 2, 1, 1, 2, 3, 1, 2, 2] -satisfies 1.8 0.6 [3, 1, 2, 1, 1, 2, 2, 2, 2, 2] -satisfy 2.0 0.63246 [3, 2, 2, 2, 2, 1, 1, 2, 3, 2] -satisfying 2.0 1.48324 [2, 3, 2, 1, 3, 3, 3, 2, -2, 3] -satisfyingly 1.9 0.9434 [1, 2, 2, 1, 2, 1, 4, 1, 3, 2] -savage -2.0 1.73205 [-3, -4, -3, 1, -2, -1, -3, -4, -2, 1] -savaged -2.0 1.34164 [-1, 0, -4, -3, -3, -3, -2, 0, -1, -3] -savagely -2.2 0.74833 [-2, -1, -3, -2, -2, -1, -2, -3, -3, -3] -savageness -2.6 1.0198 [-3, -1, -2, -3, -2, -1, -4, -4, -3, -3] -savagenesses -0.9 1.86815 [-2, 3, -1, -3, -2, 2, -3, -1, -1, -1] -savageries -1.9 1.75784 [-3, 1, -3, -4, -3, 1, -2, -3, 0, -3] -savagery -2.5 1.62788 [-2, -3, -3, -3, 2, -3, -3, -4, -4, -2] -savages -2.4 1.0198 [-2, -2, -3, -4, -3, -3, -2, 0, -2, -3] -save 2.2 1.16619 [1, 3, 3, 1, 2, 1, 2, 4, 1, 4] -saved 1.8 0.6 [1, 2, 2, 2, 1, 3, 2, 2, 1, 2] -scam -2.7 0.64031 [-2, -3, -3, -3, -2, -2, -4, -3, -3, -2] -scams -2.8 0.87178 [-3, -1, -3, -4, -4, -3, -2, -2, -3, -3] -scandal -1.9 1.81384 [-3, -2, -2, -4, 3, -3, -3, -1, -2, -2] -scandalous -2.4 0.8 [-2, -1, -3, -2, -4, -2, -3, -3, -2, -2] -scandals -2.2 0.9798 [-2, -3, -3, -2, -1, 0, -3, -3, -2, -3] -scapegoat -1.7 0.64031 [-3, -2, -2, -2, -1, -1, -1, -2, -1, -2] -scapegoats -1.4 0.8 [-1, -2, -2, -1, 0, -2, -2, 0, -2, -2] -scare -2.2 0.87178 [-2, -2, -4, -2, -3, -1, -2, -1, -2, -3] -scarecrow -0.8 0.9798 [-1, 0, -1, 0, 0, 0, -2, -3, -1, 0] -scarecrows -0.7 1.1 [2, 0, -1, -1, -1, -2, -1, -2, 0, -1] -scared -1.9 0.7 [-1, -1, -2, -3, -2, -3, -1, -2, -2, -2] -scaremonger -2.1 0.53852 [-1, -2, -2, -3, -2, -2, -3, -2, -2, -2] -scaremongers -2.0 1.0 [-2, -2, 0, -4, -2, -2, -1, -2, -3, -2] -scarer -1.7 0.78102 [-2, -1, -1, -2, -3, -1, -3, -1, -2, -1] -scarers -1.3 0.9 [-1, -2, -1, 0, 0, -1, -3, -2, -1, -2] -scares -1.4 0.4899 [-1, -1, -2, -1, -1, -2, -1, -2, -2, -1] -scarey -1.7 0.64031 [-1, -1, -2, -2, -1, -2, -1, -2, -3, -2] -scaring -1.9 1.22066 [-3, -2, -1, -3, -1, -3, -2, -2, 1, -3] -scary -2.2 0.87178 [-2, -1, -4, -3, -3, -2, -2, -2, -2, -1] -sceptic -1.0 0.89443 [-3, 0, -1, -1, -1, 0, 0, -2, -1, -1] -sceptical -1.2 0.4 [-1, -1, -1, -1, -1, -1, -1, -2, -2, -1] -scepticism -0.8 0.87178 [-1, -2, -2, 0, 0, -1, 1, -1, -1, -1] -sceptics -0.7 0.78102 [0, 0, 0, -1, -2, 0, -1, -1, 0, -2] -scold -1.7 0.78102 [-2, -1, -1, -1, -3, -3, -2, -2, -1, -1] -scoop 0.6 0.8 [0, 0, 1, 0, 2, 0, 2, 0, 1, 0] -scorn -1.7 0.64031 [-2, -3, -2, -1, -1, -1, -1, -2, -2, -2] -scornful -1.8 1.16619 [-3, -3, -2, -1, -4, 0, -2, -1, -1, -1] -scream -1.7 0.78102 [0, -3, -1, -1, -2, -2, -2, -2, -2, -2] -screamed -1.3 1.1 [-2, -3, -2, -1, -1, -2, -2, -1, 1, 0] -screamers -1.5 0.92195 [-2, -1, -2, -2, -2, -2, -1, -2, 1, -2] -screaming -1.6 0.8 [0, -1, -1, -2, -3, -1, -2, -2, -2, -2] -screams -1.2 0.9798 [-1, -2, -2, -1, -1, -2, 1, -2, 0, -2] -screw -0.4 0.91652 [-1, -2, -1, 0, 0, 1, 0, -1, 1, -1] -screwball -0.2 0.87178 [0, -1, 0, 0, 1, 1, -1, 0, -2, 0] -screwballs -0.3 1.00499 [-2, 0, -2, -1, 0, 1, 0, 1, 0, 0] -screwbean 0.3 0.64031 [0, 0, 0, 0, 0, 1, 0, 2, 0, 0] -screwdriver 0.3 0.45826 [1, 0, 0, 0, 0, 1, 0, 0, 1, 0] -screwdrivers 0.1 0.53852 [-1, 0, 0, 1, 0, 0, 0, 1, 0, 0] -screwed -2.2 0.4 [-2, -2, -2, -2, -2, -3, -3, -2, -2, -2] -screwed up -1.5 0.67082 [-2, -2, -2, -1, -1, 0, -2, -1, -2, -2] -screwer -1.2 0.87178 [-1, -2, -1, -2, 0, 0, -2, 0, -2, -2] -screwers -0.5 1.5 [-2, -2, 0, -2, 0, 2, 2, -1, 0, -2] -screwier -0.6 1.2 [0, -1, 2, -2, -1, -2, -1, -1, 1, -1] -screwiest -2.0 0.89443 [-3, -2, -2, -4, -1, -2, -1, -1, -2, -2] -screwiness -0.5 1.80278 [-2, 0, -2, 3, -2, -1, -2, 1, 2, -2] -screwing -0.9 0.9434 [-1, 0, 0, 0, -1, -1, -3, -2, 0, -1] -screwlike 0.1 1.04403 [2, -1, 0, 0, 0, 1, 0, 1, -2, 0] -screws -1.0 1.09545 [0, -3, 0, 0, -1, 0, -2, -2, -2, 0] -screwup -1.7 0.9 [-2, -2, -2, 1, -2, -2, -2, -2, -2, -2] -screwups -1.0 1.61245 [-2, -2, -2, -2, 0, 2, -2, -2, 2, -2] -screwworm -0.4 0.66332 [0, -1, 0, 0, 0, 0, -2, 0, -1, 0] -screwworms -0.1 1.22066 [-3, 0, -1, 0, 0, 0, 0, 2, 1, 0] -screwy -1.4 0.8 [-2, -2, -1, -1, -1, 0, -2, -1, -3, -1] -scrumptious 2.1 1.22066 [3, 3, 0, 3, 2, 3, 1, 3, 0, 3] -scrumptiously 1.5 1.43178 [2, 3, 3, -2, 1, 1, 2, 3, 1, 1] -scumbag -3.2 0.6 [-4, -3, -3, -2, -3, -4, -3, -3, -4, -3] -secure 1.4 0.4899 [1, 2, 1, 1, 2, 1, 1, 2, 2, 1] -secured 1.7 0.78102 [2, 2, 3, 1, 1, 2, 2, 0, 2, 2] -securely 1.4 0.8 [2, 0, 1, 2, 1, 1, 1, 3, 2, 1] -securement 1.1 0.7 [0, 2, 1, 1, 1, 0, 2, 2, 1, 1] -secureness 1.4 0.66332 [2, 1, 1, 3, 1, 1, 1, 1, 2, 1] -securer 1.5 0.67082 [1, 2, 2, 2, 1, 2, 1, 0, 2, 2] -securers 0.6 0.91652 [1, 3, 0, 0, 1, 0, 0, 0, 0, 1] -secures 1.3 0.64031 [1, 2, 2, 1, 1, 2, 1, 0, 2, 1] -securest 2.6 0.8 [3, 3, 2, 3, 1, 4, 3, 2, 2, 3] -securing 1.3 1.00499 [0, 3, 1, 1, 1, 3, 1, 1, 2, 0] -securities 1.2 0.6 [1, 2, 2, 2, 1, 1, 1, 0, 1, 1] -securitization 0.2 1.07703 [0, 0, 1, -1, 1, 0, -2, 0, 2, 1] -securitizations 0.1 0.9434 [0, 0, 0, 0, 2, 0, -2, 0, 1, 0] -securitize 0.3 1.34536 [2, 1, 0, 0, 2, 0, 1, 0, -3, 0] -securitized 1.4 1.0198 [3, 0, 2, 2, 0, 1, 2, 2, 0, 2] -securitizes 1.6 1.0198 [3, 0, 2, 2, 0, 1, 3, 2, 1, 2] -securitizing 0.7 0.9 [2, 0, 0, 1, 2, 0, 2, 0, 0, 0] -security 1.4 0.8 [1, 2, 3, 2, 1, 1, 2, 0, 1, 1] -sedition -1.8 1.249 [-3, -4, -2, -2, -2, -2, -1, -1, -2, 1] -seditious -1.7 0.64031 [-1, -2, -2, -1, -1, -1, -3, -2, -2, -2] -seduced -1.5 0.67082 [0, -1, -2, -2, -2, -2, -1, -1, -2, -2] -self-confident 2.5 0.80623 [1, 3, 3, 3, 2, 3, 1, 3, 3, 3] -selfish -2.1 0.7 [-1, -2, -2, -3, -1, -2, -2, -2, -3, -3] -selfishly -1.4 0.91652 [-3, 0, -1, -1, -1, -2, -3, -1, -1, -1] -selfishness -1.7 0.64031 [-1, -1, -1, -2, -2, -1, -2, -2, -3, -2] -selfishnesses -2.0 1.94936 [-4, -3, -1, -3, -2, -4, 2, 1, -3, -3] -sentence 0.3 0.64031 [0, 0, 0, 0, 1, 2, 0, 0, 0, 0] -sentenced -0.1 1.3 [0, -2, 2, -1, 0, -2, 2, 0, 0, 0] -sentences 0.2 1.07703 [0, 0, 2, 0, 0, -2, 2, 0, 0, 0] -sentencing -0.6 1.8 [-2, 0, -3, -2, 2, 3, 0, -1, -1, -2] -sentimental 1.3 0.64031 [2, 1, 1, 2, 1, 0, 1, 2, 2, 1] -sentimentalise 1.2 0.87178 [2, 1, 0, 3, 2, 1, 1, 0, 1, 1] -sentimentalised 0.8 1.16619 [2, 1, 1, 0, 0, 2, 3, -1, 0, 0] -sentimentalising 0.4 0.91652 [0, 2, 0, 0, 0, -1, 1, 0, 2, 0] -sentimentalism 1.0 0.63246 [2, 1, 0, 2, 1, 1, 1, 0, 1, 1] -sentimentalisms 0.4 0.8 [0, 1, 1, 0, 0, 2, 1, 0, 0, -1] -sentimentalist 0.8 0.87178 [2, 1, 0, 2, 0, 1, 2, 0, 0, 0] -sentimentalists 0.7 0.78102 [0, 0, 1, 0, 0, 1, 1, 2, 0, 2] -sentimentalities 0.9 0.83066 [2, 1, 1, 2, 1, 0, 0, 2, 0, 0] -sentimentality 1.2 1.46969 [-2, 1, 1, 2, 2, 0, 4, 2, 1, 1] -sentimentalization 1.2 0.87178 [0, 1, 2, 0, 1, 1, 3, 1, 2, 1] -sentimentalizations 0.4 0.8 [0, 1, 0, 1, 0, 0, 0, 2, -1, 1] -sentimentalize 0.8 1.07703 [2, 0, 0, 2, 0, 2, 1, -1, 2, 0] -sentimentalized 1.1 1.22066 [3, 0, 2, 0, 1, 3, 2, 0, 0, 0] -sentimentalizes 1.1 1.37477 [3, 0, 1, 0, 1, 4, 2, 0, 0, 0] -sentimentalizing 0.8 0.87178 [1, 1, 1, 1, 2, 0, -1, 1, 0, 2] -sentimentally 1.9 0.9434 [3, 2, 3, 1, 0, 2, 1, 2, 3, 2] -serene 2.0 1.0 [1, 1, 3, 2, 2, 4, 3, 2, 1, 1] -serious -0.3 0.45826 [0, -1, 0, -1, -1, 0, 0, 0, 0, 0] -seriously -0.7 1.34536 [-3, -2, 0, 0, -1, -2, 2, -1, 0, 0] -seriousness -0.2 1.16619 [0, 2, 0, 0, 0, 0, -3, -1, 0, 0] -severe -1.6 1.8 [-3, -2, -4, 1, -2, -3, 2, -1, -1, -3] -severed -1.5 0.5 [-1, -1, -2, -1, -2, -1, -1, -2, -2, -2] -severely -2.0 0.89443 [-2, -1, -1, -2, -2, -1, -3, -2, -4, -2] -severeness -1.0 1.73205 [0, 0, -1, -4, 1, -2, 0, 1, -1, -4] -severer -1.6 1.49666 [-2, -3, -2, -1, -2, 2, -4, -1, -1, -2] -severest -1.5 1.85742 [-4, -1, 2, -2, -2, -3, -4, -1, 1, -1] -sexy 2.4 0.8 [2, 3, 3, 4, 2, 2, 2, 2, 3, 1] -shake -0.7 0.9 [-2, 0, 0, -2, 1, -1, 0, -1, -1, -1] -shakeable -0.3 1.00499 [2, -1, 0, 0, -1, -2, 0, 0, -1, 0] -shakedown -1.2 0.4 [-2, -1, -1, -1, -2, -1, -1, -1, -1, -1] -shakedowns -1.4 0.8 [-2, -1, -1, -3, -1, -1, 0, -2, -2, -1] -shaken -0.3 0.9 [-1, -1, 1, -1, 1, 0, -1, 1, -1, -1] -shakeout -1.3 0.78102 [-1, -2, 0, -1, -1, -2, -2, -2, 0, -2] -shakeouts -0.8 1.16619 [-2, -1, 0, 0, -1, 2, -2, -1, -2, -1] -shakers 0.3 1.00499 [2, 0, 0, -1, 2, 0, 1, -1, 0, 0] -shakeup -0.6 0.4899 [-1, 0, -1, -1, -1, 0, 0, 0, -1, -1] -shakeups -0.5 0.92195 [2, -1, 0, 0, -1, -1, -1, -1, -1, -1] -shakier -0.9 0.3 [-1, -1, 0, -1, -1, -1, -1, -1, -1, -1] -shakiest -1.2 0.74833 [-1, 0, 0, -1, -1, -1, -2, -2, -2, -2] -shakily -0.7 0.45826 [-1, -1, -1, -1, -1, 0, 0, 0, -1, -1] -shakiness -0.7 1.1 [2, -1, -1, -1, -2, -1, -1, -2, 0, 0] -shaking -0.7 0.45826 [-1, -1, -1, 0, -1, -1, 0, 0, -1, -1] -shaky -0.9 0.3 [-1, -1, -1, 0, -1, -1, -1, -1, -1, -1] -shame -2.1 0.53852 [-2, -2, -2, -3, -3, -1, -2, -2, -2, -2] -shamed -2.6 0.4899 [-2, -3, -3, -2, -3, -3, -3, -2, -2, -3] -shamefaced -2.3 0.64031 [-2, -2, -2, -3, -3, -3, -3, -1, -2, -2] -shamefacedly -1.9 0.3 [-2, -2, -2, -2, -2, -2, -2, -1, -2, -2] -shamefacedness -2.0 0.89443 [-1, -1, -2, -2, -2, -1, -2, -4, -2, -3] -shamefast -1.0 0.44721 [-1, -1, 0, -1, -1, -1, -1, -2, -1, -1] -shameful -2.2 0.6 [-3, -3, -2, -2, -2, -3, -1, -2, -2, -2] -shamefully -1.9 0.7 [-2, -3, -1, -3, -1, -2, -2, -1, -2, -2] -shamefulness -2.4 0.4899 [-2, -3, -3, -2, -3, -2, -3, -2, -2, -2] -shamefulnesses -2.3 0.78102 [-4, -2, -2, -2, -3, -1, -2, -2, -3, -2] -shameless -1.4 1.0198 [-1, -1, 1, -2, -3, -1, -2, -2, -1, -2] -shamelessly -1.4 1.0198 [-1, 0, -1, -2, 0, -1, -3, -3, -1, -2] -shamelessness -1.4 1.0198 [-1, -3, -2, 1, -2, -1, -2, -2, -1, -1] -shamelessnesses -2.0 1.0 [-2, 0, -2, -4, -2, -1, -2, -3, -2, -2] -shames -1.7 0.9 [-3, -3, -3, -1, -1, -1, -1, -1, -1, -2] -share 1.2 0.74833 [0, 1, 1, 2, 2, 2, 1, 1, 0, 2] -shared 1.4 0.4899 [2, 2, 2, 1, 2, 1, 1, 1, 1, 1] -shares 1.2 0.87178 [0, 2, 1, 1, 0, 2, 2, 2, 2, 0] -sharing 1.8 0.6 [2, 2, 1, 2, 2, 3, 1, 1, 2, 2] -shattered -2.1 0.7 [-1, -3, -3, -2, -2, -2, -3, -2, -1, -2] -shit -2.6 1.0198 [-2, -1, -4, -3, -4, -4, -2, -2, -2, -2] -shitake -0.3 1.26886 [-4, 0, 0, 0, 0, 0, 0, 0, 1, 0] -shitakes -1.1 1.7 [0, -4, 0, 0, 0, 0, -3, 0, -4, 0] -shithead -3.1 0.83066 [-3, -4, -4, -3, -4, -3, -1, -3, -3, -3] -shitheads -2.6 1.35647 [-2, -3, -4, -3, -3, -3, -2, -4, 1, -3] -shits -2.1 1.22066 [-3, 0, -3, 0, -2, -4, -2, -2, -2, -3] -shittah 0.1 1.3 [-2, -2, 0, 2, 0, 0, 0, 0, 1, 2] -shitted -1.7 