├── .gitignore
├── 1. Text Representation.ipynb
├── 2. Topic Modeling.ipynb
├── 3. Sentiment Analysis.ipynb
├── 4. Applications.ipynb
├── LICENSE
├── README.md
├── d4sci.mplstyle
├── data
    ├── Apple-Twitter-Sentiment-DFE.csv
    ├── D4Sci_logo_ball.png
    ├── D4Sci_logo_full.png
    ├── googlebooks-eng-all-1gram-20120701-a.gz
    ├── mary.pickle
    ├── negative-words.txt
    ├── nltk_stopwords.txt
    ├── polyglot-en.pkl
    ├── positive-words.txt
    ├── questions-words.txt
    ├── table_langs.dat
    ├── text8.gz
    └── vader_lexicon.txt
├── requirements.txt
└── slides
    └── NLP.pdf


/.gitignore:
--------------------------------------------------------------------------------
  1 | *.key
  2 | 
  3 | # Byte-compiled / optimized / DLL files
  4 | __pycache__/
  5 | *.py[cod]
  6 | *$py.class
  7 | 
  8 | # C extensions
  9 | *.so
 10 | 
 11 | # Distribution / packaging
 12 | .Python
 13 | build/
 14 | develop-eggs/
 15 | dist/
 16 | downloads/
 17 | eggs/
 18 | .eggs/
 19 | lib/
 20 | lib64/
 21 | parts/
 22 | sdist/
 23 | var/
 24 | wheels/
 25 | *.egg-info/
 26 | .installed.cfg
 27 | *.egg
 28 | MANIFEST
 29 | 
 30 | # PyInstaller
 31 | #  Usually these files are written by a python script from a template
 32 | #  before PyInstaller builds the exe, so as to inject date/other infos into it.
 33 | *.manifest
 34 | *.spec
 35 | 
 36 | # Installer logs
 37 | pip-log.txt
 38 | pip-delete-this-directory.txt
 39 | 
 40 | # Unit test / coverage reports
 41 | htmlcov/
 42 | .tox/
 43 | .coverage
 44 | .coverage.*
 45 | .cache
 46 | nosetests.xml
 47 | coverage.xml
 48 | *.cover
 49 | .hypothesis/
 50 | .pytest_cache/
 51 | 
 52 | # Translations
 53 | *.mo
 54 | *.pot
 55 | 
 56 | # Django stuff:
 57 | *.log
 58 | local_settings.py
 59 | db.sqlite3
 60 | 
 61 | # Flask stuff:
 62 | instance/
 63 | .webassets-cache
 64 | 
 65 | # Scrapy stuff:
 66 | .scrapy
 67 | 
 68 | # Sphinx documentation
 69 | docs/_build/
 70 | 
 71 | # PyBuilder
 72 | target/
 73 | 
 74 | # Jupyter Notebook
 75 | .ipynb_checkpoints
 76 | 
 77 | # pyenv
 78 | .python-version
 79 | 
 80 | # celery beat schedule file
 81 | celerybeat-schedule
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 83 | # SageMath parsed files
 84 | *.sage.py
 85 | 
 86 | # Environments
 87 | .env
 88 | .venv
 89 | env/
 90 | venv/
 91 | ENV/
 92 | env.bak/
 93 | venv.bak/
 94 | 
 95 | # Spyder project settings
 96 | .spyderproject
 97 | .spyproject
 98 | 
 99 | # Rope project settings
100 | .ropeproject
101 | 
102 | # mkdocs documentation
103 | /site
104 | 
105 | # mypy
106 | .mypy_cache/
107 | 


--------------------------------------------------------------------------------
/3. Sentiment Analysis.ipynb:
--------------------------------------------------------------------------------
   1 | {
   2 |  "cells": [
   3 |   {
   4 |    "cell_type": "markdown",
   5 |    "metadata": {},
   6 |    "source": [
   7 |     "<div style=\"width: 100%; overflow: hidden;\">\n",
   8 |     "    <div style=\"width: 150px; float: left;\"> <img src=\"data/D4Sci_logo_ball.png\" alt=\"Data For Science, Inc\" align=\"left\" border=\"0\"> </div>\n",
   9 |     "    <div style=\"float: left; margin-left: 10px;\"> \n",
  10 |     "        <h1>Natural Language Processing For Everyone</h1>\n",
  11 |     "        <h1>Sentiment Analysis</h1>\n",
  12 |     "        <p>Bruno Gonçalves<br/>\n",
  13 |     "        <a href=\"http://www.data4sci.com/\">www.data4sci.com</a><br/>\n",