0.64031 [-2, -1, -2, -1, -2, -2, -3, -1, -2, -1] -shittier -2.1 0.83066 [-3, -3, -2, -1, -1, -1, -3, -2, -2, -3] -shittiest -3.4 0.66332 [-3, -4, -3, -4, -4, -4, -3, -3, -4, -2] -shittim -0.6 1.0198 [-3, 0, 0, 0, 0, -2, 0, 0, -1, 0] -shittimwood -0.3 0.9 [0, 0, -3, 0, 0, 0, 0, 0, 0, 0] -shitting -1.8 0.9798 [-1, -2, -2, -1, -3, -1, -1, -2, -4, -1] -shitty -2.6 0.8 [-3, -4, -2, -3, -3, -2, -3, -1, -2, -3] -shock -1.6 0.91652 [0, -3, -1, -2, -1, -2, -2, -1, -3, -1] -shockable -1.0 1.0 [-3, -1, -1, 0, 0, -2, -1, -2, 0, 0] -shocked -1.3 1.18743 [-2, -1, -1, 0, 0, -2, 0, -2, -1, -4] -shocker -0.6 1.49666 [-2, -1, 3, -1, 0, -3, -1, 0, -1, 0] -shockers -1.1 0.9434 [-1, -2, -2, -1, -1, 0, 0, -3, 0, -1] -shocking -1.7 1.34536 [-3, -3, 0, -1, 0, -3, 0, -1, -3, -3] -shockingly -0.7 1.48661 [-2, 0, -1, -3, -3, 0, 2, 0, 0, 0] -shockproof 1.3 0.64031 [1, 0, 1, 1, 2, 2, 1, 2, 1, 2] -shocks -1.6 0.91652 [-3, -1, 0, -1, -2, -2, -1, -3, -2, -1] -shook -0.4 0.66332 [-1, -2, 0, 0, 0, 0, 0, 0, 0, -1] -shoot -1.4 1.11355 [-1, -4, -1, -1, -2, 0, -2, 0, -1, -2] -short-sighted -1.2 0.6 [0, -1, -2, -2, -1, -1, -1, -2, -1, -1] -short-sightedness -1.1 1.37477 [-1, -2, -2, -2, -3, -1, 0, 2, 0, -2] -shortage -1.0 1.09545 [-2, -2, -1, -2, -1, -1, 2, -1, -1, -1] -shortages -0.6 1.0198 [0, -2, -1, -1, 0, -2, 1, 1, -1, -1] -shrew -0.9 1.04403 [-2, -1, -2, -2, 1, 0, 0, 0, -1, -2] -shy -1.0 0.0 [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1] -shyer -0.8 0.6 [-1, -1, -1, -1, 0, -1, 0, 0, -2, -1] -shying -0.9 0.83066 [-1, -2, -1, 0, -2, 0, 0, 0, -2, -1] -shylock -2.1 1.13578 [-2, -2, -2, 0, -3, -3, -3, -3, 0, -3] -shylocked -0.7 1.00499 [0, -3, -1, 0, 0, -2, 0, -1, 0, 0] -shylocking -1.5 1.11803 [0, -2, -3, 0, -1, -3, -2, 0, -2, -2] -shylocks -1.4 1.11355 [0, -2, -1, -2, -3, 0, -3, -1, -2, 0] -shyly -0.7 0.45826 [-1, -1, -1, -1, 0, 0, -1, 0, -1, -1] -shyness -1.3 1.00499 [-2, 0, -3, 0, -1, -2, -2, -1, -2, 0] -shynesses -1.2 0.6 [-2, -1, -1, -2, -1, -2, 0, -1, -1, -1] -shyster -1.6 0.66332 [-2, -1, -2, -3, -2, -1, -1, -1, -1, -2] -shysters -0.9 0.7 [0, -2, 0, 0, -2, -1, -1, -1, -1, -1] -sick -2.3 0.78102 [-1, -2, -3, -2, -2, -4, -3, -2, -2, -2] -sicken -1.9 0.7 [-2, -3, -1, -3, -1, -1, -2, -2, -2, -2] -sickened -2.5 0.92195 [-3, -2, -4, -3, -1, -1, -3, -3, -2, -3] -sickener -2.2 0.87178 [-3, -1, -2, -3, -1, -1, -3, -3, -2, -3] -sickeners -2.2 0.6 [-3, -1, -2, -3, -2, -3, -2, -2, -2, -2] -sickening -2.4 0.91652 [-3, -4, -1, -3, -2, -2, -1, -3, -2, -3] -sickeningly -2.1 0.7 [-3, -3, -1, -2, -2, -1, -3, -2, -2, -2] -sickens -2.0 0.63246 [-2, -1, -2, -2, -3, -2, -1, -2, -3, -2] -sigh 0.1 1.22066 [2, -1, -1, -1, 0, 2, 1, 1, -1, -1] -significance 1.1 1.22066 [0, 0, 0, 1, 3, 2, 3, 2, 0, 0] -significant 0.8 0.9798 [1, 0, 1, 3, 0, 1, 0, 0, 2, 0] -silencing -0.5 0.67082 [-2, -1, 0, 0, 0, 0, 0, -1, 0, -1] -sillibub -0.1 0.3 [0, 0, 0, 0, -1, 0, 0, 0, 0, 0] -sillier 1.0 0.7746 [1, 1, 0, 2, 0, 1, 1, 2, 2, 0] -sillies 0.8 0.74833 [2, 1, 0, 1, 0, 1, 0, 2, 1, 0] -silliest 0.8 0.9798 [0, 1, 1, 1, 1, 0, 3, 1, -1, 1] -sillily -0.1 1.04403 [1, -1, -1, -1, 2, 1, -1, 0, 0, -1] -sillimanite 0.1 0.3 [1, 0, 0, 0, 0, 0, 0, 0, 0, 0] -sillimanites 0.2 0.6 [0, 0, 0, 0, 2, 0, 0, 0, 0, 0] -silliness -0.9 1.22066 [1, -3, -1, 0, 1, -1, -2, -1, -2, -1] -sillinesses -1.2 1.46969 [-3, -2, -3, 0, -2, 0, 1, -2, -2, 1] -silly 0.1 1.04403 [1, 1, 0, 0, 0, 2, -1, -2, 0, 0] -sin -2.6 0.8 [-2, -4, -3, -2, -2, -2, -4, -3, -2, -2] -sincere 1.7 0.78102 [1, 2, 3, 0, 2, 2, 2, 2, 1, 2] -sincerely 2.1 1.04403 [1, 3, 2, 4, 2, 3, 1, 1, 3, 1] -sincereness 1.8 0.74833 [3, 1, 1, 2, 2, 3, 1, 2, 2, 1] -sincerer 2.0 1.0 [1, 3, 3, 2, 3, 2, 1, 3, 0, 2] -sincerest 2.0 1.34164 [0, 3, 1, 1, 4, 2, 1, 4, 1, 3] -sincerities 1.5 0.67082 [2, 1, 1, 1, 1, 1, 3, 2, 2, 1] -sinful -2.6 0.8 [-4, -3, -3, -2, -1, -2, -3, -2, -3, -3] -singleminded 1.2 0.87178 [1, 2, 0, 0, 3, 2, 1, 1, 1, 1] -sinister -2.9 1.13578 [-4, -4, -1, -3, -1, -4, -3, -3, -2, -4] -sins -2.0 1.0 [-2, -1, -2, -3, -1, -4, -3, -2, -1, -1] -skeptic -0.9 1.13578 [0, 0, -1, -1, -1, 0, -2, -2, 1, -3] -skeptical -1.3 0.9 [0, -3, -2, -2, -1, -2, 0, -1, -1, -1] -skeptically -1.2 0.4 [-1, -1, -1, -1, -1, -1, -2, -1, -1, -2] -skepticism -1.0 0.89443 [0, 0, -1, -1, -1, -1, 0, -1, -3, -2] -skepticisms -1.2 0.9798 [1, -2, 0, -1, -2, -1, -2, -2, -1, -2] 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-2, -3, -1, -2, -3, -1, -3, -4] -sluttishness -2.5 0.92195 [-2, -1, -3, -4, -2, -1, -3, -3, -3, -3] -sluttishnesses -2.0 1.09545 [0, -2, -1, -3, -3, -1, -3, -1, -3, -3] -slutty -2.3 0.9 [-3, -1, -3, -3, -3, -2, -1, -3, -1, -3] -smart 1.7 0.78102 [2, 2, 1, 2, 1, 3, 2, 0, 2, 2] -smartass -2.1 0.83066 [-1, -1, -2, -3, -2, -1, -2, -3, -3, -3] -smartasses -1.7 2.05183 [-1, -2, -3, -3, -3, -1, -2, -3, 4, -3] -smarted 0.7 1.41774 [2, 1, -2, 1, 1, 2, 2, 2, -1, -1] -smarten 1.9 0.7 [3, 1, 2, 1, 2, 2, 2, 3, 1, 2] -smartened 1.5 0.67082 [2, 2, 1, 3, 1, 1, 1, 1, 2, 1] -smartening 1.7 0.9 [1, 3, 3, 1, 1, 1, 2, 1, 1, 3] -smartens 1.5 0.5 [2, 2, 1, 1, 1, 1, 2, 2, 2, 1] -smarter 2.0 0.7746 [2, 2, 1, 1, 2, 2, 2, 2, 4, 2] -smartest 3.0 1.0 [4, 3, 4, 3, 2, 2, 4, 3, 1, 4] -smartie 1.3 0.9 [1, 4, 1, 1, 1, 1, 1, 1, 1, 1] -smarties 1.7 0.9 [1, 1, 2, 4, 2, 2, 1, 2, 1, 1] -smarting -0.7 1.9 [2, 3, -1, -2, 1, -2, -1, -3, -2, -2] -smartly 1.5 0.67082 [2, 1, 1, 1, 1, 2, 1, 3, 1, 2] -smartness 2.0 0.89443 [1, 3, 3, 1, 2, 1, 2, 3, 1, 3] -smartnesses 1.5 0.92195 [1, 0, 1, 1, 1, 2, 1, 2, 3, 3] -smarts 1.6 0.66332 [2, 1, 3, 1, 2, 1, 2, 1, 2, 1] -smartweed 0.2 0.6 [0, 0, 0, 0, 0, 2, 0, 0, 0, 0] -smartweeds 0.1 0.53852 [0, 0, -1, 0, 0, 0, 1, 0, 0, 1] -smarty 1.1 0.53852 [0, 2, 1, 2, 1, 1, 1, 1, 1, 1] -smear -1.5 1.20416 [-2, -1, -1, -2, -3, 0, 0, -4, -1, -1] -smilax 0.6 0.66332 [0, 2, 1, 0, 0, 0, 1, 1, 1, 0] -smilaxes 0.3 0.78102 [0, 0, 0, 0, 1, 2, 1, -1, 0, 0] -smile 1.5 0.67082 [2, 1, 1, 1, 2, 2, 3, 1, 1, 1] -smiled 2.5 0.80623 [3, 2, 3, 2, 1, 2, 3, 4, 3, 2] -smileless -1.4 0.4899 [-1, -1, -1, -1, -2, -1, -2, -1, -2, -2] -smiler 1.7 0.78102 [1, 1, 3, 1, 3, 2, 2, 2, 1, 1] -smiles 2.1 1.04403 [2, 4, 2, 1, 3, 1, 1, 3, 1, 3] -smiley 1.7 0.78102 [1, 2, 1, 2, 2, 0, 2, 3, 2, 2] -smileys 1.5 0.92195 [1, 2, 1, 3, 1, 0, 1, 3, 1, 2] -smiling 2.0 1.18322 [2, 1, 1, 1, 2, 3, 4, 1, 4, 1] -smilingly 2.3 0.64031 [3, 2, 3, 2, 3, 1, 2, 2, 2, 3] -smog -1.2 0.6 [-1, -1, -2, -1, -1, -2, -2, -1, 0, -1] -smother -1.8 0.87178 [-2, -2, -3, -1, -2, -1, -2, -2, -3, 0] -smothered -0.9 1.7 [2, -4, 0, -1, -3, -2, 0, -1, 1, -1] -smothering -1.4 1.56205 [-2, -3, -1, -4, 0, -2, -1, 2, -1, -2] -smothers -1.9 1.04403 [-1, -1, -3, -1, -2, -3, 0, -2, -3, -3] -smothery -1.1 0.7 [-2, 0, -2, -1, -2, -1, 0, -1, -1, -1] -smug 0.8 1.16619 [-1, 2, 0, 2, 1, -1, 2, 1, 0, 2] -smugger -1.0 0.89443 [1, -2, -1, -2, -1, -1, -1, 0, -2, -1] -smuggest -1.5 1.28452 [-1, -1, -1, 1, -1, -3, -4, -2, -1, -2] -smuggle -1.6 1.11355 [-2, -1, -1, -1, -2, 0, -1, -1, -3, -4] -smuggled -1.5 0.92195 [-1, -1, -2, -1, -1, -1, -2, -1, -1, -4] -smuggler -2.1 1.22066 [-1, -3, -3, -1, -1, -1, -4, -1, -2, -4] -smugglers -1.4 1.56205 [-2, -3, -4, 1, -2, 0, -2, 1, -1, -2] -smuggles -1.7 1.00499 [-1, -2, -2, -1, -1, -1, -3, -1, -1, -4] -smuggling -2.1 0.83066 [-3, -2, -2, -1, -2, -2, -1, -2, -4, -2] -smugly 0.2 1.249 [-1, 2, -1, -1, 1, 1, -1, 1, 2, -1] -smugness -1.4 1.11355 [-1, -1, -1, -3, -3, -2, 1, -1, -2, -1] -smugnesses -1.7 0.78102 [-1, -1, -2, -1, -3, -1, -2, -2, -3, -1] -sneaky -0.9 0.7 [-1, -1, -1, -2, -1, -1, -1, 1, -1, -1] -snob -2.0 0.63246 [-2, -2, -2, -2, -2, -1, -3, -1, -3, -2] -snobbery -2.0 0.63246 [-1, -2, -2, -2, -2, -3, -2, -1, -3, -2] -snobbier -0.7 1.00499 [-1, 2, -1, -1, -1, -1, -1, 0, -2, -1] -snobbiest -0.5 1.11803 [-2, -2, 1, -1, 1, -1, 0, -1, 1, -1] -snobbily -1.6 1.11355 [-1, -2, -2, -2, -1, -3, -3, -1, 1, -2] -snobbish -0.9 1.37477 [-2, -1, 1, -1, 1, -2, -3, -2, 1, -1] -snobbishly -1.2 1.249 [-2, 1, -2, -1, -2, -3, -1, -2, -1, 1] -snobbishness -1.1 1.22066 [-1, -2, -2, -1, -3, -1, -1, -1, 2, -1] -snobbishnesses -1.7 0.78102 [-2, -1, -3, -2, -1, -1, -2, -1, -3, -1] -snobbism -1.0 1.41421 [-2, -1, 1, -1, 1, -2, -3, -2, 1, -2] -snobbisms -0.3 1.18743 [1, -1, -1, 0, -1, -1, 1, -2, 2, -1] -snobby -1.7 1.00499 [-1, -1, -1, -3, -2, -2, 0, -3, -3, -1] -snobs -1.4 1.0198 [-2, -1, -1, -2, -2, -3, -1, -2, 1, -1] -snub -1.8 0.4 [-2, -2, -1, -2, -2, -2, -2, -2, -1, -2] -snubbed -2.0 0.7746 [-2, -2, 0, -2, -3, -2, -2, -2, -3, -2] -snubbing -0.9 1.13578 [-2, -1, -1, -1, 1, -1, -3, 1, -1, -1] -snubs -2.1 0.9434 [-2, -1, -1, -1, -3, -2, -4, -3, -2, -2] -sob -1.0 1.34164 [-1, -2, -2, -2, -1, -1, 2, 1, -2, -2] -sobbed -1.9 1.3 [-2, -4, 1, -1, -3, -1, -3, -2, -2, -2] -sobbing -1.6 1.49666 [1, -2, -3, -1, -1, -3, 1, -2, -3, -3] -sobering -0.8 1.32665 [2, -2, 0, -2, -1, -1, -2, 1, -1, -2] -sobs -2.5 0.67082 [-3, -3, -2, -2, -3, -3, -3, -1, -2, -3] -sociabilities 1.2 0.9798 [1, 3, 1, 2, 0, 1, 0, 2, 2, 0] -sociability 1.1 0.9434 [0, 1, 1, 1, 0, 2, 1, 0, 2, 3] -sociable 1.9 0.7 [1, 1, 2, 3, 1, 2, 2, 2, 3, 2] -sociableness 1.5 0.5 [1, 1, 1, 2, 2, 2, 1, 2, 1, 2] -sociably 1.6 0.91652 [3, 2, 0, 1, 3, 2, 1, 1, 2, 1] -sok 1.3 1.1 [0, 1, 2, 1, 1, 0, 1, 4, 2, 1] -solemn -0.3 1.1 [-1, -2, -1, 0, -1, 2, 0, -1, 1, 0] -solemnified -0.5 0.67082 [0, 0, 0, 0, -1, -1, -1, 0, -2, 0] -solemnifies -0.5 0.67082 [0, 0, 0, 0, -1, -2, -1, 0, -1, 0] -solemnify 0.3 1.18743 [2, 1, 2, 1, 0, 0, -2, -1, 0, 0] -solemnifying 0.1 1.3 [2, -1, 0, -3, 0, 1, 1, 1, 0, 0] -solemnities 0.3 0.78102 [0, 1, -1, 0, 0, 0, 2, 1, 0, 0] -solemnity -1.1 0.9434 [0, -2, 0, -2, -2, -1, -2, 0, 0, -2] -solemnization 0.7 1.34536 [-1, -1, 0, 2, 2, 0, 3, 2, 0, 0] -solemnize 0.3 0.78102 [1, -1, 0, 2, 0, 0, 1, 0, 0, 0] -solemnized -0.7 0.9 [0, 0, 0, -1, -1, -1, -1, 0, 0, -3] -solemnizes 0.6 0.91652 [0, 0, 0, 0, 0, 0, 2, 2, 2, 0] -solemnizing -0.6 0.8 [0, 0, -1, -1, 0, 0, -2, -2, 0, 0] -solemnly 0.8 0.9798 [0, 2, 0, 1, 1, 2, -1, 2, 1, 0] -solid 0.6 0.8 [0, 2, 1, 2, 0, 1, 0, 0, 0, 0] -solidarity 1.2 0.6 [1, 1, 1, 1, 2, 0, 1, 2, 2, 1] -solution 1.3 0.64031 [1, 2, 1, 2, 1, 1, 2, 2, 0, 1] -solutions 0.7 0.78102 [1, 1, 2, 0, 1, 0, 2, 0, 0, 0] -solve 0.8 0.4 [0, 1, 1, 1, 1, 0, 1, 1, 1, 1] -solved 1.1 0.53852 [1, 2, 1, 0, 1, 1, 1, 2, 1, 1] -solves 1.1 0.7 [2, 0, 1, 0, 1, 2, 1, 2, 1, 1] -solving 1.4 0.8 [0, 3, 1, 2, 1, 1, 2, 1, 2, 1] -somber -1.8 0.6 [-1, -2, -2, -3, -2, -1, -2, -1, -2, -2] -son-of-a-bitch -2.7 0.64031 [-3, -3, -3, -1, -2, -3, -3, -3, -3, -3] -soothe 1.5 0.92195 [3, 2, 2, 1, 2, 0, 2, 0, 2, 1] -soothed 0.5 1.43178 [2, -3, 1, 1, 0, 1, 1, 1, 2, -1] -soothing 1.3 0.64031 [2, 1, 2, 1, 1, 1, 2, 0, 2, 1] -sophisticated 2.6 0.91652 [3, 4, 3, 3, 3, 1, 2, 1, 3, 3] -sore -1.5 0.5 [-2, -2, -2, -1, -1, -1, -2, -1, -1, -2] -sorrow -2.4 0.8 [-2, -2, -2, -1, -2, -3, -2, -4, -3, -3] -sorrowed -2.4 0.8 [-1, -2, -3, -3, -2, -3, -2, -4, -2, -2] -sorrower -2.3 0.78102 [-1, -2, -1, -3, -3, -2, -2, -3, -3, -3] -sorrowful -2.2 0.6 [-3, -3, -2, -2, -2, -2, -3, -1, -2, -2] -sorrowfully -2.3 0.64031 [-3, -3, -2, -1, -2, -2, -3, -2, -2, -3] -sorrowfulness -2.5 0.67082 [-4, -3, -2, -3, -2, -3, -2, -2, -2, -2] -sorrowing -1.7 1.26886 [-2, -2, 1, -1, -1, -2, -4, -3, -2, -1] -sorrows -1.6 0.66332 [-1, -1, -2, -1, -2, -2, -1, -2, -1, -3] -sorry -0.3 1.61555 [-1, 0, -1, -2, -1, -1, 4, 1, -1, -1] -soulmate 2.9 0.83066 [4, 2, 2, 2, 3, 4, 3, 3, 2, 4] -spam -1.5 1.0247 [-1, -1, -1, -2, 1, -2, -3, -2, -2, -2] -spammer -2.2 0.6 [-3, -2, -2, -1, -2, -3, -2, -2, -3, -2] -spammers -1.6 1.11355 [-2, -1, -2, -3, -2, -1, -2, -1, 1, -3] -spamming -2.1 0.83066 [-3, -3, -1, -3, -2, -1, -2, -2, -1, -3] -spark 0.9 1.04403 [0, 2, 1, 1, 0, 1, 3, -1, 1, 1] -sparkle 1.8 0.74833 [0, 2, 2, 2, 1, 2, 3, 2, 2, 2] -sparkles 1.3 1.18743 [3, 2, 0, 0, 3, 0, 2, 0, 1, 2] -sparkling 1.2 0.4 [1, 1, 1, 2, 1, 1, 1, 2, 1, 1] -special 1.7 0.78102 [3, 1, 3, 2, 2, 1, 1, 2, 1, 1] -speculative 0.4 1.11355 [1, -1, 1, 0, -1, -1, 1, 2, 2, 0] -spirit 0.7 1.00499 [0, 0, 1, 2, 3, 1, 0, 0, 0, 0] -spirited 1.3 1.00499 [1, 1, 0, 1, 1, 3, 2, 3, 0, 1] -spiritless -1.3 0.64031 [-2, -1, -1, -2, -2, -1, 0, -1, -2, -1] -spite -2.4 0.8 [-2, -2, -3, -2, -3, -2, -4, -1, -3, -2] -spited -2.4 0.91652 [-2, -3, -3, -4, -2, -1, -2, -1, -3, -3] -spiteful -1.9 1.75784 [-2, 3, -2, -3, -2, -3, -2, -2, -4, -2] -spitefully -2.3 0.78102 [-2, -2, -1, -3, -3, -2, -2, -2, -4, -2] -spitefulness -1.5 1.74642 [-3, -2, 1, -3, -3, -3, -2, 2, 0, -2] -spitefulnesses -2.3 0.9 [-1, -4, -2, -3, -3, -2, -2, -3, -1, -2] -spites -1.4 1.28062 [0, -2, -2, -3, -2, -1, 1, 0, -3, -2] -splendent 2.7 0.78102 [3, 2, 1, 3, 2, 3, 4, 3, 3, 3] -splendid 2.8 0.9798 [4, 2, 3, 4, 2, 2, 3, 1, 3, 4] -splendidly 2.1 1.22066 [1, 4, 1, 3, 3, 4, 1, 2, 1, 1] -splendidness 2.3 0.9 [2, 1, 3, 3, 4, 2, 1, 3, 2, 2] -splendiferous 2.6 1.95959 [4, 4, 3, -3, 3, 3, 4, 2, 3, 3] -splendiferously 1.9 1.3 [2, 4, 4, 3, 0, 1, 1, 1, 2, 1] -splendiferousness 1.7 1.18743 [1, 2, 3, 1, 2, 3, 3, 2, -1, 1] -splendor 3.0 0.63246 [3, 3, 3, 3, 3, 2, 4, 4, 3, 2] -splendorous 2.2 0.87178 [4, 2, 1, 2, 2, 3, 3, 1, 2, 2] -splendors 2.0 0.44721 [2, 2, 2, 2, 3, 2, 2, 2, 1, 2] -splendour 2.2 0.6 [2, 2, 2, 3, 3, 1, 2, 3, 2, 2] -splendours 2.2 1.249 [3, 0, 2, 1, 4, 3, 2, 4, 1, 2] -splendrous 2.2 1.16619 [4, 4, 3, 2, 1, 1, 3, 1, 2, 1] -sprightly 2.0 0.89443 [0, 2, 3, 2, 2, 1, 2, 3, 3, 2] -squelched -1.0 0.63246 [-1, -1, -1, -1, 0, -2, -1, 0, -1, -2] -stab -2.8 0.6 [-3, -2, -2, -3, -3, -3, -3, -2, -4, -3] -stabbed -1.9 1.22066 [-2, -1, -3, -2, -2, 1, -3, -3, -1, -3] -stable 1.2 0.74833 [1, 2, 2, 0, 1, 2, 1, 1, 2, 0] -stabs -1.9 1.13578 [-3, -3, -4, 0, -1, -2, -2, -2, -1, -1] -stall -0.8 0.74833 [-1, 0, -1, 0, -1, 0, -2, 0, -2, -1] -stalled -0.8 0.87178 [-2, -1, 0, -1, -1, 0, 1, -2, -1, -1] -stalling -0.8 1.4 [-3, -2, -1, -1, 0, 2, 1, -2, -1, -1] -stamina 1.2 0.9798 [1, 0, 3, 0, 1, 2, 2, 1, 2, 0] -stammer -0.9 0.3 [-1, 0, -1, -1, -1, -1, -1, -1, -1, -1] -stammered -0.9 0.7 [-2, -1, -1, -1, 1, -1, -1, -1, -1, -1] -stammerer -1.1 0.3 [-1, -2, -1, -1, -1, -1, -1, -1, -1, -1] -stammerers -0.8 0.4 [-1, -1, -1, -1, -1, 0, 0, -1, -1, -1] -stammering -1.0 0.63246 [-2, -1, 0, -1, -1, -2, 0, -1, -1, -1] -stammers -0.8 0.4 [-1, -1, -1, 0, -1, -1, -1, 0, -1, -1] -stampede -1.8 1.07703 [-2, -3, -2, -3, 0, 0, -2, -1, -2, -3] -stank -1.9 1.04403 [-2, -2, -2, -1, -2, -4, -3, 0, -1, -2] -startle -1.3 0.64031 [-1, -1, -1, -1, -1, -2, -1, -1, -3, -1] -startled -0.7 0.78102 [-2, -1, -1, 0, 1, -1, -1, 0, -1, -1] -startlement -0.5 1.20416 [-1, 0, 0, 1, -1, -1, 2, -2, -1, -2] -startlements 0.2 1.32665 [2, 2, 0, 0, -1, 2, 0, -2, -1, 0] -startler -0.8 0.74833 [-2, -1, -1, 0, 1, -1, -1, -1, -1, -1] -startlers -0.5 0.80623 [0, 0, 0, 0, -1, -1, -1, 1, -1, -2] -startles -0.5 1.36015 [-2, 2, -1, 0, 2, -1, -1, -2, -1, -1] -startling 0.3 1.41774 [-2, 2, -1, 0, -1, 2, -1, 1, 1, 2] -startlingly -0.3 0.9 [-1, -1, 0, -2, 1, 0, 1, 0, -1, 0] -starve -1.9 2.02237 [2, -3, -4, -1, -3, -4, -1, -2, 1, -4] -starved -2.6 1.11355 [-3, -4, -1, -3, -3, -4, -1, -1, -3, -3] -starves -2.3 0.78102 [-3, -2, -2, -3, -2, -3, -1, -1, -3, -3] -starving -1.8 2.03961 [-2, -2, -4, -4, -3, -3, 2, 2, -2, -2] -steadfast 1.0 1.0 [0, 0, 2, 1, 1, 2, 3, 0, 1, 0] -steal -2.2 0.6 [-2, -2, -2, -3, -3, -3, -1, -2, -2, -2] -stealable -1.7 1.00499 [-3, -1, -2, -1, -2, -1, -1, -1, -4, -1] -stealer -1.7 0.78102 [-2, -2, -1, -2, -3, -1, -2, -2, -2, 0] -stealers -2.2 0.74833 [-2, -2, -2, -4, -2, -2, -3, -1, -2, -2] -stealing -2.7 0.9 [-3, -2, -2, -4, -4, -3, -1, -3, -2, -3] -stealings -1.9 0.9434 [-2, -2, -1, -1, -1, -3, -4, -2, -1, -2] -steals -2.3 0.64031 [-4, -2, -2, -3, -2, -2, -2, -2, -2, -2] -stealth -0.3 1.34536 [-2, 1, 1, -1, 0, -3, 0, 1, -1, 1] -stealthier -0.3 1.00499 [0, 0, -3, 0, 0, 1, 0, -1, 0, 0] -stealthiest 0.4 2.10713 [-1, 2, 1, 1, 3, 4, -1, 0, -2, -3] -stealthily 0.1 1.37477 [2, 0, 0, -1, 1, 0, -3, 2, 0, 0] -stealthiness 0.2 0.74833 [1, 0, 0, -1, 1, 0, -1, 0, 1, 1] -stealths -0.3 0.78102 [-2, 0, 0, -1, 0, 1, -1, 0, 0, 0] -stealthy -0.1 0.7 [0, 0, 0, -1, 1, -1, -1, 0, 1, 0] -stench -2.3 0.64031 [-3, -2, -2, -3, -3, -1, -3, -2, -2, -2] -stenches -1.5 1.11803 [-2, -2, -1, -3, 0, 0, -3, -2, 0, -2] -stenchful -2.4 0.91652 [-3, -1, -3, -1, -2, -2, -3, -4, -2, -3] -stenchy -2.3 1.00499 [-4, -1, -2, -3, -1, -1, -2, -3, -3, -3] -stereotype -1.3 0.78102 [-1, -1, -2, 0, -2, 0, -2, -1, -2, -2] -stereotyped -1.2 0.4 [-1, -1, -2, -1, -2, -1, -1, -1, -1, -1] -stifled -1.4 0.66332 [-1, -1, -1, -1, -3, -1, -2, -2, -1, -1] -stimulate 0.9 0.83066 [1, 0, 1, 1, 1, 2, -1, 2, 1, 1] -stimulated 0.9 0.7 [1, 0, 0, 0, 1, 1, 2, 1, 2, 1] -stimulates 1.0 0.89443 [1, 0, 0, 0, 1, 1, 2, 1, 3, 1] -stimulating 1.9 0.7 [2, 3, 2, 1, 3, 2, 1, 2, 1, 2] -stingy -1.6 0.8 [-1, 0, -2, -2, -1, -1, -2, -2, -3, -2] -stink -1.7 0.64031 [-2, -2, -1, -3, -2, -1, -1, -2, -1, -2] -stinkard -2.3 0.9 [-2, -3, -3, -2, -3, -2, -3, -3, 0, -2] -stinkards -1.0 1.26491 [-2, -1, 2, -2, -1, -1, 0, -3, -1, -1] -stinkbug -0.2 0.4 [-1, 0, 0, 0, 0, 0, 0, 0, -1, 0] -stinkbugs -1.0 1.26491 [0, 0, 0, -4, -1, -2, -1, 0, -2, 0] -stinker -1.5 0.80623 [-3, -1, -3, -1, -1, -2, -1, -1, -1, -1] -stinkers -1.2 1.07703 [-3, 1, -1, -2, -2, -1, -1, -2, 0, -1] -stinkhorn -0.2 1.16619 [-2, -2, 0, 0, -1, 0, 1, 2, 0, 0] -stinkhorns -0.8 0.9798 [0, -3, 0, -2, 0, 0, -1, -1, -1, 0] -stinkier -1.5 1.0247 [-2, -1, -2, -2, -1, 1, -2, -1, -3, -2] -stinkiest -2.1 1.57797 [-1, -2, -3, -4, -2, -1, 1, -4, -1, -4] -stinking -2.4 0.91652 [-2, -4, -2, -3, -3, -1, -2, -1, -3, -3] -stinkingly -1.3 1.55242 [-2, -3, -3, -2, -2, 1, -2, 2, -1, -1] -stinko -1.5 0.80623 [-1, -2, -2, -2, 0, -1, -2, -1, -1, -3] -stinkpot -2.5 0.92195 [-4, -1, -3, -4, -2, -2, -3, -2, -2, -2] -stinkpots -0.7 1.26886 [-1, -3, -2, -1, 0, 2, 0, -1, 0, -1] -stinks -1.0 1.34164 [-2, -2, -1, -2, 2, -1, -2, 1, -1, -2] -stinkweed -0.4 1.0198 [-2, 0, -1, 0, 2, 0, -1, -1, 0, -1] -stinkwood -0.1 1.13578 [0, -2, 0, 0, 0, -2, 1, 0, 2, 0] -stinky -1.5 0.5 [-2, -1, -1, -2, -1, -1, -2, -2, -1, -2] -stolen -2.2 0.9798 [-3, -2, -2, -1, -3, -2, -3, 0, -3, -3] -stop -1.2 0.87178 [-1, 0, -2, -2, 0, -1, -2, -2, 0, -2] -stopped -0.9 0.53852 [-1, -1, -1, -1, -2, -1, -1, -1, 0, 0] -stopping -0.6 0.66332 [-1, 0, 0, -1, 0, 0, 0, -1, -2, -1] -stops -0.6 0.8 [-1, -1, 0, 0, -2, 0, -2, 0, 0, 0] -stout 0.7 1.34536 [2, 0, 3, 1, 2, 1, 0, 0, -2, 0] -straight 0.9 1.04403 [2, 0, 1, 0, 0, 0, 1, 2, 3, 0] -strain -0.2 0.9798 [0, 0, -2, 0, -1, 2, 0, -1, 0, 0] -strained -1.7 0.78102 [0, -2, -1, -1, -2, -2, -2, -3, -2, -2] -strainer -0.8 1.249 [2, -2, -1, 0, -1, 0, -2, 0, -2, -2] -strainers -0.3 0.45826 [0, 0, 0, 0, -1, -1, 0, -1, 0, 0] -straining -1.3 0.78102 [0, -3, -2, -1, -1, -1, -1, -1, -2, -1] -strains -1.2 0.4 [-1, -1, -1, -2, -1, -2, -1, -1, -1, -1] -strange -0.8 0.74833 [0, -1, -1, 0, -2, 0, -1, -2, 0, -1] -strangely -1.2 0.87178 [0, -1, -2, -2, 0, -3, -1, -1, -1, -1] -strangled -2.5 1.0247 [-1, -1, -3, -3, -3, -3, -1, -4, -3, -3] -strength 2.2 0.6 [1, 2, 2, 3, 2, 3, 3, 2, 2, 2] -strengthen 1.3 0.64031 [1, 1, 2, 1, 2, 1, 2, 0, 2, 1] -strengthened 1.8 0.4 [2, 2, 2, 2, 1, 2, 2, 1, 2, 2] -strengthener 1.8 0.6 [2, 0, 2, 2, 2, 2, 2, 2, 2, 2] -strengtheners 1.4 0.91652 [1, 2, 1, 2, 3, 0, 2, 0, 2, 1] -strengthening 2.2 0.74833 [3, 3, 1, 1, 2, 2, 2, 2, 3, 3] -strengthens 2.0 0.63246 [3, 2, 1, 2, 2, 3, 2, 1, 2, 2] -strengths 1.7 0.64031 [2, 1, 3, 1, 2, 1, 2, 1, 2, 2] -stress -1.8 0.6 [-1, -2, -2, -1, -2, -1, -2, -3, -2, -2] -stressed -1.4 0.4899 [-1, -1, -1, -2, -2, -1, -2, -2, -1, -1] -stresses -2.0 1.0 [-3, -3, -2, -1, -2, 0, -2, -1, -3, -3] -stressful -2.3 0.45826 [-2, -2, -2, -2, -3, -3, -2, -3, -2, -2] -stressfully -2.6 0.66332 [-2, -3, -1, -3, -3, -3, -3, -2, -3, -3] -stressing -1.5 0.67082 [-1, -2, -1, -1, -3, -1, -2, -2, -1, -1] -stressless 1.6 0.4899 [1, 2, 1, 2, 1, 2, 1, 2, 2, 2] -stresslessness 1.6 0.8 [1, 3, 1, 3, 2, 1, 2, 1, 1, 1] -stressor -1.8 0.74833 [-2, -1, -1, -2, -3, -2, -1, -2, -3, -1] -stressors -2.1 0.83066 [-3, -2, -2, -2, -3, -1, -3, -1, -1, -3] -stricken -2.3 0.9 [0, -2, -2, -2, -2, -3, -3, -3, -3, -3] -strike -0.5 1.11803 [0, 0, 0, -2, -2, 1, 1, -2, -1, 0] -strikers -0.6 1.0198 [0, 0, -2, -3, 0, 0, -1, 0, 0, 0] -strikes -1.5 0.92195 [0, -2, -2, -2, -3, -1, -2, -1, 0, -2] -strong 2.3 0.78102 [3, 2, 3, 3, 1, 1, 3, 2, 2, 3] -strongbox 0.7 0.78102 [2, 1, 0, 0, 0, 1, 2, 1, 0, 0] -strongboxes 0.3 0.64031 [0, 0, 0, 0, 0, 1, 0, 2, 0, 0] -stronger 1.6 0.66332 [2, 1, 1, 1, 