  14 |     "        @bgoncalves, @data4sci</p></div>\n",
  15 |     "</div>"
  16 |    ]
  17 |   },
  18 |   {
  19 |    "cell_type": "code",
  20 |    "execution_count": 1,
  21 |    "metadata": {},
  22 |    "outputs": [],
  23 |    "source": [
  24 |     "import string\n",
  25 |     "import gzip\n",
  26 |     "from collections import Counter\n",
  27 |     "\n",
  28 |     "import numpy as np\n",
  29 |     "import pandas as pd\n",
  30 |     "\n",
  31 |     "import matplotlib\n",
  32 |     "import matplotlib.pyplot as plt\n",
  33 |     "import matplotlib.cm as cm\n",
  34 |     "\n",
  35 |     "import watermark\n",
  36 |     "\n",
  37 |     "%matplotlib inline\n",
  38 |     "%load_ext watermark"
  39 |    ]
  40 |   },
  41 |   {
  42 |    "cell_type": "markdown",
  43 |    "metadata": {},
  44 |    "source": [
  45 |     "List out the versions of all loaded libraries"
  46 |    ]
  47 |   },
  48 |   {
  49 |    "cell_type": "code",
  50 |    "execution_count": 2,
  51 |    "metadata": {},
  52 |    "outputs": [
  53 |     {
  54 |      "name": "stdout",
  55 |      "output_type": "stream",
  56 |      "text": [
  57 |       "Python implementation: CPython\n",
  58 |       "Python version       : 3.11.7\n",
  59 |       "IPython version      : 8.20.0\n",
  60 |       "\n",
  61 |       "Compiler    : Clang 14.0.6 \n",
  62 |       "OS          : Darwin\n",
  63 |       "Release     : 23.4.0\n",
  64 |       "Machine     : arm64\n",
  65 |       "Processor   : arm\n",
  66 |       "CPU cores   : 16\n",
  67 |       "Architecture: 64bit\n",
  68 |       "\n",
  69 |       "Git hash: ed7010f27131287f28d990d9846e4ce6cd87e34d\n",
  70 |       "\n",
  71 |       "watermark : 2.4.3\n",
  72 |       "numpy     : 1.26.4\n",
  73 |       "pandas    : 2.1.4\n",
  74 |       "matplotlib: 3.8.0\n",
  75 |       "\n"
  76 |      ]
  77 |     }
  78 |    ],
  79 |    "source": [
  80 |     "%watermark -n -v -m -g -iv"
  81 |    ]
  82 |   },
  83 |   {
  84 |    "cell_type": "markdown",
  85 |    "metadata": {},
  86 |    "source": [
  87 |     "Set the default style"
  88 |    ]
  89 |   },
  90 |   {
  91 |    "cell_type": "code",
  92 |    "execution_count": 3,
  93 |    "metadata": {},
  94 |    "outputs": [],
  95 |    "source": [
  96 |     "plt.style.use('d4sci.mplstyle')"
  97 |    ]
  98 |   },
  99 |   {
 100 |    "cell_type": "markdown",
 101 |    "metadata": {},
 102 |    "source": [
 103 |     "## Word counting"
 104 |    ]
 105 |   },
 106 |   {
 107 |    "cell_type": "markdown",
 108 |    "metadata": {},
 109 |    "source": [
 110 |     "We start by taking the simplest approach and simply counting positive and negative words. We'll use Hu and Liu's Lexicon from their 2004 KDD paper: https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html"
 111 |    ]
 112 |   },
 113 |   {
 114 |    "cell_type": "code",
 115 |    "execution_count": 4,
 116 |    "metadata": {},
 117 |    "outputs": [],
 118 |    "source": [
 119 |     "pos = np.loadtxt('data/positive-words.txt', dtype='str', comments=';')\n",
 120 |     "neg = np.loadtxt('data/negative-words.txt', dtype='str', comments=';')"
 121 |    ]
 122 |   },
 123 |   {
 124 |    "cell_type": "code",
 125 |    "execution_count": 5,
 126 |    "metadata": {},
 127 |    "outputs": [
 128 |     {
 129 |      "data": {
 130 |       "text/plain": [