2, 3, 2, 1, 2, 1] -strongest 1.9 0.9434 [2, 3, 2, 1, 2, 2, 0, 3, 1, 3] -stronghold 0.5 0.80623 [0, 2, 0, 0, 2, 0, 0, 0, 0, 1] -strongholds 1.0 0.89443 [2, 2, 0, 1, 2, 2, 1, 0, 0, 0] -strongish 1.7 0.78102 [1, 1, 2, 3, 1, 2, 1, 3, 2, 1] -strongly 1.1 0.83066 [0, 0, 2, 2, 0, 1, 2, 2, 1, 1] -strongman 0.7 1.00499 [0, 1, 3, 0, 1, -1, 1, 1, 0, 1] -strongmen 0.5 1.11803 [-1, 0, 0, 3, 0, 1, 0, 2, 0, 0] -strongyl 0.6 1.0198 [0, 1, 0, 0, 0, 0, 0, 2, 3, 0] -strongyles 0.2 1.07703 [0, -2, 1, 1, -1, 1, 0, 0, 2, 0] -strongyloidosis -0.8 1.66132 [-2, -3, 0, 0, -2, -2, 2, -2, 2, -1] -strongyls 0.1 0.3 [0, 0, 1, 0, 0, 0, 0, 0, 0, 0] -struck -1.0 0.89443 [-1, -2, -1, 0, -2, -2, -1, -1, 1, -1] -struggle -1.3 0.45826 [-2, -1, -2, -1, -2, -1, -1, -1, -1, -1] -struggled -1.4 0.66332 [-2, -2, -1, -1, -1, -1, -2, -2, 0, -2] -struggler -1.1 0.7 [-1, -1, -1, -1, 0, -1, -2, -2, 0, -2] -strugglers -1.4 0.4899 [-1, -2, -1, -1, -2, -1, -2, -2, -1, -1] -struggles -1.5 0.5 [-2, -2, -1, -1, -1, -1, -2, -2, -1, -2] -struggling -1.8 0.6 [-2, -2, -2, -2, -1, -1, -2, -2, -3, -1] -stubborn -1.7 1.00499 [0, -1, -2, -2, -2, -4, -1, -2, -1, -2] -stubborner -1.5 1.20416 [-2, -3, -1, -1, -2, 1, -3, -2, 0, -2] -stubbornest -0.6 1.62481 [-2, 4, -2, -1, -1, 0, -1, -1, -1, -1] -stubbornly -1.4 0.4899 [-2, -2, -1, -2, -1, -1, -2, -1, -1, -1] -stubbornness -1.1 0.53852 [-1, -1, 0, -2, -1, -1, -1, -2, -1, -1] -stubbornnesses -1.5 0.80623 [-1, -2, -3, -1, -1, -3, -1, -1, -1, -1] -stuck -1.0 0.44721 [-1, -1, -1, -1, 0, -1, -1, -1, -1, -2] -stunk -1.6 1.68523 [-2, -2, -3, 2, -2, -3, -3, 1, -1, -3] -stunned -0.4 1.28062 [-1, -3, -1, 0, -1, -1, 0, 2, 1, 0] -stunning 1.6 1.42829 [0, 0, 3, 2, 2, 4, 3, 0, 2, 0] -stuns 0.1 1.04403 [1, 0, -1, -2, 0, 1, 1, -1, 1, 1] -stupid -2.4 0.66332 [-2, -3, -3, -2, -3, -3, -2, -1, -2, -3] -stupider -2.5 0.5 [-3, -2, -3, -3, -2, -2, -3, -2, -3, -2] -stupidest -2.4 0.66332 [-2, -3, -2, -3, -1, -3, -3, -2, -2, -3] -stupidities -2.0 0.7746 [-2, -3, -2, -1, -3, -1, -3, -1, -2, -2] -stupidity -1.9 0.3 [-2, -2, -2, -2, -2, -2, -1, -2, -2, -2] -stupidly -2.0 0.7746 [-1, -2, -3, -3, -1, -3, -2, -1, -2, -2] -stupidness -1.7 0.64031 [-3, -1, -2, -1, -2, -1, -2, -2, -1, -2] -stupidnesses -2.6 0.8 [-2, -2, -2, -4, -4, -3, -3, -2, -2, -2] -stupids -2.3 0.64031 [-2, -3, -1, -3, -2, -3, -3, -2, -2, -2] -stutter -1.0 0.0 [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1] -stuttered -0.9 1.04403 [-1, -1, 2, -1, -1, -1, -2, -2, -1, -1] -stutterer -1.0 1.18322 [-1, -1, 2, -1, -1, -1, -3, -2, -1, -1] -stutterers -1.1 0.53852 [-1, -1, -1, 0, -1, -1, -2, -2, -1, -1] -stuttering -1.3 0.9 [-1, -1, -1, 0, -3, -1, -1, -1, -3, -1] -stutters -1.0 0.63246 [-1, -1, -1, -2, 0, -2, 0, -1, -1, -1] -suave 2.0 0.44721 [2, 3, 2, 2, 2, 1, 2, 2, 2, 2] -submissive -1.3 0.9 [-1, 0, -1, -3, -1, 0, -1, -2, -2, -2] -submissively -1.0 1.18322 [-1, -1, -1, -1, 2, -1, -1, -2, -3, -1] -submissiveness -0.7 0.78102 [-2, 0, -1, 0, -1, 0, -2, 0, -1, 0] -substantial 0.8 0.6 [2, 0, 1, 1, 0, 0, 1, 1, 1, 1] -subversive -0.9 1.81384 [-3, 0, -4, -1, -2, -1, 2, -1, 2, -1] -succeed 2.2 0.74833 [2, 3, 2, 2, 2, 1, 2, 4, 2, 2] -succeeded 1.8 0.87178 [2, 2, 1, 2, 2, 0, 2, 3, 3, 1] -succeeder 1.2 1.07703 [1, 0, 0, 2, 2, 0, 0, 3, 2, 2] -succeeders 1.3 0.64031 [2, 0, 2, 1, 2, 1, 1, 1, 1, 2] -succeeding 2.2 1.16619 [2, 3, 0, 3, 4, 3, 1, 1, 2, 3] -succeeds 2.2 0.9798 [4, 1, 4, 1, 2, 2, 2, 2, 2, 2] -success 2.7 0.64031 [4, 3, 2, 2, 3, 2, 3, 3, 2, 3] -successes 2.6 0.66332 [2, 4, 3, 3, 2, 3, 2, 2, 3, 2] -successful 2.8 0.6 [3, 3, 2, 3, 4, 3, 3, 3, 2, 2] -successfully 2.2 0.6 [2, 2, 1, 2, 2, 2, 3, 3, 2, 3] -successfulness 2.7 0.78102 [3, 3, 4, 3, 3, 2, 3, 2, 1, 3] -succession 0.8 0.87178 [2, 0, 1, 2, 0, 2, 1, 0, 0, 0] -successional 0.9 1.04403 [0, 1, 0, 2, 3, 0, 0, 1, 2, 0] -successionally 1.1 1.13578 [2, 2, 0, 0, 0, 0, 2, 3, 0, 2] -successions 0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 1, 0, 0] -successive 1.1 1.13578 [3, 0, 0, 1, 3, 2, 1, 0, 1, 0] -successively 0.9 1.04403 [1, 0, 0, 1, 3, 0, 2, 0, 2, 0] -successiveness 1.0 1.0 [0, 1, 2, 0, 3, 1, 1, 2, 0, 0] -successor 0.9 0.83066 [0, 2, 0, 0, 1, 2, 2, 1, 1, 0] -successors 1.1 1.04403 [2, 0, 1, 2, 0, 1, 3, 0, 2, 0] -suck -1.9 1.04403 [-1, -1, -1, -2, -1, -1, -3, -4, -3, -2] -sucked -2.0 0.89443 [-2, -2, -1, -1, -1, -3, -4, -2, -2, -2] -sucker -2.4 1.2 [-3, -1, -1, -2, -1, -4, -4, -2, -4, -2] -suckered -2.0 1.0 [-2, -1, -1, -3, -3, -1, -1, -2, -2, -4] -suckering -2.1 0.7 [-2, -3, -2, -1, -2, -3, -3, -2, -1, -2] -suckers -2.3 1.00499 [-2, -1, -2, -4, -1, -2, -3, -2, -4, -2] -sucks -1.5 1.28452 [-1, -2, -2, -1, -3, -4, -1, 1, -1, -1] -sucky -1.9 0.9434 [-1, -2, -2, -1, -2, -4, -1, -1, -3, -2] -suffer -2.5 0.67082 [-3, -3, -2, -2, -3, -3, -3, -2, -1, -3] -suffered -2.2 0.74833 [-3, -2, -1, -3, -2, -3, -1, -3, -2, -2] -sufferer -2.0 0.63246 [-3, -2, -2, -2, -2, -3, -1, -2, -2, -1] -sufferers -2.4 0.8 [-1, -3, -3, -2, -1, -2, -3, -3, -3, -3] -suffering -2.1 0.83066 [-2, -1, -3, -2, -1, -2, -3, -3, -1, -3] -suffers -2.1 0.7 [-3, -2, -1, -2, -2, -2, -3, -1, -3, -2] -suicidal -3.5 0.67082 [-4, -4, -4, -4, -3, -4, -3, -3, -2, -4] -suicide -3.5 0.67082 [-4, -3, -4, -4, -4, -2, -3, -4, -4, -3] -suing -1.1 1.13578 [1, -1, -1, 0, -1, -3, -1, -1, -3, -1] -sulking -1.5 0.67082 [-2, -1, -3, -1, -1, -2, -1, -2, -1, -1] -sulky -0.8 1.77764 [-3, 3, -2, -3, 0, -2, 0, -1, 1, -1] -sullen -1.7 1.00499 [0, -2, -2, -1, -1, -4, -2, -1, -2, -2] -sunnier 2.3 0.64031 [3, 2, 3, 2, 3, 2, 2, 1, 3, 2] -sunniest 2.4 1.28062 [2, 0, 4, 2, 1, 3, 2, 4, 4, 2] -sunny 1.8 0.87178 [2, 2, 1, 2, 0, 2, 3, 3, 2, 1] -sunshine 2.2 0.6 [3, 1, 2, 2, 2, 2, 2, 3, 3, 2] -sunshiny 1.9 0.7 [2, 2, 3, 1, 2, 2, 1, 3, 1, 2] -super 2.9 0.7 [4, 2, 4, 3, 3, 3, 2, 3, 2, 3] -superb 3.1 0.9434 [3, 4, 2, 4, 3, 1, 3, 3, 4, 4] -superior 2.5 1.11803 [2, 3, 1, 3, 3, 0, 3, 3, 4, 3] -superiorities 0.8 1.6 [-1, 1, 3, -1, -1, 2, 2, 1, 3, -1] -superiority 1.4 1.2 [0, 1, -1, 3, 1, 2, 2, 2, 3, 1] -superiorly 2.2 1.4 [4, 3, 1, 2, 3, -1, 2, 4, 2, 2] -superiors 1.0 1.0 [3, 0, 0, 1, 2, 1, 1, 2, 0, 0] -support 1.7 0.9 [1, 1, 1, 2, 1, 3, 3, 3, 1, 1] -supported 1.3 0.45826 [2, 1, 2, 1, 1, 2, 1, 1, 1, 1] -supporter 1.1 0.3 [1, 1, 1, 1, 1, 2, 1, 1, 1, 1] -supporters 1.9 0.7 [1, 1, 1, 2, 2, 3, 2, 2, 3, 2] -supporting 1.9 0.9434 [3, 2, 1, 1, 3, 3, 1, 1, 3, 1] -supportive 1.2 0.4 [1, 1, 1, 1, 1, 2, 2, 1, 1, 1] -supportiveness 1.5 1.11803 [3, 1, 2, 1, 3, 2, 2, 1, -1, 1] -supports 1.5 0.67082 [2, 1, 2, 0, 2, 2, 2, 1, 1, 2] -supremacies 0.8 1.72047 [3, -2, 3, 0, 0, 2, -1, 3, 0, 0] -supremacist 0.5 2.15639 [3, 2, -3, 1, 2, 2, 2, -2, 1, -3] -supremacists -1.0 1.89737 [-4, -2, -1, -3, -2, 2, 2, 0, 0, -2] -supremacy 0.2 1.77764 [-1, -2, 0, 3, 2, 0, -3, 0, 1, 2] -suprematists 0.4 1.56205 [2, 1, 0, 0, 2, 2, 2, -2, -1, -2] -supreme 2.6 1.11355 [2, 3, 2, 1, 4, 2, 1, 3, 4, 4] -supremely 2.7 1.00499 [2, 4, 1, 4, 2, 4, 2, 3, 2, 3] -supremeness 2.3 0.64031 [1, 2, 2, 3, 3, 2, 2, 3, 3, 2] -supremer 2.3 1.1 [4, 3, 3, 0, 1, 2, 3, 2, 3, 2] -supremest 2.2 1.98997 [4, 3, 1, 0, 4, 4, -2, 3, 1, 4] -supremo 1.9 1.3 [1, 0, 3, 0, 4, 3, 1, 3, 2, 2] -supremos 1.3 0.78102 [0, 2, 2, 1, 0, 2, 2, 1, 2, 1] -sure 1.3 0.64031 [1, 1, 3, 1, 1, 2, 1, 1, 1, 1] -surefire 1.0 0.7746 [1, 1, 0, 2, 2, 1, 0, 1, 2, 0] -surefooted 1.9 0.83066 [0, 3, 2, 2, 2, 2, 1, 2, 3, 2] -surefootedly 1.6 0.91652 [1, 1, 2, 0, 2, 1, 3, 3, 1, 2] -surefootedness 1.5 1.20416 [2, 1, 4, 1, 0, 3, 2, 1, 1, 0] -surely 1.9 0.7 [2, 2, 2, 1, 1, 1, 3, 2, 3, 2] -sureness 2.0 0.7746 [2, 3, 2, 1, 2, 1, 3, 3, 2, 1] -surer 1.2 1.32665 [1, 1, 3, 1, 3, 2, 1, -2, 1, 1] -surest 1.3 0.78102 [2, 0, 2, 2, 2, 1, 0, 1, 1, 2] -sureties 1.3 0.9 [2, 0, 2, 0, 2, 2, 1, 2, 0, 2] -surety 1.0 0.44721 [1, 1, 1, 1, 1, 0, 1, 1, 2, 1] -suretyship -0.1 1.51327 [-1, 0, 0, -2, -1, 2, -2, 3, 0, 0] -suretyships 0.4 0.66332 [0, 0, 0, 1, 0, 0, 1, 0, 0, 2] -surprisal 1.5 0.80623 [3, 1, 1, 2, 1, 2, 2, 1, 2, 0] -surprisals 0.7 1.1 [0, 0, 0, 0, 0, 0, 0, 2, 2, 3] -surprise 1.1 1.04403 [0, 2, 0, 2, 3, 0, 1, 1, 2, 0] -surprised 0.9 0.9434 [2, 0, 0, 0, 0, 2, 2, 1, 2, 0] -surpriser 0.6 0.66332 [2, 0, 0, 0, 0, 1, 1, 1, 1, 0] -surprisers 0.3 1.00499 [2, 0, 1, 1, 0, 0, -2, 1, 0, 0] -surprises 0.9 0.7 [2, 0, 0, 0, 1, 1, 2, 1, 1, 1] -surprising 1.1 0.9434 [1, 1, 1, 0, 0, 2, 0, 1, 3, 2] -surprisingly 1.2 0.87178 [1, 0, 2, 0, 0, 2, 2, 1, 2, 2] -survived 2.3 0.78102 [3, 4, 2, 2, 2, 1, 2, 3, 2, 2] -surviving 1.2 0.87178 [1, 3, 1, 0, 2, 0, 1, 1, 1, 2] -survivor 1.5 1.0247 [1, 3, 2, 3, 1, 0, 0, 1, 2, 2] -suspect -1.2 0.9798 [0, -1, -1, -2, -2, -2, 1, -1, -2, -2] -suspected -0.9 1.13578 [-1, 0, -1, -2, -1, -1, -2, 2, -2, -1] -suspecting -0.7 1.34536 [-1, 2, -1, -1, -1, 1, -2, -1, -3, 0] -suspects -1.4 0.91652 [-2, -2, -2, -1, -2, -1, -2, -2, 1, -1] -suspend -1.3 0.64031 [0, -2, -1, -2, -1, -1, -2, -1, -2, -1] -suspended -2.1 0.83066 [-2, -1, -2, -3, -3, -1, -3, -1, -2, -3] -suspicion -1.6 0.91652 [-2, -2, -1, -2, 1, -2, -2, -2, -2, -2] -suspicions -1.5 0.67082 [-1, -2, -1, -2, -1, -1, -3, -1, -2, -1] -suspicious -1.5 0.67082 [-1, -2, -1, -1, -2, -1, -2, -1, -3, -1] -suspiciously -1.7 0.45826 [-2, -2, -1, -2, -1, -2, -2, -1, -2, -2] -suspiciousness -1.2 1.46969 [-2, -3, -2, -1, -1, 1, 2, -2, -2, -2] -sux -1.5 0.92195 [-1, -1, -2, -1, -2, -1, -3, 0, -3, -1] -swear -0.2 1.53623 [-2, 2, -1, 1, 1, 0, -1, -2, 2, -2] -swearing -1.0 1.09545 [0, -2, -1, -1, -2, 0, 1, -3, -1, -1] -swears 0.2 1.4 [1, -2, 2, 0, 1, -2, -1, 2, 1, 0] -sweet 2.0 0.63246 [1, 2, 2, 2, 3, 3, 2, 1, 2, 2] -sweet<3 3.0 0.44721 [3, 3, 3, 3, 4, 2, 3, 3, 3, 3] -sweetheart 3.3 1.00499 [4, 1, 3, 4, 4, 4, 2, 3, 4, 4] -sweethearts 2.8 0.87178 [2, 2, 2, 4, 3, 2, 4, 3, 4, 2] -sweetie 2.2 0.6 [2, 3, 3, 2, 1, 3, 2, 2, 2, 2] -sweeties 2.1 0.9434 [1, 2, 2, 3, 2, 1, 2, 4, 3, 1] -sweetly 2.1 0.7 [1, 2, 2, 2, 2, 2, 1, 3, 3, 3] -sweetness 2.2 0.74833 [3, 2, 3, 1, 2, 2, 3, 3, 2, 1] -sweets 2.2 0.6 [2, 1, 3, 2, 2, 2, 3, 2, 3, 2] -swift 0.8 0.6 [1, 0, 1, 1, 0, 2, 0, 1, 1, 1] -swiftly 1.2 0.9798 [0, 3, 1, 0, 1, 1, 1, 3, 1, 1] -swindle -2.4 1.0198 [-1, -4, -1, -3, -3, -2, -2, -2, -4, -2] -swindles -1.5 0.92195 [0, -2, -2, -3, -2, -1, -1, 0, -2, -2] -swindling -2.0 1.0 [-2, -2, -2, -4, -1, 