 131 |        "array(['a+', 'abound', 'abounds', ..., 'zenith', 'zest', 'zippy'],\n",
 132 |        "      dtype='<U20')"
 133 |       ]
 134 |      },
 135 |      "execution_count": 5,
 136 |      "metadata": {},
 137 |      "output_type": "execute_result"
 138 |     }
 139 |    ],
 140 |    "source": [
 141 |     "pos"
 142 |    ]
 143 |   },
 144 |   {
 145 |    "cell_type": "code",
 146 |    "execution_count": 6,
 147 |    "metadata": {},
 148 |    "outputs": [
 149 |     {
 150 |      "data": {
 151 |       "text/plain": [
 152 |        "array(['2-faced', '2-faces', 'abnormal', ..., 'zealous', 'zealously',\n",
 153 |        "       'zombie'], dtype='<U24')"
 154 |       ]
 155 |      },
 156 |      "execution_count": 6,
 157 |      "metadata": {},
 158 |      "output_type": "execute_result"
 159 |     }
 160 |    ],
 161 |    "source": [
 162 |     "neg"
 163 |    ]
 164 |   },
 165 |   {
 166 |    "cell_type": "markdown",
 167 |    "metadata": {},
 168 |    "source": [
 169 |     "Create a dictionary and assign the valence to each positive and negative word"
 170 |    ]
 171 |   },
 172 |   {
 173 |    "cell_type": "code",
 174 |    "execution_count": 7,
 175 |    "metadata": {},
 176 |    "outputs": [],
 177 |    "source": [
 178 |     "valence = {}\n",
 179 |     "\n",
 180 |     "for word in pos:\n",
 181 |     "    valence[word.lower()] = +1\n",
 182 |     "    \n",
 183 |     "for word in neg:\n",
 184 |     "    valence[word.lower()] = -1"
 185 |    ]
 186 |   },
 187 |   {
 188 |    "cell_type": "markdown",
 189 |    "metadata": {},
 190 |    "source": [
 191 |     "Here's the simple word extraction function we defined in Lesson I"
 192 |    ]
 193 |   },
 194 |   {
 195 |    "cell_type": "code",
 196 |    "execution_count": 8,
 197 |    "metadata": {},
 198 |    "outputs": [],
 199 |    "source": [
 200 |     "def extract_words(text):\n",
 201 |     "    temp = text.split() # Split the text on whitespace\n",
 202 |     "    text_words = []\n",
 203 |     "\n",
 204 |     "    for word in temp:\n",
 205 |     "        # Remove any punctuation characters present in the beginning of the word\n",
 206 |     "        while word[0] in string.punctuation:\n",
 207 |     "            word = word[1:]\n",
 208 |     "\n",
 209 |     "        # Remove any punctuation characters present in the end of the word\n",
 210 |     "        while word[-1] in string.punctuation:\n",
 211 |     "            word = word[:-1]\n",
 212 |     "\n",
 213 |     "        # Append this word into our list of words.\n",
 214 |     "        text_words.append(word.lower())\n",
 215 |     "        \n",
 216 |     "    return text_words"
 217 |    ]
 218 |   },
 219 |   {
 220 |    "cell_type": "markdown",
 221 |    "metadata": {},
 222 |    "source": [
 223 |     "That now we can use to define a sentiment measuring function that returns the valence of a sentence or piece of text. Notice that we use the valence directly from the dictionary instead of treating positive and negative words separatly. This will prove useful later on ;)\n",
 224 |     "\n",
 225 |     "\n",
 226 |     "$$ sentiment=\\frac{P-N}{P+N}$$"
 227 |    ]
 228 |   },
 229 |   {
 230 |    "cell_type": "code",
 231 |    "execution_count": 9,
 232 |    "metadata": {},
 233 |    "outputs": [],
 234 |    "source": [
 235 |     "def sentiment(text, valence):\n",
 236 |     "    words = extract_words(text.lower())\n",
 237 |     "    \n",
 238 |     "    word_count = 0\n",