0, -3, -2, -2, -2] -sympathetic 2.3 0.64031 [3, 3, 2, 2, 3, 3, 2, 2, 1, 2] -sympathy 1.5 1.11803 [-1, 2, 3, 2, 1, 1, 1, 2, 1, 3] -talent 1.8 1.07703 [3, 1, 2, 2, 0, 3, 3, 2, 2, 0] -talented 2.3 0.64031 [1, 2, 2, 3, 2, 3, 3, 2, 3, 2] -talentless -1.6 0.4899 [-2, -2, -2, -1, -2, -1, -1, -1, -2, -2] -talents 2.0 1.18322 [2, 4, 1, 2, 0, 2, 4, 2, 2, 1] -tantrum -1.8 1.16619 [-3, -2, -2, -3, -1, 0, -1, 0, -3, -3] -tantrums -1.5 1.36015 [-1, -2, -4, -2, -2, -1, -1, 0, 1, -3] -tard -2.5 0.92195 [-3, -3, -3, -2, -2, -3, -1, -4, -1, -3] -tears -0.9 1.13578 [0, -2, -2, -1, -1, -2, -2, 1, 1, -1] -teas 0.3 0.45826 [1, 0, 0, 0, 0, 1, 0, 1, 0, 0] -tease -1.3 0.9 [0, -1, -1, -2, -1, 0, -3, -2, -1, -2] -teased -1.2 0.87178 [0, -2, -2, -1, -1, -1, 0, -3, -1, -1] -teasel -0.1 0.3 [0, -1, 0, 0, 0, 0, 0, 0, 0, 0] -teaseled -0.8 0.74833 [-1, 0, -1, 0, 0, -1, -2, -1, -2, 0] -teaseler -0.8 0.87178 [0, 0, -2, 0, 0, -1, -2, -1, -2, 0] -teaselers -1.2 1.249 [0, -3, 0, 0, 0, -3, -2, -2, -2, 0] -teaseling -0.4 0.91652 [-1, 0, -3, 0, 0, 0, 0, 0, 0, 0] -teaselled -0.4 0.91652 [0, -3, 0, 0, 0, 0, -1, 0, 0, 0] -teaselling -0.2 0.4 [0, 0, 0, 0, -1, 0, -1, 0, 0, 0] -teasels -0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 0, -1, 0] -teaser -1.0 1.18322 [0, -1, -3, -1, -1, -1, 0, -3, -1, 1] -teasers -0.7 1.1 [-1, -2, -3, -1, 0, 0, -1, 1, 0, 0] -teases -1.2 0.74833 [-1, -1, 0, -1, -2, -1, -3, -1, -1, -1] -teashops 0.2 0.4 [0, 1, 0, 1, 0, 0, 0, 0, 0, 0] -teasing -0.3 1.1 [0, 0, 1, 1, -1, 0, 0, 0, -1, -3] -teasingly -0.4 1.11355 [0, 1, 1, 0, -2, 0, -2, 0, -2, 0] -teaspoon 0.2 0.4 [0, 0, 0, 0, 0, 0, 1, 0, 1, 0] -teaspoonful 0.2 0.4 [0, 0, 0, 1, 0, 0, 1, 0, 0, 0] -teaspoonfuls 0.4 0.8 [2, 0, 0, 0, 0, 0, 0, 0, 2, 0] -teaspoons 0.5 0.80623 [0, 0, 0, 2, 0, 0, 1, 2, 0, 0] -teaspoonsful 0.3 0.9 [2, 0, 0, 0, 0, 2, 0, -1, 0, 0] -temper -1.8 0.4 [-1, -2, -2, -2, -2, -2, -2, -2, -1, -2] -tempers -1.3 0.64031 [-1, -1, 0, -1, -1, -2, -2, -2, -1, -2] -tendered 0.5 0.92195 [0, 0, 2, 1, -1, -1, 1, 1, 1, 1] -tenderer 0.6 0.66332 [0, 1, 1, 0, 0, 0, 2, 1, 1, 0] -tenderers 1.2 0.9798 [2, 0, 0, 1, 0, 2, 3, 1, 1, 2] -tenderest 1.4 1.56205 [2, 1, 3, -1, 0, 2, 2, 2, -1, 4] -tenderfeet -0.4 0.91652 [-1, -1, 0, 0, -1, 0, -1, -2, 1, 1] -tenderfoot -0.1 0.53852 [-1, 1, 0, 0, 0, 0, 0, -1, 0, 0] -tenderfoots -0.5 1.11803 [1, -1, 0, 0, 0, -1, -1, 1, -3, -1] -tenderhearted 1.5 1.0247 [2, 2, 1, 2, 3, 1, 1, -1, 2, 2] -tenderheartedly 2.7 0.64031 [2, 2, 2, 3, 3, 3, 3, 4, 3, 2] -tenderheartedness 0.7 1.48661 [1, 3, 2, 2, -1, -1, 1, -2, 1, 1] -tenderheartednesses 2.8 0.74833 [2, 3, 3, 2, 3, 3, 4, 4, 2, 2] -tendering 0.6 0.66332 [0, 0, 1, 1, 1, 0, 0, 1, 2, 0] -tenderization 0.2 0.74833 [-1, 2, 0, 0, 0, 1, 0, 0, 0, 0] -tenderize 0.1 0.53852 [0, 0, 0, 0, 0, -1, 0, 1, 0, 1] -tenderized 0.1 0.53852 [0, 1, 0, 1, 0, 0, -1, 0, 0, 0] -tenderizer 0.4 0.66332 [0, 1, 0, 1, 0, 0, 2, 0, 0, 0] -tenderizes 0.3 0.45826 [0, 1, 0, 1, 0, 0, 1, 0, 0, 0] -tenderizing 0.3 0.45826 [1, 1, 0, 0, 0, 1, 0, 0, 0, 0] -tenderloin -0.2 0.74833 [0, 0, 0, 0, -2, 0, 1, 0, -1, 0] -tenderloins 0.4 0.66332 [1, 0, 0, 0, 2, 0, 0, 1, 0, 0] -tenderly 1.8 0.74833 [2, 1, 2, 1, 3, 2, 1, 2, 3, 1] -tenderness 1.8 0.4 [2, 2, 1, 2, 2, 2, 2, 1, 2, 2] -tendernesses 0.9 1.44568 [1, 2, 1, 1, 3, -1, -2, 2, 2, 0] -tenderometer 0.2 0.4 [1, 0, 0, 0, 0, 1, 0, 0, 0, 0] -tenderometers 0.2 0.4 [0, 0, 1, 0, 0, 0, 0, 0, 1, 0] -tenders 0.6 0.8 [0, 2, 0, 1, 1, 1, -1, 0, 1, 1] -tense -1.4 0.4899 [-1, -1, -1, -1, -1, -2, -1, -2, -2, -2] -tensed -1.0 0.44721 [-1, 0, -1, -1, -1, -1, -2, -1, -1, -1] -tensely -1.2 0.6 [-1, -2, -2, -2, -1, 0, -1, -1, -1, -1] -tenseness -1.5 0.67082 [-1, -1, -1, -1, -1, -2, -2, -1, -2, -3] -tenser -1.5 0.67082 [-2, -2, -1, -2, -1, -1, -3, -1, -1, -1] -tenses -0.9 1.04403 [-1, -3, 0, 0, 0, -1, 0, -2, -2, 0] -tensest -1.2 1.07703 [-2, 0, -2, -2, -2, 0, 1, -1, -2, -2] -tensing -1.0 0.44721 [-1, -2, -1, 0, -1, -1, -1, -1, -1, -1] -tension -1.3 1.00499 [-2, -1, -1, -1, -1, -2, -2, -3, 1, -1] -tensional -0.8 0.74833 [-1, 0, -1, -1, -1, -2, 1, -1, -1, -1] -tensioned -0.4 1.11355 [-2, 0, -1, 2, -1, 0, -1, -1, -1, 1] -tensioner -1.6 0.8 [-1, -3, -2, -2, -2, 0, -1, -2, -1, -2] -tensioners -0.9 1.04403 [-1, 0, -2, -2, -1, 1, -2, 0, 0, -2] -tensioning -1.4 1.0198 [-1, -1, -1, -1, 0, -2, -3, -3, 0, -2] -tensionless 0.6 0.8 [1, 1, 1, -1, 0, 0, 0, 2, 1, 1] -tensions -1.7 0.78102 [-1, -3, -1, -1, -2, -2, -3, -1, -2, -1] -terrible -2.1 0.9434 [-1, -3, -2, -1, -3, -1, -2, -2, -4, -2] -terribleness -1.9 1.81384 [3, -3, -3, -3, -3, -1, -2, -1, -3, -3] -terriblenesses -2.6 0.4899 [-2, -3, -3, -2, -3, -2, -2, -3, -3, -3] -terribly -2.6 0.4899 [-3, -3, -3, -2, -2, -3, -3, -2, -2, -3] -terrific 2.1 1.81384 [4, 3, 4, 1, -1, -1, 4, 2, 2, 3] -terrifically 1.7 1.95192 [2, 2, 4, 2, 3, 3, -2, 3, -2, 2] -terrified -3.0 0.63246 [-2, -3, -3, -3, -4, -3, -4, -2, -3, -3] -terrifies -2.6 1.0198 [-2, -4, -3, -3, -4, -1, -2, -3, -1, -3] -terrify -2.3 0.78102 [-3, -3, -2, -2, -1, -4, -2, -2, -2, -2] -terrifying -2.7 0.78102 [-4, -3, -3, -2, -2, -2, -4, -2, -3, -2] -terror -2.4 1.2 [-3, -4, -2, -1, 0, -4, -3, -2, -2, -3] -terrorise -3.1 0.83066 [-2, -3, -4, -4, -3, -3, -2, -4, -2, -4] -terrorised -3.3 0.64031 [-3, -3, -4, -3, -2, -4, -4, -3, -4, -3] -terrorises -3.3 0.45826 [-3, -3, -4, -3, -3, -4, -4, -3, -3, -3] -terrorising -3.0 0.44721 [-3, -3, -3, -3, -2, -3, -4, -3, -3, -3] -terrorism -3.6 0.4899 [-4, -3, -4, -4, -4, -3, -3, -4, -3, -4] -terrorisms -3.2 0.6 [-4, -4, -4, -3, -3, -3, -2, -3, -3, -3] -terrorist -3.7 0.45826 [-4, -3, -4, -4, -4, -3, -4, -4, -3, -4] -terroristic -3.3 0.78102 [-4, -3, -2, -3, -4, -3, -4, -2, -4, -4] -terrorists -3.1 0.9434 [-3, -4, -2, -2, -4, -2, -2, -4, -4, -4] -terrorization -2.7 0.9 [-4, -4, -3, -2, -2, -4, -2, -2, -2, -2] -terrorize -3.3 0.78102 [-4, -4, -3, -3, -4, -2, -2, -4, -3, -4] -terrorized -3.1 0.7 [-2, -3, -2, -4, -4, -4, -3, -3, -3, -3] -terrorizes -3.1 0.53852 [-2, -3, -3, -4, -3, -4, -3, -3, -3, -3] -terrorizing -3.0 1.0 [-3, -1, -4, -4, -4, -3, -2, -3, -2, -4] -terrorless 0.9 1.04403 [-2, 2, 1, 2, 1, 1, 1, 1, 1, 1] -terrors -2.6 0.4899 [-2, -3, -3, -3, -2, -2, -3, -2, -3, -3] -thank 1.5 0.92195 [3, 1, 1, 0, 1, 1, 2, 3, 1, 2] -thanked 1.9 1.22066 [1, 3, 1, 1, 1, 1, 4, 4, 2, 1] -thankful 2.7 0.78102 [4, 2, 2, 3, 2, 4, 3, 3, 2, 2] -thankfuller 1.9 0.53852 [2, 2, 1, 2, 2, 2, 1, 2, 3, 2] -thankfullest 2.0 1.0 [3, 1, 1, 4, 1, 2, 2, 2, 3, 1] -thankfully 1.8 0.6 [2, 1, 2, 1, 2, 3, 2, 2, 1, 2] -thankfulness 2.1 1.44568 [3, 3, 4, 2, 2, 1, -1, 1, 2, 4] -thanks 1.9 1.04403 [1, 1, 1, 1, 3, 2, 1, 4, 3, 2] -thief -2.4 0.66332 [-3, -2, -2, -2, -2, -4, -2, -2, -3, -2] -thieve -2.2 0.4 [-2, -2, -2, -3, -2, -2, -3, -2, -2, -2] -thieved -1.4 1.28062 [-1, -2, -3, -1, -2, 2, -2, -1, -2, -2] -thieveries -2.1 0.53852 [-2, -3, -2, -3, -1, -2, -2, -2, -2, -2] -thievery -2.0 0.89443 [-2, -2, -2, -1, -1, -3, -1, -2, -4, -2] -thieves -2.3 0.78102 [-3, -2, -2, -4, -1, -2, -2, -2, -3, -2] -thorny -1.1 0.83066 [1, -1, -1, -1, -1, -1, -1, -2, -2, -2] -thoughtful 1.6 0.4899 [2, 2, 1, 1, 1, 1, 2, 2, 2, 2] -thoughtfully 1.7 0.64031 [2, 1, 1, 3, 1, 2, 1, 2, 2, 2] -thoughtfulness 1.9 0.53852 [1, 2, 1, 2, 2, 3, 2, 2, 2, 2] -thoughtless -2.0 0.63246 [-2, -1, -3, -3, -2, -1, -2, -2, -2, -2] -threat -2.4 0.66332 [-2, -3, -2, -2, -2, -4, -3, -2, -2, -2] -threaten -1.6 1.56205 [-4, -1, -3, -2, 1, -3, -1, 1, -2, -2] -threatened -2.0 0.63246 [-2, -2, -3, -2, -2, -1, -2, -3, -1, -2] -threatener -1.4 1.68523 [-2, -2, -3, -2, 3, 0, -2, -3, -1, -2] -threateners -1.8 0.74833 [-3, -1, -2, -1, -1, -3, -2, -2, -2, -1] -threatening -2.4 0.8 [-3, -3, -2, -3, -2, -1, -3, -1, -3, -3] -threateningly -2.2 0.6 [-2, -2, -2, -2, -2, -2, -2, -2, -4, -2] -threatens -1.6 1.56205 [-2, -2, -2, 1, -4, -3, -3, -1, 1, -1] -threating -2.0 0.44721 [-3, -2, -2, -2, -1, -2, -2, -2, -2, -2] -threats -1.8 0.74833 [-1, -1, -1, -2, -2, -2, -3, -3, -2, -1] -thrill 1.5 1.11803 [2, 2, 2, 0, 1, -1, 2, 3, 2, 2] -thrilled 1.9 1.81384 [3, -1, 3, 3, 1, -2, 3, 3, 3, 3] -thriller 0.4 1.2 [0, 0, 3, 1, 1, -2, 0, 1, 0, 0] -thrillers 0.1 0.83066 [0, 2, 0, 0, 0, -1, 0, -1, 0, 1] -thrilling 2.1 1.04403 [3, 0, 2, 3, 1, 3, 3, 2, 1, 3] -thrillingly 2.0 0.7746 [0, 2, 2, 3, 3, 2, 2, 2, 2, 2] -thrills 1.5 0.92195 [2, 3, 1, 2, 0, 2, 1, 0, 2, 2] -thwarted -0.1 1.75784 [1, -2, -3, 0, 2, 0, 2, -2, -1, 2] -thwarting -0.7 0.78102 [0, 0, -1, -1, -1, -2, 1, -1, -1, -1] -thwarts -0.4 1.28062 [-2, 0, 0, -2, 0, 1, 2, 0, -1, -2] -ticked -1.8 0.6 [-2, -1, -1, -2, -2, -1, -2, -2, -3, -2] -timid -1.0 0.44721 [-1, -1, -1, -1, 0, -1, -2, -1, -1, -1] -timider -1.0 0.44721 [-1, -2, -1, -1, -1, 0, -1, -1, -1, -1] -timidest -0.9 0.7 [0, -1, 0, -1, 0, -1, -1, -2, -1, -2] -timidities -0.7 0.64031 [-1, -1, -1, 0, -2, 0, -1, 0, 0, -1] -timidity -1.3 0.45826 [-1, -2, -1, -1, -1, -1, -2, -2, -1, -1] -timidly -0.7 0.78102 [0, -1, -1, -1, -1, 1, 0, -1, -2, -1] -timidness -1.0 0.89443 [-1, -2, -1, 0, -1, -2, 1, -2, -1, -1] -timorous -0.8 0.9798 [-2, -1, -1, -1, -1, -2, -1, 1, 1, -1] -tired -1.9 0.7 [-2, -1, -2, -3, -2, -3, -1, -1, -2, -2] -tits -0.9 0.53852 [-1, -1, -2, -1, -1, -1, 0, -1, 0, -1] -tolerance 1.2 1.53623 [2, 3, 2, 2, -2, 1, 1, 3, -1, 1] -tolerances 0.3 0.9 [-1, 1, 0, 0, 1, 2, 0, -1, 1, 0] -tolerant 1.1 0.53852 [1, 2, 1, 1, 1, 1, 1, 1, 0, 2] -tolerantly 0.4 1.2 [0, 1, 1, 1, 0, -3, 1, 1, 1, 1] -toothless -1.4 1.0198 [-1, -4, -1, -2, -1, 0, -1, -2, -1, -1] -top 0.8 0.87178 [1, 3, 1, 1, 1, 0, 0, 1, 0, 0] -tops 2.3 1.00499 [3, 3, 3, 0, 2, 2, 3, 3, 1, 3] -torn -1.0 1.0 [-1, -1, -1, 0, -1, -1, -3, -2, 1, -1] -torture -2.9 1.51327 [-4, -4, -3, -4, 1, -2, -3, -2, -4, -4] -tortured -2.6 1.0198 [-4, -1, -2, -2, -4, -3, -2, -2, -4, -2] -torturer -2.3 1.18743 [-4, -1, -1, -2, -4, -1, -2, -2, -4, -2] -torturers -3.5 0.67082 [-4, -4, -3, -3, -4, -4, -4, -2, -3, -4] -tortures -2.5 0.92195 [-2, -3, -2, -4, -1, -3, -2, -4, -2, -2] -torturing -3.0 0.89443 [-4, -4, -4, -2, -3, -2, -4, -2, -2, -3] -torturous -2.7 0.78102 [-3, -3, -1, -3, -4, -2, -2, -3, -3, -3] -torturously -2.2 1.6 [2, -3, -3, -2, -3, -2, -4, -3, -1, -3] -totalitarian -2.1 1.3 [0, -4, -3, 0, -3, -2, -3, -1, -2, -3] -totalitarianism -2.7 1.18743 [-2, -3, 0, -4, -2, -4, -4, -2, -3, -3] -tough -0.5 1.43178 [0, -2, 0, 0, 1, 2, -1, -2, -3, 0] -toughed 0.7 0.64031 [1, 1, 0, 1, 1, 0, 2, 1, 0, 0] -toughen 0.1 1.04403 [0, 0, 1, 0, 1, 0, 2, 0, -2, -1] -toughened 0.1 0.53852 [1, 0, 0, 0, 0, -1, 1, 0, 0, 0] -toughening 0.9 0.83066 [0, 2, 2, 1, 1, 0, 1, 0, 0, 2] -toughens -0.2 1.16619 [1, -1, 0, 1, 0, -2, -2, 1, -1, 1] -tougher 0.7 1.00499 [1, 1, -1, 0, 2, 0, 2, 2, 0, 0] -toughest -0.3 1.84662 [2, 1, -1, -3, 0, -2, 2, -2, 2, -2] -toughie -0.7 0.64031 [-1, 1, 0, -1, -1, -1, -1, -1, -1, -1] -toughies -0.6 0.66332 [-1, -1, -1, 0, 0, -1, 1, -1, -1, -1] -toughing -0.5 1.20416 [-1, 0, -2, 0, 0, -2, 2, 0, -2, 0] -toughish -1.0 1.0 [0, -1, 0, -2, -2, -1, 1, -2, -2, -1] -toughly -1.1 0.83066 [-1, 0, 0, -1, 0, -1, -2, -2, -2, -2] -toughness -0.2 1.07703 [0, 0, -1, -2, 0, 1, 1, 1, -2, 0] -toughnesses 0.3 1.18743 [1, 2, -1, 0, 1, 1, -2, 1, -1, 1] -toughs -0.8 1.16619 [0, 0, -1, 0, -1, -3, -2, 1, 0, -2] -toughy -0.5 1.11803 [-1, -2, -1, 0, -1, -1, 1, -1, 2, -1] 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-1, -1] -tranquiler 1.9 0.7 [2, 1, 2, 2, 3, 3, 2, 2, 1, 1] -tranquilest 1.6 1.35647 [1, 2, 2, 2, 0, 2, -1, 4, 3, 1] -tranquilities 1.5 1.36015 [3, 2, 4, -1, 1, 0, 2, 2, 1, 1] -tranquility 1.8 1.16619 [3, 2, 1, 2, 3, 4, 1, 1, 1, 0] -tranquilize 0.3 1.00499 [0, -2, 1, -1, 1, 1, 1, 0, 1, 1] -tranquilized -0.2 1.32665 [-2, 0, 1, 0, 1, 2, 0, -2, -2, 0] -tranquilizer -0.1 0.9434 [0, 1, -1, 0, -1, 0, -2, 1, 1, 0] -tranquilizers -0.4 0.8 [0, 0, 0, -2, -1, -1, -1, 1, 0, 0] -tranquilizes -0.1 0.9434 [-2, 0, 1, 0, 1, 1, 0, -1, -1, 0] -tranquilizing -0.5 0.67082 [-1, 0, 0, -1, -1, -1, 1, 0, -1, -1] -tranquillest 0.8 1.4 [1, 1, 2, 3, 1, 1, 0, -1, -2, 2] -tranquillities 0.5 1.20416 [-2, 1, 2, 0, 2, 1, 0, -1, 1, 1] -tranquillity 1.8 1.07703 [1, 2, 2, 2, 3, 3, 2, -1, 2, 2] -tranquillized -0.2 1.07703 [0, 1, 0, 0, -3, 0, 1, 0, -1, 0] -tranquillizer -0.1 0.7 [0, 1, 0, 0, -1, 0, 1, 0, -1, -1] -tranquillizers -0.2 0.74833 [0, 0, 0, -2, 1, 0, 0, 0, -1, 0] -tranquillizes 0.1 0.7 [-1, -1, 0, 0, 1, 1, 1, 0, 0, 0] -tranquillizing 0.8 0.87178 [1, 2, 0, 2, 0, 0, 2, 0, 0, 1] -tranquilly 1.2 0.87178 [2, 2, 1, 2, -1, 2, 1, 1, 1, 1] -tranquilness 1.5 1.20416 [3, 3, 1, 2, 2, 2, 0, -1, 1, 2] -trap -1.3 0.78102 [-1, -1, -2, 0, -1, -1, -2, -1, -1, -3] -trapped -2.4 0.91652 [-3, -2, -3, -1, -3, -1, -2, -2, -4, -3] -trauma -1.8 1.249 [-2, -2, -3, -1, -2, 1, -2, -4, -1, -2] -traumas -2.2 1.6 [-3, -3, -2, -4, 0, -1, -4, -3, 1, -3] -traumata -1.7 1.34536 [-2, -3, -2, 0, -2, 1, -4, -2, -1, -2] -traumatic -2.7 1.00499 [-2, -4, -2, -1, -4, -3, -2, -3, -4, -2] -traumatically -2.8 0.6 [-4, -2, -3, -2, -2, -3, -3, -3, -3, -3] -traumatise -2.8 0.6 [-4, -3, -3, -2, -2, -3, -2, -3, -3, -3] -traumatised -2.4 0.91652 [-4, -4, -2, -2, -1, -2, -3, -2, -2, -2] -traumatises -2.2 0.87178 [-3, -4, -2, -2, -1, -2, -3, -1, -2, -2] -traumatising -1.9 1.86815 [-3, -3, -3, -1, -3, 1, -4, -2, 2, -3] -traumatism -2.4 0.4899 [-3, -2, -3, -2, -2, -2, -2, -3, -3, -2] -traumatization -3.0 1.0 [-4, -4, -4, -2, -2, -2, -4, -4, -2, -2] -traumatizations -2.2 1.16619 [-3, -2, -4, 0, -1, -2, -4, -2, -2, -2] -traumatize -2.4 0.66332 [-3, -3, -2, -4, -2, -2, -2, -2, -2, -2] -traumatized -1.7 1.41774 [-1, -2, -2, -2, 2, -4, -2, -2, -2, -2] -traumatizes -1.4 1.42829 [-2, -1, -2, -2, 2, -4, -1, -2, -1, -1] -traumatizing -2.3 1.61555 [-4, -2, -2, -3, -2, -4, -4, 1, 0, -3] -travesty -2.7 1.48661 [-3, -4, 0, -2, -4, -3, -4, 0, -3, -4] -treason -1.9 1.75784 [-3, -3, -2, -3, -3, 1, -2, -3, -3, 2] -treasonous -2.7 1.34536 [-3, -3, -3, -4, -3, -4, -2, 1, -3, -3] -treasurable 2.5 0.67082 [2, 3, 3, 3, 2, 4, 2, 2, 2, 2] -treasure 1.2 1.16619 [3, 1, 3, 2, 0, 2, 1, 0, 0, 0] -treasured 2.6 0.66332 [3, 3, 2, 3, 3, 2, 1, 3, 3, 3] -treasurer 0.5 0.67082 [1, 0, 0, 0, 1, 0, 0, 0, 1, 2] -treasurers 0.4 0.66332 [0, 0, 0, 0, 1, 1, 2, 0, 0, 0] -treasurership 0.4 0.66332 [0, 0, 2, 0, 1, 0, 1, 0, 0, 0] -treasurerships 1.2 0.87178 [2, 0, 2, 0, 2, 1, 2, 2, 1, 0] -treasures 1.8 1.32665 [3, 3, 0, 1, 1, 4, 0, 3, 2, 1] -treasuries 0.9 1.04403 [0, 0, 1, 3, 2, 2, 0, 1, 0, 0] -treasuring 2.1 0.7 [2, 1, 3, 1, 3, 2, 2, 2, 2, 3] -treasury 0.8 1.07703 [2, 3, 0, 0, 0, 0, 0, 1, 2, 0] -treat 1.7 0.78102 [2, 2, 2, 0, 2, 1, 3, 2, 1, 2] -tremble -1.1 1.3 [-2, 0, -1, -2, -2, -2, 2, 0, -2, -2] -trembled -1.1 1.22066 [-1, 1, -1, -2, -2, -1, -3, -2, 1, -1] -trembler -0.6 1.28062 [-2, -2, -1, 0, -1, 2, 1, -2, -1, 0] -tremblers -1.0 0.63246 [-2, 0, -1, -1, 0, -2, -1, -1, -1, -1] -trembles -0.1 1.51327 [-1, -2, -1, 0, -1, 2, 2, -2, 2, 0] -trembling -1.5 0.92195 [-3, 0, -1, -3, -1, -1, -1, -2, -1, -2] -trembly -1.2 0.87178 [-2, 0, -1, -2, -2, -1, 0, 0, -2, -2] -tremulous -1.0 1.09545 [-1, -2, -1, -1, -1, -1, 2, -2, -2, -1] -trick -0.2 1.32665 [-1, 1, -2, -2, -1, 2, 0, 1, 1, -1] -tricked -0.6 0.91652 [-1, -1, -1, -1, 2, 0, -1, -1, -1, -1] -tricker -0.9 0.83066 [-2, 0, -1, -1, 1, -2, -1, -1, -1, -1] -trickeries -1.2 1.46969 [-2, -2, -1, -2, -1, 2, 1, -2, -3, -2] -trickers -1.4 0.66332 [-1, -3, -1, -2, -2, -1, -1, -1, -1, -1] -trickery -1.1 1.51327 [1, -1, -1, -2, -3, -2, -3, 2, -1, -1] -trickie -0.4 1.0198 [1, -1, 0, -1, -1, 1, -2, -1, 1, -1] -trickier -0.7 0.78102 [-1, -1, -1, 0, 1, -1, -1, -1, 0, -2] -trickiest -1.2 0.6 [-2, -2, 0, -1, -2, -1, -1, -1, -1, -1] -trickily -0.8 0.74833 [0, 1, -1, -1, -1, -1, -1, -1, -2, -1] -trickiness -1.2 0.9798 [-2, -1, -1, -2, -1, -2, 1, 0, -2, -2] -trickinesses -0.4 1.0198 [0, 2, 0, -2, -1, -1, 0, 0, -1, -1] -tricking 0.1 1.37477 [0, -2, 2, -1, 2, -2, 0, 1, 1, 0] -trickish -1.0 0.44721 [-1, -2, 0, -1, -1, -1, -1, -1, -1, -1] -trickishly -0.7 1.55242 [-3, -2, -1, 2, -1, 2, -2, -1, 0, -1] -trickishness -0.4 1.28062 [-1, 1, -2, -1, -1, -1, 0, -2, 1, 2] -trickled 0.1 0.3 [0, 0, 0, 0, 0, 0, 0, 0, 1, 0] -trickledown -0.7 0.64031 [0, -1, 0, -1, -2, 0, 0, -1, -1, -1] -trickles 0.2 0.4 [0, 0, 0, 1, 0, 0, 0, 0, 1, 0] -trickling -0.2 0.9798 [0, 0, -1, -2, -1, 2, 0, 0, 0, 0] -trickly -0.3 0.45826 [0, 0, -1, 0, 0, 0, 0, -1, 0, -1] -tricks -0.5 0.67082 [0, 0, -1, -1, 1, -1, -1, 0, -1, -1] -tricksier -0.5 0.67082 [-1, -1, 1, 0, -1, 0, 0, -1, -1, -1] -tricksiness -1.0 0.89443 [0, 0, -1, -1, -1, 0, -1, -2, -3, -1] -trickster -0.9 0.83066 [-1, -2, 0, -1, -2, -1, -1, 1, -1, -1] -tricksters -1.3 0.9 [-1, -2, -1, -2, 1, -2, -2, -1, -1, -2] -tricksy -0.8 0.9798 [-1, -1, -2, -1, 2, -1, -1, -1, -1, -1] -tricky -0.6 0.66332 [0, 0, -1, -1, 1, -1, -1, -1, -1, -1] -trite -0.8 0.4 [-1, -1, 0, 0, -1, -1, -1, -1, -1, -1] -triumph 2.1 1.04403 [2, 4, 3, 3, 1, 3, 1, 2, 1, 1] -triumphal 2.0 0.63246 [2, 3, 3, 2, 1, 2, 1, 2, 2, 2] -triumphalisms 1.9 0.9434 [2, 1, 2, 2, 2, 0, 2, 2, 4, 2] -triumphalist 0.5 1.20416 [1, 1, 2, 2, -1, -2, 0, 1, 0, 1] -triumphalists 0.9 1.64012 [1, -1, 0, 0, 1, 3, -2, 3, 1, 3] -triumphant 2.4 0.91652 [2, 3, 3, 3, 4, 1, 2, 1, 3, 2] -triumphantly 2.3 1.00499 [3, 3, 3, 3, 1, 0, 3, 2, 2, 3] -triumphed 2.2 1.4 [2, 3, 3, 3, 4, 3, 1, 1, -1, 3] -triumphing 2.3 0.64031 [2, 2, 3, 2, 2, 3, 2, 3, 1, 3] -triumphs 2.0 1.41421 [3, 2, 3, 3, 3, 1, -1, 1, 1, 4] -trivial -0.1 0.83066 [0, -1, -1, 0, 1, 0, 1, -1, 1, -1] -trivialise -0.8 1.16619 [-3, -1, -2, 0, 1, -1, -1, 1, -1, -1] -trivialised -0.8 1.6 [-2, 0, -2, 1, -1, 0, 1, 1, -4, -2] -trivialises -1.1 0.53852 [-1, -1, -1, 0, -1, -1, -1, -2, -2, -1] -trivialising -1.4 0.66332 [-2, -1, -2, -1, 0, -1, -2, -1, -2, -2] -trivialities -1.0 0.63246 [-2, -2, -1, -1, -1, 0, 0, -1, -1, -1] -triviality -0.5 1.11803 [-1, -1, -2, 0, -1, -1, 2, -1, 1, -1] -trivialization -0.9 1.04403 [-1, 2, -1, -1, -2, -2, -1, -1, -1, -1] -trivializations -0.7 1.18743 [-2, -1, -1, -2, 1, -1, -1, -1, 2, -1] -trivialize -1.1 0.53852 [0, -2, -2, -1, -1, -1, -1, -1, -1, -1] -trivialized -0.6 0.8 [-1, -1, 0, 0, -1, -1, 1, -1, 0, -2] -trivializes -1.0 0.7746 [-1, -1, -1, 0, -1, 0, -1, -1, -1, -3] -trivializing -0.6 1.95959 [-1, -1, -2, -1, -1, 2, -2, -4, 1, 3] -trivially 0.4 1.56205 [-1, -1, -1, -1, 0, 3, 0, 2, 3, 0] -trivium -0.3 0.64031 [0, 0, -2, 0, 0, 0, 0, -1, 0, 0] -trouble -1.7 0.64031 [-2, -2, -1, -1, -3, -2, -1, -2, -1, -2] -troubled -2.0 0.44721 [-2, -2, -2, -1, -2, -3, -2, -2, -2, -2] -troublemaker -2.0 0.63246 [-3, -2, -3, -2, -2, -1, -1, -2, -2, -2] -troublemakers -2.2 0.74833 [-3, -3, -3, -1, -3, -1, -2, -2, -2, -2] -troublemaking -1.8 0.6 [-2, -1, -1, -2, -2, -2, -3, -2, -1, -2] -troubler -1.4 0.4899 [-1, -1, -2, -1, -1, -1, -2, -2, -2, -1] -troublers -1.9 0.3 [-2, -2, -2, -2, -1, -2, -2, -2, -2, -2] -troubles -2.0 0.44721 [-2, -2, -2, -1, -2, -3, -2, -2, -2, -2] -troubleshoot 0.8 0.9798 [0, 0, 0, 2, 2, 2, 2, 0, 0, 0] -troubleshooter 1.0 0.89443 [0, 0, 0, 1, 2, 2, 0, 1, 2, 2] -troubleshooters 0.8 0.87178 [0, 0, 1, 2, 0, 1, 0, 2, 2, 0] -troubleshooting 0.7 1.34536 [0, 2, 1, 1, -1, 2, 0, 2, -2, 2] -troubleshoots 0.5 0.92195 [1, -1, 0, 0, 0, 0, 1, 0, 2, 2] -troublesome -2.3 0.78102 [-3, -2, -3, -2, -3, -3, -1, -2, -1, -3] -troublesomely -1.8 0.6 [-3, -1, -2, -2, -1, -2, -2, -2, -2, -1] -troublesomeness -1.9 0.7 [-2, -1, -2, -3, -2, -3, -1, -2, -1, -2] -troubling -2.5 0.67082 [-3, -3, -3, -3, -1, -2, -3, -2, -3, -2] -troublous -2.1 0.53852 [-2, -2, -2, -2, -2, -3, -2, -3, -1, -2] -troublously -2.1 1.22066 [-2, -3, -3, -3, -2, -1, 1, -2, -3, -3] -trueness 2.1 0.9434 [2, 1, 1, 3, 3, 4, 2, 1, 2, 2] -truer 1.5 0.67082 [1, 2, 1, 2, 1, 1, 2, 1, 3, 1] -truest 1.9 0.83066 [2, 2, 2, 3, 3, 0, 2, 1, 2, 2] -truly 1.9 0.9434 [4, 3, 1, 2, 2, 1, 1, 1, 2, 2] -trust 2.3 1.26886 [0, 4, 3, 3, 4, 1, 2, 2, 1, 3] -trustability 2.1 0.7 [1, 3, 3, 2, 2, 2, 1, 3, 2, 2] -trustable 2.3 0.45826 [2, 2, 3, 2, 2, 3, 3, 2, 2, 2] -trustbuster -0.5 1.28452 [-3, -1, 0, 0, 0, 0, -2, 0, 2, -1] -trusted 2.1 0.9434 [3, 2, 2, 1, 4, 1, 2, 2, 3, 1] -trustee 1.0 0.89443 [2, 2, 0, 1, 1, 0, 2, 0, 2, 0] -trustees 0.3 0.64031 [0, 1, 0, 0, 2, 0, 0, 0, 0, 0] -trusteeship 0.5 0.67082 [0, 1, 1, 0, 0, 1, 0, 0, 2, 0] -trusteeships 0.6 1.0198 [3, 0, 0, 0, 0, 0, 0, 2, 1, 0] -truster 1.9 1.3 [2, 2, 1, 1, 4, 0, 3, 1, 4, 1] -trustful 2.1 0.9434 [1, 2, 2, 1, 2, 2, 1, 3, 3, 4] -trustfully 1.5 0.67082 [2, 1, 2, 1, 1, 3, 1, 2, 1, 1] -trustfulness 2.1 0.83066 [3, 2, 3, 2, 3, 2, 2, 2, 0, 2] -trustier 1.3 1.1 [1, 1, 1, 2, 0, 0, 