 239 |     "    score = 0\n",
 240 |     "    \n",
 241 |     "    for word in words:\n",
 242 |     "        if word in valence:\n",
 243 |     "            score += valence[word]\n",
 244 |     "            word_count += 1\n",
 245 |     "    \n",
 246 |     "    return score/word_count"
 247 |    ]
 248 |   },
 249 |   {
 250 |    "cell_type": "markdown",
 251 |    "metadata": {},
 252 |    "source": [
 253 |     "Now let's test our simple code with some simple examples"
 254 |    ]
 255 |   },
 256 |   {
 257 |    "cell_type": "code",
 258 |    "execution_count": 10,
 259 |    "metadata": {},
 260 |    "outputs": [
 261 |     {
 262 |      "name": "stdout",
 263 |      "output_type": "stream",
 264 |      "text": [
 265 |       "I'm very happy : 1.0\n",
 266 |       "The product is pretty annoying, and I hate it : -0.3333333333333333\n",
 267 |       "I'm sad : -1.0\n"
 268 |      ]
 269 |     }
 270 |    ],
 271 |    "source": [
 272 |     "texts = [\"I'm very happy\",\n",
 273 |     "         \"The product is pretty annoying, and I hate it\",\n",
 274 |     "         \"I'm sad\",\n",
 275 |     "        ]\n",
 276 |     "\n",
 277 |     "for text in texts:\n",
 278 |     "    print(text, ':', sentiment(text, valence))"
 279 |    ]
 280 |   },
 281 |   {
 282 |    "cell_type": "markdown",
 283 |    "metadata": {},
 284 |    "source": [
 285 |     "This is a bit surprising. One might expect the second sentence to be negative, after all \"pretty annoying\" and \"hate\" sound pretty negative. However, since each word in taken by itself, regardless of context we end up with:"
 286 |    ]
 287 |   },
 288 |   {
 289 |    "cell_type": "code",
 290 |    "execution_count": 11,
 291 |    "metadata": {},
 292 |    "outputs": [
 293 |     {
 294 |      "name": "stdout",
 295 |      "output_type": "stream",
 296 |      "text": [
 297 |       "pretty 1\n",
 298 |       "annoying -1\n",
 299 |       "hate -1\n"
 300 |      ]
 301 |     }
 302 |    ],
 303 |    "source": [
 304 |     "words = extract_words(texts[1].lower())\n",
 305 |     "\n",
 306 |     "for word in words:\n",
 307 |     "    if word in valence:\n",
 308 |     "        print(word, valence[word])"
 309 |    ]
 310 |   },
 311 |   {
 312 |    "cell_type": "markdown",
 313 |    "metadata": {},
 314 |    "source": [
 315 |     "We'll see in a bit how to handle cases like this, but the solution requires two important changes to our current approach: modifier words and real valued weights"
 316 |    ]
 317 |   },
 318 |   {
 319 |    "cell_type": "markdown",
 320 |    "metadata": {},
 321 |    "source": [
 322 |     "## Modifiers"
 323 |    ]
 324 |   },
 325 |   {
 326 |    "cell_type": "markdown",
 327 |    "metadata": {},
 328 |    "source": [
 329 |     "The first step is to define a dictionary of modifiers"
 330 |    ]
 331 |   },
 332 |   {
 333 |    "cell_type": "code",
 334 |    "execution_count": 12,
 335 |    "metadata": {},
 336 |    "outputs": [],
 337 |    "source": [
 338 |     "modifiers = {\n",
 339 |     "    \"very\": 1.5,\n",
 340 |     "    \"much\": 1.3,\n",
 341 |     "    \"not\": -1,\n",
 342 |     "    \"pretty\": 1.5,\n",
 343 |     "    \"somewhat\": 1.2\n",
 344 |     "}"
 345 |    ]
 346 |   },
 347 |   {
 348 |    "cell_type": "markdown",
 349 |    "metadata": {},
 350 |    "source": [
 351 |     "And to change our sentiment measuring function to take the modifiers into account."
 352 |    ]
 353 |   },
 354 |   {
 355 |    "cell_type": "code",
 356 |    "execution_count": 13,
 357 |    "metadata": {
 358 |     "code_folding": []
 359 |    },
 360 |    "outputs": [],
 361 |    "source": [
 362 |     "def sentiment_modified(text, valence, modifiers, verbose=False):\n",
 363 |     "    words = extract_words(text.lower())\n",
 364 |     "    \n",
 365 |     "    ngrams = [[]]\n",
 366 |     "    \n",
 367 |     "    # generate ngrams\n",
 368 |     "    for i in range(len(words)):\n",
 369 |     "        word = words[i]\n",
 370 |     "        \n",
 371 |     "        if word in modifiers:\n",
 372 |     "            ngrams[-1].append(word)\n",
 373 |     "            continue\n",
 374 |     "\n",
 375 |     "        if word in valence:\n",
 376 |     "            ngrams[-1].append(word)\n",
 377 |     "        else:\n",
 378 |     "            if len(ngrams[-1]) > 0:\n",
 379 |     "                ngrams.append([])\n",
 380 |     "\n",
 381 |     "    score = 0\n",
 382 |     "    \n",
 383 |     "    # Remove the trailing empty ngram if necessary\n",
 384 |     "    if len(ngrams[-1]) == 0:\n",
 385 |     "        ngrams = ngrams[:-1]\n",
 386 |     "\n",
 387 |     "    for ngram in ngrams:\n",
 388 |     "        value = 1\n",
 389 |     "\n",
 390 |     "        for word in ngram:\n",
 391 |     "            if word in modifiers:\n",
 392 |     "                value *= modifiers[word]\n",
 393 |     "            elif word in valence:\n",
 394 |     "                value *= valence[word]\n",
 395 |     "\n",
 396 |     "        if verbose:\n",
 397 |     "            print(ngram, value)\n",
 398 |     "\n",
 399 |     "        score += value\n",
 400 |     "\n",
 401 |     "    return score/len(ngrams)"
 402 |    ]
 403 |   },
 404 |   {
 405 |    "cell_type": "markdown",
 406 |    "metadata": {},
 407 |    "source": [
 408 |     "This implementation is still relatively simple, but, as you can see, the results are already better."
 409 |    ]
 410 |   },
 411 |   {
 412 |    "cell_type": "code",
 413 |    "execution_count": 14,
 414 |    "metadata": {},
 415 |    "outputs": [
 416 |     {
 417 |      "name": "stdout",
 418 |      "output_type": "stream",
 419 |      "text": [
 420 |       "The product is pretty annoying, and I hate it\n"
 421 |      ]
 422 |     }
 423 |    ],
 424 |    "source": [
 425 |     "print(texts[1])"
 426 |    ]
 427 |   },
 428 |   {
 429 |    "cell_type": "code",
 430 |    "execution_count": 15,
 431 |    "metadata": {},
 432 |    "outputs": [
 433 |     {
 434 |      "name": "stdout",
 435 |      "output_type": "stream",
 436 |      "text": [
 437 |       "['pretty', 'annoying'] -1.5\n",
 438 |       "['hate'] -1\n"
 439 |      ]
 440 |     },
 441 |     {
 442 |      "data": {
 443 |       "text/plain": [
 444 |        "-1.25"
 445 |       ]
 446 |      },
 447 |      "execution_count": 15,
 448 |      "metadata": {},
 449 |      "output_type": "execute_result"
 450 |     }
 451 |    ],
 452 |    "source": [
 453 |     "sentiment_modified(texts[1], valence, modifiers, verbose=True)"
 454 |    ]
 455 |   },
 456 |   {
 457 |    "cell_type": "markdown",
 458 |    "metadata": {},
 459 |    "source": [
 460 |     "A more complete implementation would be more careful in handling the modifiers and would build larger ngrams so that cases like this one would also work:"
 461 |    ]
 462 |   },
 463 |   {
 464 |    "cell_type": "code",
 465 |    "execution_count": 16,