3, 0, 3, 2] -trusties 1.0 0.7746 [1, 1, 0, 2, 1, 0, 2, 0, 1, 2] -trustiest 2.2 0.87178 [3, 2, 2, 3, 2, 2, 4, 1, 1, 2] -trustily 1.6 0.91652 [2, 0, 3, 1, 2, 1, 1, 1, 2, 3] -trustiness 1.6 0.91652 [2, 3, 0, 1, 2, 2, 2, 2, 0, 2] -trusting 1.7 1.00499 [3, 0, 1, 2, 3, 0, 2, 2, 2, 2] -trustingly 1.6 0.91652 [3, 1, 2, 3, 2, 2, 0, 1, 1, 1] -trustingness 1.6 1.2 [1, 2, 1, 3, 2, 1, 4, 2, 0, 0] -trustless -2.3 0.78102 [-2, -4, -3, -2, -2, -3, -2, -2, -1, -2] -trustor 0.4 0.66332 [2, 0, 0, 1, 0, 0, 0, 1, 0, 0] -trustors 1.2 0.87178 [0, 0, 2, 1, 1, 2, 2, 2, 0, 2] -trusts 2.1 0.53852 [2, 2, 2, 2, 1, 2, 2, 3, 2, 3] -trustworthily 2.3 0.9 [3, 1, 2, 2, 2, 1, 3, 4, 3, 2] -trustworthiness 1.8 0.74833 [2, 1, 3, 1, 2, 2, 1, 2, 3, 1] -trustworthy 2.6 0.91652 [3, 2, 3, 4, 2, 4, 2, 3, 1, 2] -trusty 2.2 0.74833 [3, 2, 3, 1, 2, 2, 3, 2, 1, 3] -truth 1.3 1.00499 [2, 1, 0, 1, 1, 0, 3, 3, 1, 1] -truthful 2.0 0.63246 [2, 2, 1, 3, 3, 2, 1, 2, 2, 2] -truthfully 1.9 1.04403 [3, 1, 3, 0, 2, 1, 3, 2, 1, 3] -truthfulness 1.7 1.1 [3, 2, 2, 2, 1, -1, 3, 2, 2, 1] -truths 1.8 0.87178 [0, 1, 1, 3, 2, 2, 3, 2, 2, 2] -tumor -1.6 1.49666 [-3, -2, -2, -1, -2, 1, -4, 1, -2, -2] -turmoil -1.5 0.92195 [-1, -1, -3, -3, -2, -2, -1, -1, 0, -1] -twat -3.4 0.91652 [-3, -4, -4, -4, -3, -1, -4, -4, -3, -4] -ugh -1.8 0.9798 [-1, -1, -1, -1, -1, -2, -4, -2, -3, -2] -uglier -2.2 0.87178 [-2, -2, -1, -3, -4, -1, -3, -2, -2, -2] -uglies -2.0 0.89443 [-2, -2, -1, -3, -4, -1, -2, -2, -1, -2] -ugliest -2.8 0.74833 [-3, -3, -4, -3, -3, -3, -3, -3, -1, -2] -uglification -2.2 0.87178 [-3, -1, -2, -2, -1, -2, -4, -3, -2, -2] -uglified -1.5 0.67082 [-1, -1, -3, -2, -2, -1, -1, -1, -2, -1] -uglifies -1.8 0.74833 [-1, -1, -3, -2, -3, -1, -2, -2, -2, -1] -uglify -2.1 0.9434 [-3, -3, -1, -4, -2, -2, -1, -2, -1, -2] -uglifying -2.2 0.4 [-3, -2, -2, -2, -2, -2, -2, -2, -3, -2] -uglily -2.1 0.3 [-3, -2, -2, -2, -2, -2, -2, -2, -2, -2] -ugliness -2.7 0.9 [-4, -2, -3, -2, -4, -2, -4, -2, -2, -2] -uglinesses -2.5 1.0247 [-3, -3, -2, -1, -1, -3, -2, -2, -4, -4] -ugly -2.3 0.9 [-3, -2, -1, -2, -4, -1, -3, -2, -2, -3] -unacceptable -2.0 0.44721 [-2, -2, -1, -2, -2, -2, -2, -3, -2, -2] -unappreciated -1.7 0.78102 [-1, -3, -2, -1, -1, -1, -2, -1, -2, -3] -unapproved -1.4 0.4899 [-1, -1, -1, -2, -2, -1, -2, -2, -1, -1] -unattractive -1.9 0.53852 [-1, -2, -3, -2, -1, -2, -2, -2, -2, -2] -unaware -0.8 0.4 [-1, -1, -1, 0, -1, -1, 0, -1, -1, -1] -unbelievable 0.8 1.6 [0, 0, 1, -2, 1, 3, 1, 0, 4, 0] -unbelieving -0.8 0.4 [0, -1, -1, -1, -1, -1, -1, 0, -1, -1] -unbiased -0.1 1.22066 [-2, -1, 2, 1, 0, -1, -1, 1, 1, -1] -uncertain -1.2 0.6 [-2, -1, -2, -1, -1, -1, 0, -1, -2, -1] -uncertainly -1.4 0.4899 [-2, -1, -1, -1, -2, -1, -1, -2, -2, -1] -uncertainness -1.3 0.45826 [-2, -2, -1, -1, -1, -1, -1, -2, -1, -1] -uncertainties -1.4 0.66332 [-3, -2, -1, -1, -1, -1, -1, -2, -1, -1] -uncertainty -1.4 0.4899 [-1, -1, -2, -1, -2, -1, -2, -1, -2, -1] -unclear -1.0 0.44721 [-2, -1, 0, -1, -1, -1, -1, -1, -1, -1] -uncomfortable -1.6 0.4899 [-2, -1, -2, -1, -1, -2, -2, -1, -2, -2] -uncomfortably -1.7 0.64031 [-2, -1, -3, -1, -1, -2, -2, -1, -2, -2] -uncompelling -0.9 0.7 [0, -2, -1, 0, -1, -1, -1, 0, -1, -2] -unconcerned -0.9 0.83066 [-2, -2, -1, 1, -1, -1, -1, 0, -1, -1] -unconfirmed -0.5 0.67082 [0, -1, 0, -1, 0, -1, 0, 0, -2, 0] -uncontrollability -1.7 0.45826 [-1, -1, -2, -2, -2, -2, -1, -2, -2, -2] -uncontrollable -1.5 1.11803 [-2, -1, -1, -2, -1, -1, 1, -2, -3, -3] -uncontrollably -1.5 0.67082 [-2, -1, 0, -2, -1, -1, -2, -2, -2, -2] -uncontrolled -1.0 0.7746 [-1, 0, -1, -2, -1, 0, -1, -2, -2, 0] -unconvinced -1.6 0.8 [-2, -3, -1, -2, -1, 0, -2, -2, -1, -2] -uncredited -1.0 1.09545 [-1, -2, -2, 2, -1, -2, -1, -1, -1, -1] -undecided -0.9 0.9434 [-1, 0, -1, 0, -1, -1, -2, 0, -3, 0] -underestimate -1.2 0.4 [-1, -2, -1, -1, -1, -1, -1, -1, -2, -1] -underestimated -1.1 0.53852 [-1, -1, -1, -2, 0, -1, -2, -1, -1, -1] -underestimates -1.1 1.64012 [-2, -4, 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2, 4, 1, 0, 3, 3, 2, 2, 3] -virtuosity 2.1 0.83066 [3, 3, 3, 2, 1, 3, 2, 2, 1, 1] -virtuoso 2.0 1.0 [2, 2, 3, 2, 1, 0, 3, 3, 3, 1] -virtuosos 1.8 1.16619 [2, 3, 1, -1, 2, 1, 3, 3, 2, 2] -virtuous 2.4 1.2 [0, 3, 2, 1, 3, 4, 2, 2, 4, 3] -virtuously 1.8 1.16619 [3, 2, 3, 1, 3, 1, -1, 2, 2, 2] -virtuousness 2.0 1.09545 [3, 4, 2, 2, 0, 1, 2, 3, 2, 1] -virulent -2.7 0.64031 [-3, -2, -4, -2, -3, -3, -2, -3, -2, -3] -vision 1.0 1.0 [0, 0, 0, 2, 1, 3, 2, 1, 1, 0] -visionary 2.4 1.0198 [1, 3, 1, 2, 4, 1, 3, 3, 3, 3] -visioning 1.1 0.9434 [1, 2, 0, 0, 3, 0, 1, 1, 2, 1] -visions 0.9 0.9434 [2, 0, 0, 0, 0, 1, 2, 2, 0, 2] -vital 1.2 1.46969 [-3, 2, 1, 1, 2, 2, 1, 2, 2, 2] -vitalise 1.1 0.9434 [1, 2, 0, 2, 2, 0, 2, 0, 2, 0] -vitalised 0.6 1.49666 [1, -2, 2, 0, 2, 1, -2, 2, 0, 2] -vitalises 1.1 1.3 [1, 2, 2, 0, 2, 2, -2, 2, 0, 2] -vitalising 2.1 0.53852 [2, 2, 3, 2, 3, 2, 2, 1, 2, 2] -vitalism 0.2 0.6 [0, 0, 0, 0, 0, 0, 0, 0, 2, 0] -vitalist 0.3 0.64031 [0, 0, 0, 0, 0, 0, 1, 0, 2, 0] -vitalists 0.3 1.34536 [2, -3, 1, 0, 0, 0, 1, 0, 2, 0] -vitalities 1.2 0.87178 [2, 1, 3, 1, 1, 0, 2, 1, 0, 1] -vitality 1.3 0.9 [3, 2, 0, 1, 1, 1, 2, 0, 2, 1] -vitalization 1.6 0.91652 [2, 3, 3, 1, 2, 1, 0, 2, 1, 1] -vitalizations 0.8 0.74833 [0, 1, 1, 2, 0, 0, 0, 2, 1, 1] -vitalize 1.6 0.66332 [3, 2, 2, 1, 2, 1, 1, 1, 2, 1] -vitalized 1.5 0.67082 [1, 1, 2, 2, 0, 2, 1, 2, 2, 2] -vitalizes 1.4 0.4899 [2, 1, 1, 2, 1, 2, 1, 2, 1, 1] -vitalizing 1.3 0.9 [3, 1, 0, 0, 1, 1, 2, 2, 2, 1] -vitally 1.1 0.53852 [0, 2, 1, 1, 1, 1, 2, 1, 1, 1] -vitals 1.1 0.7 [1, 0, 1, 2, 2, 0, 2, 1, 1, 1] -vitamin 1.2 0.87178 [3, 1, 0, 0, 1, 2, 1, 2, 1, 1] -vitriolic -2.1 0.83066 [-2, -2, -2, -4, -3, -2, -1, -1, -2, -2] -vivacious 1.8 0.9798 [0, 1, 3, 3, 3, 2, 2, 2, 1, 1] -vociferous -0.8 0.9798 [1, -2, -1, -2, -1, -1, 1, -1, -1, -1] -vulnerabilities -0.6 1.49666 [0, -3, -1, -1, -1, 2, -2, 2, -1, -1] -vulnerability -0.9 1.75784 [1, -1, -1, -2, 1, -3, -1, 2, -4, -1] -vulnerable -0.9 1.37477 [-2, -2, 2, -1, -3, -1, 1, -1, -1, -1] 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1, 2, 3, 2, 2, 2, -2, 2] -warmhearted 1.8 0.6 [3, 2, 2, 2, 2, 1, 2, 1, 1, 2] -warmheartedness 2.7 0.64031 [2, 4, 3, 2, 3, 3, 3, 2, 2, 3] -warming 0.6 0.8 [0, 0, 2, 2, 1, 1, 0, 0, 0, 0] -warmish 1.4 0.66332 [1, 3, 2, 1, 1, 1, 1, 2, 1, 1] -warmly 1.7 0.64031 [2, 1, 2, 1, 2, 1, 2, 1, 2, 3] -warmness 1.5 0.92195 [3, 1, 2, 1, 0, 1, 3, 2, 1, 1] -warmonger -2.9 1.13578 [-3, 0, -4, -4, -2, -3, -4, -3, -3, -3] -warmongering -2.5 0.67082 [-2, -3, -3, -1, -2, -3, -3, -2, -3, -3] -warmongers -2.8 0.87178 [-2, -3, -4, -4, -3, -1, -2, -3, -3, -3] -warmouth 0.4 0.66332 [0, 0, 2, 0, 0, 0, 0, 1, 1, 0] -warmouths -0.8 1.32665 [-1, -1, -2, -1, -2, -2, 0, 2, 1, -2] -warms 1.1 0.7 [2, 2, 1, 2, 1, 0, 1, 1, 0, 1] -warmth 2.0 0.44721 [2, 2, 2, 2, 1, 2, 2, 3, 2, 2] -warmup 0.4 0.66332 [0, 2, 0, 1, 1, 0, 0, 0, 0, 0] -warmups 0.8 0.9798 [0, 2, 0, 0, 0, 2, 2, 0, 2, 0] -warn -0.4 1.35647 [0, -1, 0, -2, -1, 2, 1, -2, 1, -2] -warned -1.1 0.53852 [-1, -1, -2, 0, -1, -1, -1, -2, -1, -1] -warning -1.4 1.0198 [-2, -1, 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0.5 [-2, -2, -1, -1, -2, -1, -1, -2, -1, -2] -weakside -1.1 1.37477 [-3, -2, -3, -1, -2, -1, 1, 1, -1, 0] -wealth 2.2 0.4 [2, 3, 2, 2, 2, 3, 2, 2, 2, 2] -wealthier 2.2 0.6 [3, 2, 1, 3, 2, 2, 2, 3, 2, 2] -wealthiest 2.2 0.9798 [2, 4, 4, 1, 2, 1, 2, 2, 2, 2] -wealthily 2.0 0.89443 [2, 3, 1, 4, 2, 1, 1, 2, 2, 2] -wealthiness 2.4 1.11355 [2, 4, 2, 4, 1, 2, 4, 1, 2, 2] -wealthy 1.5 1.0247 [1, 2, 1, 4, 1, 0, 2, 1, 2, 1] -weapon -1.2 0.87178 [0, -2, -2, -1, 0, -2, -1, -2, 0, -2] -weaponed -1.4 0.91652 [-2, -2, -3, -1, -1, 0, 0, -2, -1, -2] -weaponless 0.1 1.13578 [2, -1, 0, 0, -1, 1, -1, 0, 2, -1] -weaponry -0.9 0.7 [-2, -2, 0, -1, 0, -1, -1, -1, 0, -1] -weapons -1.9 0.9434 [-2, -1, -2, -2, -1, -3, -3, -3, -2, 0] -weary -1.1 1.13578 [-2, -1, -2, -3, 0, -1, -1, -2, 0, 1] -weep -2.7 0.9 [-2, -4, -4, -3, -3, -3, -3, -2, -1, -2] -weeper -1.9 0.53852 [-2, -2, -2, -3, -1, -1, -2, -2, -2, -2] -weepers -1.1 1.13578 [-2, -2, -1, -2, -1, 1, -2, 1, -1, -2] -weepie -0.4 0.91652 [0, 1, -1, 0, -1, -2, 0, 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0.64031 [-2, -1, -2, -1, -1, -2, -1, 0, -1, -2] -weirdos -1.1 0.9434 [-1, -1, -1, -2, 1, -3, -1, -1, -1, -1] -weirds -0.6 0.4899 [-1, -1, -1, 0, -1, 0, 0, -1, 0, -1] -weirdy -0.9 0.83066 [-1, -1, 0, 0, -1, 0, -2, -2, 0, -2] -welcome 2.0 0.63246 [1, 3, 2, 1, 2, 2, 2, 2, 3, 2] -welcomed 1.4 0.4899 [1, 1, 2, 2, 1, 2, 1, 2, 1, 1] -welcomely 1.9 0.53852 [2, 2, 2, 2, 1, 3, 2, 1, 2, 2] -welcomeness 2.0 0.89443 [2, 3, 1, 2, 3, 0, 2, 3, 2, 2] -welcomer 1.4 0.4899 [1, 1, 2, 2, 2, 2, 1, 1, 1, 1] -welcomers 1.9 0.7 [2, 2, 3, 2, 2, 1, 1, 3, 1, 2] -welcomes 1.7 0.78102 [1, 1, 2, 2, 3, 3, 1, 2, 1, 1] -welcoming 1.9 0.7 [2, 2, 1, 1, 2, 2, 2, 3, 3, 1] -well 1.1 1.04403 [0, 0, 2, 0, 2, 0, 1, 1, 3, 2] -welladay 0.3 1.18743 [2, -2, 0, 0, -1, 1, 0, 1, 2, 0] -wellaway -0.8 1.98997 [3, -2, -3, -3, -1, -2, 1, -2, -1, 2] -wellborn 1.8 0.74833 [2, 1, 2, 1, 2, 2, 1, 3, 1, 3] -welldoer 2.5 0.67082 [2, 2, 2, 3, 2, 3, 4, 3, 2, 2] -welldoers 1.6 0.8 [3, 1, 1, 0, 2, 1, 2, 2, 2, 2] -welled 0.4 0.8 [0, 0, 2, 0, 0, 0, 0, 0, 2, 0] -wellhead 0.1 0.3 [0, 0, 1, 0, 0, 0, 0, 0, 0, 0] -wellheads 0.5 0.92195 [0, 2, 0, 2, -1, 0, 1, 1, 0, 0] -wellhole -0.1 0.3 [0, 0, 0, -1, 0, 0, 0, 0, 0, 0] -wellies 0.4 0.4899 [0, 1, 0, 0, 0, 1, 0, 0, 1, 1] -welling 1.6 0.8 [2, 0, 1, 2, 2, 1, 3, 2, 2, 1] -wellness 1.9 0.9434 [1, 2, 2, 1, 2, 1, 1, 3, 4, 2] -wells 1.0 1.0 [2, 0, 3, 0, 1, 0, 2, 1, 1, 0] -wellsite 0.5 0.67082 [0, 0, 1, 2, 0, 0, 0, 0, 1, 1] -wellspring 1.5 0.92195 [3, 1, 1, 1, 0, 2, 2, 3, 1, 1] -wellsprings 1.4 0.8 [1, 0, 0, 2, 2, 2, 1, 2, 2, 2] -welly 0.2 0.4 [0, 0, 0, 1, 0, 1, 0, 0, 0, 0] -wept -2.0 1.09545 [-3, -2, -3, -3, -1, -3, 0, -1, -1, -3] -whimsical 0.3 1.61555 [2, 1, 1, 2, -1, 1, -3, -2, 1, 1] -whine -1.5 1.11803 [-1, -4, -1, -1, -1, -3, 0, -2, -1, -1] -whined -0.9 1.04403 [-2, -1, -2, -1, -1, -1, -2, 1, 1, -1] -whiner -1.2 0.4 [-1, -2, -1, -1, -1, -2, -1, -1, -1, -1] -whiners -0.6 1.95959 [-2, 0, -2, -2, 4, 1, 1, -2, -2, -2] -whines -1.8 0.6 [-2, -2, -2, -1, -2, -2, -3, -1, -2, -1] -whiney -1.3 0.45826 [-1, -2, -1, -1, -1, -2, -2, -1, -1, -1] -whining -0.9 1.51327 [-3, 0, -1, -1, -3, -1, 1, 2, -2, -1] -whitewash 0.1 0.7 [-1, 0, 1, -1, 0, 0, 0, 1, 1, 0] -whore -3.3 0.64031 [-4, -4, -3, -2, -3, -4, -3, -3, -4, -3] -whored -2.8 0.87178 [-2, -3, -4, -2, -2, -3, -4, -4, -2, -2] -whoredom -2.1 2.02237 [-4, -2, -4, -3, -3, -3, -4, -1, 2, 1] -whoredoms -2.4 1.11355 [-1, -3, 0, -3, -2, -3, -3, -4, -2, -3] -whorehouse -1.1 2.11896 [-2, -2, -2, 3, 3, -3, -3, -2, -1, -2] -whorehouses -1.9 1.92094 [-4, -3, -4, -3, 0, 0, -3, 2, -1, -3] -whoremaster -1.9 1.22066 [-1, -3, -3, -2, -1, -3, 0, 0, -3, -3] -whoremasters -1.5 1.85742 [-3, -1, -1, -4, -2, 2, -1, 1, -2, -4] -whoremonger -2.6 0.91652 [-3, -1, -3, -3, -3, -3, -3, -1, -4, -2] -whoremongers -2.0 1.78885 [-4, -3, 0, -3, -3, -3, -3, 1, 1, -3] -whores -3.0 1.0 [-3, -3, -4, -2, -1, -3, -4, -4, -2, -4] -whoreson -2.2 1.46969 [-2, -3, -4, -4, -3, -1, -1, 1, -3, -2] -whoresons -2.5 1.20416 [-3, -3, -2, -2, 0, -4, -3, -1, -3, -4] -wicked -2.4 0.8 [-3, -4, -3, -3, -2, -2, -2, -1, -2, -2] -wickeder -2.2 1.32665 [-2, -3, -1, -4, 1, -3, -3, -3, -2, -2] -wickedest -2.9 1.04403 [-3, -1, -3, -3, -3, -3, -1, -4, -4, -4] -wickedly -2.1 0.83066 [-2, -2, -1, -3, -2, -3, -1, -3, -1, -3] -wickedness -2.1 0.83066 [-2, -1, -2, -2, -3, -1, -2, -4, -2, -2] -wickednesses -2.2 1.16619 [-1, -2, -4, -2, -3, -1, -3, -4, -1, -1] -widowed -2.1 1.22066 [0, -4, -2, -4, -3, -2, -2, -2, -1, -1] -willingness 1.1 0.7 [0, 2, 1, 1, 2, 2, 1, 0, 1, 1] -wimp -1.4 1.28062 [-2, -3, -1, -2, -1, -2, -2, -1, 2, -2] -wimpier -1.0 1.18322 [-1, -2, -2, -1, -2, 0, 1, -2, 1, -2] -wimpiest -0.9 1.22066 [-3, -1, -2, -1, -2, -1, 1, 1, 0, -1] -wimpiness -1.2 0.9798 [1, -1, -3, -1, -2, -1, -1, -1, -2, -1] -wimpish -1.6 0.4899 [-2, -1, -2, -1, -2, -2, -1, -2, -2, -1] -wimpishness -0.2 1.249 [-3, -1, 0, -1, -1, 1, 1, 1, 1, 0] -wimple -0.2 0.74833 [0, -1, 0, 0, 0, 0, -2, 0, 0, 1] -wimples -0.3 0.78102 [-2, 0, 0, 0, 0, -1, 0, -1, 1, 0] -wimps -1.0 1.18322 [-2, -2, -1, -1, 0, -2, -2, 1, -2, 1] -wimpy -0.9 1.04403 [-2, -1, -1, -1, -1, -2, -1, 1, -2, 1] -win 2.8 0.87178 [3, 2, 4, 3, 2, 4, 3, 1, 3, 3] -winnable 1.8 0.6 [3, 2, 2, 2, 2, 1, 1, 1, 2, 2] -winned 1.8 0.6 [2, 2, 2, 2, 1, 2, 1, 1, 3, 2] -winner 2.8 0.87178 [2, 2, 2, 3, 4, 2, 3, 4, 2, 4] -winners 2.1 1.44568 [3, 3, 2, 3, 3, 2, 2, -2, 3, 2] -winning 2.4 0.4899 [2, 3, 3, 2, 2, 2, 3, 3, 2, 2] -winningly 2.3 1.48661 [1, 3, 4, 3, 3, 1, 2, 3, -1, 4] -winnings 2.5 0.92195 [3, 4, 3, 2, 2, 3, 1, 1, 3, 3] -winnow -0.3 1.00499 [0, -1, 0, -2, 1, 1, -2, 0, 0, 0] -winnower -0.1 0.3 [0, 0, 0, 0, 0, -1, 0, 0, 0, 0] -winnowers -0.2 0.6 [0, 0, 0, 0, 0, 0, 0, 0, -2, 0] -winnowing -0.1 0.53852 [0, 0, -1, 0, 0, 0, 0, 1, -1, 0] -winnows -0.2 0.4 [0, 0, -1, -1, 0, 0, 0, 0, 0, 0] -wins 2.7 0.78102 [2, 2, 3, 3, 4, 4, 3, 2, 2, 2] -wisdom 2.4 0.66332 [2, 3, 4, 2, 3, 2, 2, 2, 2, 2] -wise 2.1 0.83066 [2, 3, 1, 4, 2, 2, 1, 2, 2, 2] -wiseacre -1.2 1.16619 [-2, -1, -2, -2, -2, -1, -2, 1, 1, -2] -wiseacres -0.1 0.9434 [-2, 1, 0, -1, 0, 1, 1, -1, 0, 0] -wiseass -1.8 0.6 [-2, -2, -1, -1, -2, -2, -3, -2, -1, -2] -wiseasses -1.5 1.36015 [-1, -2, 2, -2, -1, -3, -2, -3, -1, -2] -wisecrack -0.1 1.22066 [-1, -1, -1, -2, 2, 1, -1, 1, 1, 0] -wisecracked -0.5 0.92195 [1, 1, -1, -1, 0, -1, -2, 0, -1, -1] -wisecracker -0.1 0.7 [-1, 1, -1, -1, 0, 0, 0, 0, 1, 0] -wisecrackers 0.1 1.04403 [-1, 0, 1, 1, 0, 2, 1, -1, -1, -1] -wisecracking -0.6 0.4899 [0, 0, -1, 0, -1, 0, -1, -1, -1, -1] -wisecracks -0.3 1.55242 [1, 2, -1, 2, -3, 0, 0, -2, -1, -1] -wised 1.5 0.67082 [2, 2, 2, 1, 1, 2, 0, 1, 2, 2] -wiseguys 0.3 1.9 [4, -1, 1, -1, 1, 2, 2, -2, -2, -1] -wiselier 0.9 1.3 [1, 2, 2, -2, 0, 1, 3, 1, 0, 1] -wiseliest 1.6 1.49666 [1, 4, 2, 2, 1, 2, 2, 3, -2, 1] -wisely 1.8 0.6 [1, 2, 3, 2, 1, 2, 2, 1, 2, 2] -wiseness 1.9 0.7 [2, 3, 2, 2, 3, 1, 1, 1, 2, 2] -wisenheimer -1.0 1.18322 [-1, 1, -1, -1, -1, 0, -1, -3, 0, -3] -wisenheimers -1.4 0.91652 [-3, -3, -2, -1, -1, -1, 0, -1, -1, -1] -wisents 0.4 0.91652 [0, 0, 0, 0, 1, 0, 0, 0, 3, 0] -wiser 1.2 0.87178 [1, 3, 0, 1, 1, 2, 0, 2, 1, 1] -wises 1.3 1.48661 [3, 3, 2, -2, 2, 0, 0, 2, 2, 1] -wisest 2.1 1.51327 [1, 3, 3, 3, 3, 2, 2, 3, -2, 3] -wisewomen 1.3 0.9 [2, 2, 0, 0, 2, 0, 1, 2, 2, 2] -wish 1.7 1.1 [2, 1, 1, 0, 2, 1, 3, 2, 4, 1] -wishes 0.6 0.8 [0, 0, 1, 0, 1, 0, 2, 0, 2, 0] -wishing 0.9 0.7 [2, 1, 1, 0, 0, 0, 1, 1, 2, 1] -witch -1.5 0.80623 [-1, -2, -2, -1, -3, 0, -2, -2, -1, -1] -withdrawal 0.1 1.57797 [1, -1, 0, -2, -2, 2, -1, 1, 0, 3] -woe -1.8 0.6 [-3, -2, -2, -2, -1, -1, -2, -1, -2, -2] -woebegone -2.6 0.66332 [-3, -2, -3, -2, -2, -4, -3, -2, -2, -3] -woebegoneness -1.1 1.37477 [-3, 0, -1, 1, -1, -4, 0, -1, -1, -1] -woeful -1.9 0.83066 [-1, -2, -2, -1, -3, -3, -1, -2, -1, -3] -woefully -1.7 1.48661 [-1, -3, -2, 1, -3, -3, -2, -2, 1, -3] -woefulness -2.1 0.7 [-3, -2, -2, -1, -2, -3, -3, -1, -2, -2] -woes -1.9 0.83066 [-2, -2, -2, -1, -2, -3, -3, 0, -2, -2] -woesome -1.2 1.6 [-2, -3, -2, -1, 0, 3, -2, -2, -1, -2] -won 2.7 0.9 [3, 4, 2, 2, 2, 4, 4, 2, 2, 2] -wonderful 2.7 0.78102 [2, 3, 3, 2, 4, 2, 2, 3, 4, 2] -wonderfully 2.9 0.83066 [1, 3, 3, 4, 3, 2, 3, 3, 4, 3] -wonderfulness 2.9 0.53852 [3, 2, 3, 3, 3, 3, 3, 2, 4, 3] -woo 2.1 1.37477 [4, 2, 1, 3, 2, 2, -1, 2, 2, 4] -woohoo 2.3 1.1 [3, 3, 1, 4, 4, 2, 1, 1, 2, 2] -woot 1.8 1.07703 [2, 0, 2, 2, 2, 2, 0, 4, 2, 2] -worn -1.2 0.4 [-1, -1, -1, -1, -1, -1, -2, -1, -2, -1] -worried -1.2 0.74833 [-1, -1, -1, -1, -1, -2, -3, 0, -1, -1] -worriedly -2.0 0.44721 [-2, -2, -3, -2, -2, -2, -2, -1, -2, -2] -worrier -1.8 0.6 [-2, -2, -1, -2, -1, -3, -2, -2, -1, -2] -worriers -1.7 0.45826 [-2, -1, -2, -2, -2, -2, -1, -2, -1, -2] -worries -1.8 0.6 [-2, -2, -1, -2, -1, -2, -2, -3, -1, -2] -worriment -1.5 0.67082 [-1, -2, -1, -1, -1, -2, -1, -3, -1, -2] -worriments -1.9 0.7 [-2, -1, -2, -3, -1, -2, -3, -1, -2, -2] -worrisome -1.7 0.64031 [-1, -1, -1, -2, -1, -2, -3, -2, -2, -2] -worrisomely -2.0 0.63246 [-1, -2, -1, -2, -2, -3, -2, -2, -3, -2] -worrisomeness -1.9 0.53852 [-2, -2, -3, -1, -2, -2, -2, -1, -2, -2] -worrit -2.1 0.53852 [-2, -2, -1, -2, -2, -3, -3, -2, -2, -2] -worrits -1.2 0.9798 [-1, -2, -2, -1, 0, 0, -1, -3, 0, -2] -worry -1.9 0.7 [-2, -3, -1, -3, -1, -2, -1, -2, -2, -2] -worrying -1.4 0.66332 [-2, -1, -2, -2, -1, 0, -1, -1, -2, -2] -worrywart -1.8 0.9798 [-2, -2, -2, -1, -1, -1, -1, -3, -1, -4] -worrywarts -1.5 0.5 [-2, -1, -2, -2, -2, -1, -1, -1, -2, -1] -worse -2.1 0.83066 [-2, -2, -1, -3, -4, -2, -1, -2, -2, -2] -worsen -2.3 0.78102 [-4, -3, -1, -2, -2, -2, -2, -3, -2, -2] -worsened -1.9 1.22066 [-2, -2, -2, -1, -2, -2, -4, 1, -3, -2] -worsening -2.0 0.44721 [-2, -3, -2, -2, -2, -2, -1, -2, -2, -2] -worsens -2.1 0.53852 [-2, -2, -2, -2, -1, -2, -2, -3, -3, -2] -worser -2.0 0.89443 [-2, -2, -4, -1, -2, -2, -2, -3, -1, -1] -worship 1.2 1.07703 [1, 0, 0, 1, 3, 0, 2, 3, 1, 1] -worshiped 2.4 1.0198 [1, 2, 4, 3, 4, 1, 2, 3, 2, 2] -worshiper 1.0 1.0 [0, 0, 2, 3, 0, 2, 1, 1, 1, 0] -worshipers 0.9 0.83066 [0, 0, 0, 2, 1, 1, 1, 2, 2, 0] -worshipful 0.7 1.00499 [1, -1, 3, 1, 1, 1, 0, 0, 0, 1] -worshipfully 1.1 1.3 [0, 0, 0, 1, 3, 0, 3, 3, 1, 0] -worshipfulness 1.6 0.8 [3, 1, 2, 2, 1, 1, 3, 1, 1, 1] -worshiping 1.0 1.18322 [0, 3, 0, 3, 0, 1, 1, 2, 0, 0] -worshipless -0.6 1.0198 [0, -1, -3, -1, -1, -1, 0, 0, 0, 1] -worshipped 2.7 0.78102 [3, 2, 3, 3, 1, 4, 2, 3, 3, 3] -worshipper 0.6 0.66332 [1, 1, 0, 0, 1, 0, 0, 2, 1, 0] -worshippers 0.8 0.87178 [0, 1, 0, 0, 3, 1, 1, 1, 0, 1] -worshipping 1.6 1.28062 [1, 3, 3, 3, 0, 3, 1, 0, 2, 0] -worships 1.4 1.11355 [2, 0, 1, 3, 2, 1, 0, 3, 2, 0] -worst -3.1 1.04403 [-4, -4, -3, -1, -3, -4, -2, -2, -4, -4] -worth 0.9 0.9434 [0, 0, 1, 1, 2, 1, 1, 3, 0, 0] -worthless -1.9 1.13578 [-3, -1, -3, -4, -1, -3, -1, -1, -1, -1] -worthwhile 1.4 0.4899 [1, 1, 1, 2, 1, 1, 2, 1, 2, 2] -worthy 1.9 0.53852 [2, 2, 2, 1, 1, 2, 2, 2, 3, 2] -wow 2.8 0.9798 [2, 3, 2, 4, 4, 3, 3, 2, 1, 4] -wowed 2.6 0.8 [3, 3, 4, 3, 2, 1, 3, 3, 2, 2] -wowing 2.5 0.67082 [2, 2, 3, 3, 2, 3, 4, 2, 2, 2] -wows 2.0 1.61245 [2, 3, 3, 3, 2, 1, -2, 1, 4, 3] -wowser -1.1 2.02237 [-3, 3, 0, 2, -2, -1, -3, -2, -2, -3] -wowsers 1.0 2.14476 [0, -2, 4, 2, 3, 0, 1, 2, -3, 3] -wrathful -2.7 0.64031 [-3, -2, -2, -3, -3, -2, -4, -2, -3, -3] -wreck -1.9 0.7 [-1, -2, -3, -3, -2, -2, -2, -1, -1, -2] -wrong -2.1 1.04403 [-2, -2, -2, -2, -4, -4, -1, -1, -1, -2] -wronged -1.9 0.53852 [-2, -2, -2, -2, -2, -1, -3, -2, -2, -1] -x-d 2.6 0.91652 [2, 3, 3, 4, 1, 2, 3, 4, 2, 2] -x-p 1.7 0.45826 [2, 2, 1, 2, 2, 1, 1, 2, 2, 2] -xd 2.8 0.87178 [3, 3, 4, 2, 3, 3, 1, 2, 4, 3] -xp 1.6 0.4899 [2, 2, 2, 1, 1, 1, 2, 2, 1, 2] -yay 2.4 1.0198 [1, 3, 3, 2, 2, 1, 4, 4, 2, 2] -yeah 1.2 0.6 [1, 1, 1, 2, 1, 1, 0, 2, 1, 2] -yearning 0.5 1.0247 [0, 1, 0, 1, 0, 3, 0, 1, -1, 0] -yeees 1.7 1.00499 [1, 3, 1, 2, 1, 1, 4, 2, 1, 1] -yep 1.2 0.4 [1, 1, 1, 1, 1, 1, 2, 2, 1, 1] -yes 1.7 0.78102 [1, 2, 2, 1, 1, 1, 3, 3, 1, 2] -youthful 1.3 0.45826 [1, 2, 1, 2, 1, 1, 1, 1, 2, 1] -yucky -1.8 0.6 [-2, -1, -1, -2, -2, -1, -2, -2, -3, -2] -yummy 2.4 1.0198 [1, 2, 4, 3, 2, 2, 3, 1, 4, 2] -zealot -1.9 1.04403 [-2, -3, -1, -2, -1, -3, -4, -1, -1, -1] -zealots -0.8 1.83303 [-1, -2, -1, -2, -2, 1, -2, 4, -1, -2] -zealous 0.5 1.43178 [2, -1, 2, 1, 0, 0, 3, 0, -2, 0] -{: 1.8 0.9798 [1, 3, 2, 2, 1, 1, 4, 2, 1, 1] -|-0 -1.2 0.74833 [0, -2, -1, -1, -1, -1, -1, -1, -1, -3] -|-: -0.8 0.74833 [-1, -2, 0, -1, 0, -2, -1, -1, 0, 0] -|-:> -1.6 0.4899 [-1, -2, -2, -2, -2, -1, -1, -2, -2, -1] -|-o -1.2 0.9798 [-1, 0, -1, -1, -1, -1, -1, -4, -1, -1] -|: -0.5 1.68819 [2, -3, -1, 0, -1, -1, -1, -2, -1, 3] -|;-) 2.2 1.32665 [4, 1, 1, 1, 3, 2, 4, 1, 4, 1] -|= -0.4 1.56205 [2, -2, -1, 0, -1, -1, -1, -2, -1, 3] -|^: -1.1 0.7 [-2, 0, -1, -1, 0, -1, -1, -2, -2, -1] -|o: -0.9 0.53852 [-1, 0, -1, -2, -1, 0, -1, -1, -1, -1] -||-: -2.3 0.45826 [-2, -2, -2, -3, -3, -3, -2, -2, -2, -2] -}: -2.1 0.83066 [-1, -1, -3, -2, -3, -2, -2, -1, -3, -3] -}:( -2.0 0.63246 [-3, -1, -2, -1, -3, -2, -2, -2, -2, -2] -}:) 0.4 1.42829 [1, 1, -2, 1, 2, -2, 1, -1, 2, 1] -}:-( -2.1 0.7 [-2, -1, -2, -2, -2, -4, -2, -2, -2, -2] -}:-) 0.3 1.61555 [1, 1, -2, 1, -1, -3, 2, 2, 1, 1] \ No newline at end of file