 466 |    "metadata": {},
 467 |    "outputs": [
 468 |     {
 469 |      "name": "stdout",
 470 |      "output_type": "stream",
 471 |      "text": [
 472 |       "['not', 'very', 'good'] -1.5\n"
 473 |      ]
 474 |     },
 475 |     {
 476 |      "data": {
 477 |       "text/plain": [
 478 |        "-1.5"
 479 |       ]
 480 |      },
 481 |      "execution_count": 16,
 482 |      "metadata": {},
 483 |      "output_type": "execute_result"
 484 |     }
 485 |    ],
 486 |    "source": [
 487 |     "sentiment_modified(\"It was not very good\", valence, modifiers, True)"
 488 |    ]
 489 |   },
 490 |   {
 491 |    "cell_type": "markdown",
 492 |    "metadata": {},
 493 |    "source": [
 494 |     "And even more complex (and unrealistic) examples work fine"
 495 |    ]
 496 |   },
 497 |   {
 498 |    "cell_type": "code",
 499 |    "execution_count": 17,
 500 |    "metadata": {},
 501 |    "outputs": [
 502 |     {
 503 |      "name": "stdout",
 504 |      "output_type": "stream",
 505 |      "text": [
 506 |       "['not', 'not', 'very', 'very', 'good'] 2.25\n"
 507 |      ]
 508 |     },
 509 |     {
 510 |      "data": {
 511 |       "text/plain": [
 512 |        "2.25"
 513 |       ]
 514 |      },
 515 |      "execution_count": 17,
 516 |      "metadata": {},
 517 |      "output_type": "execute_result"
 518 |     }
 519 |    ],
 520 |    "source": [
 521 |     "sentiment_modified(\"It was not not very very good\", valence, modifiers, True)"
 522 |    ]
 523 |   },
 524 |   {
 525 |    "cell_type": "markdown",
 526 |    "metadata": {},
 527 |    "source": [
 528 |     "## Continuous weights"
 529 |    ]
 530 |   },
 531 |   {
 532 |    "cell_type": "markdown",
 533 |    "metadata": {},
 534 |    "source": [
 535 |     "VADER is a state of the art sentiment analysis tool. Here we will use their excelent and well documented [lexicon](https://github.com/cjhutto/vaderSentiment) to explore non binary weights. Their approach is significantly more advanced than what we present here, but some of the fundamental ideas are the same"
 536 |    ]
 537 |   },
 538 |   {
 539 |    "cell_type": "code",
 540 |    "execution_count": 18,
 541 |    "metadata": {},
 542 |    "outputs": [],
 543 |    "source": [
 544 |     "vader = pd.read_csv(\"data/vader_lexicon.txt\", sep='\\t', header=None)"
 545 |    ]
 546 |   },
 547 |   {
 548 |    "cell_type": "markdown",
 549 |    "metadata": {},
 550 |    "source": [
 551 |     "The vader lexicon includes a lot of interesting information:"
 552 |    ]
 553 |   },
 554 |   {
 555 |    "cell_type": "code",
 556 |    "execution_count": 19,
 557 |    "metadata": {},
 558 |    "outputs": [
 559 |     {
 560 |      "data": {
 561 |       "text/html": [
 562 |        "<div>\n",
 563 |        "<style scoped>\n",
 564 |        "    .dataframe tbody tr th:only-of-type {\n",
 565 |        "        vertical-align: middle;\n",
 566 |        "    }\n",
 567 |        "\n",
 568 |        "    .dataframe tbody tr th {\n",
 569 |        "        vertical-align: top;\n",
 570 |        "    }\n",
 571 |        "\n",
 572 |        "    .dataframe thead th {\n",
 573 |        "        text-align: right;\n",
 574 |        "    }\n",
 575 |        "</style>\n",
 576 |        "<table border=\"1\" class=\"dataframe\">\n",
 577 |        "  <thead>\n",
 578 |        "    <tr style=\"text-align: right;\">\n",
 579 |        "      <th></th>\n",
 580 |        "      <th>0</th>\n",
 581 |        "      <th>1</th>\n",
 582 |        "      <th>2</th>\n",
 583 |        "      <th>3</th>\n",
 584 |        "    </tr>\n",
 585 |        "  </thead>\n",
 586 |        "  <tbody>\n",
 587 |        "    <tr>\n",
 588 |        "      <th>0</th>\n",
 589 |        "      <td>$:</td>\n",
 590 |        "      <td>-1.5</td>\n",
 591 |        "      <td>0.80623</td>\n",
 592 |        "      <td>[-1, -1, -1, -1, -3, -1, -3, -1, -2, -1]</td>\n",
 593 |        "    </tr>\n",
 594 |        "    <tr>\n",
 595 |        "      <th>1</th>\n",
 596 |        "      <td>%)</td>\n",
 597 |        "      <td>-0.4</td>\n",
 598 |        "      <td>1.01980</td>\n",
 599 |        "      <td>[-1, 0, -1, 0, 0, -2, -1, 2, -1, 0]</td>\n",
 600 |        "    </tr>\n",
 601 |        "    <tr>\n",
 602 |        "      <th>2</th>\n",
 603 |        "      <td>%-)</td>\n",
 604 |        "      <td>-1.5</td>\n",
 605 |        "      <td>1.43178</td>\n",
 606 |        "      <td>[-2, 0, -2, -2, -1, 2, -2, -3, -2, -3]</td>\n",
 607 |        "    </tr>\n",
 608 |        "    <tr>\n",
 609 |        "      <th>3</th>\n",
 610 |        "      <td>&amp;-:</td>\n",
 611 |        "      <td>-0.4</td>\n",
 612 |        "      <td>1.42829</td>\n",
 613 |        "      <td>[-3, -1, 0, 0, -1, -1, -1, 2, -1, 2]</td>\n",
 614 |        "    </tr>\n",
 615 |        "    <tr>\n",
 616 |        "      <th>4</th>\n",
 617 |        "      <td>&amp;:</td>\n",
 618 |        "      <td>-0.7</td>\n",
 619 |        "      <td>0.64031</td>\n",
 620 |        "      <td>[0, -1, -1, -1, 1, -1, -1, -1, -1, -1]</td>\n",
 621 |        "    </tr>\n",
 622 |        "  </tbody>\n",
 623 |        "</table>\n",
 624 |        "</div>"
 625 |       ],
 626 |       "text/plain": [
 627 |        "     0    1        2                                         3\n",
 628 |        "0   $: -1.5  0.80623  [-1, -1, -1, -1, -3, -1, -3, -1, -2, -1]\n",
 629 |        "1   %) -0.4  1.01980       [-1, 0, -1, 0, 0, -2, -1, 2, -1, 0]\n",
 630 |        "2  %-) -1.5  1.43178    [-2, 0, -2, -2, -1, 2, -2, -3, -2, -3]\n",
 631 |        "3  &-: -0.4  1.42829      [-3, -1, 0, 0, -1, -1, -1, 2, -1, 2]\n",
 632 |        "4   &: -0.7  0.64031    [0, -1, -1, -1, 1, -1, -1, -1, -1, -1]"
 633 |       ]
 634 |      },
 635 |      "execution_count": 19,
 636 |      "metadata": {},
 637 |      "output_type": "execute_result"
 638 |     }
 639 |    ],
 640 |    "source": [
 641 |     "vader.head()"
 642 |    ]
 643 |   },
 644 |   {
 645 |    "cell_type": "code",
 646 |    "execution_count": 20,
 647 |    "metadata": {},
 648 |    "outputs": [
 649 |     {
 650 |      "data": {
 651 |       "text/html": [
 652 |        "<div>\n",
 653 |        "<style scoped>\n",
 654 |        "    .dataframe tbody tr th:only-of-type {\n",
 655 |        "        vertical-align: middle;\n",
 656 |        "    }\n",
 657 |        "\n",
 658 |        "    .dataframe tbody tr th {\n",
 659 |        "        vertical-align: top;\n",
 660 |        "    }\n",
 661 |        "\n",
 662 |        "    .dataframe thead th {\n",
 663 |        "        text-align: right;\n",
 664 |        "    }\n",
 665 |        "</style>\n",
 666 |        "<table border=\"1\" class=\"dataframe\">\n",
 667 |        "  <thead>\n",
 668 |        "    <tr style=\"text-align: right;\">\n",
 669 |        "      <th></th>\n",
 670 |        "      <th>0</th>\n",
 671 |        "      <th>1</th>\n",
 672 |        "      <th>2</th>\n",
 673 |        "      <th>3</th>\n",
 674 |        "    </tr>\n",
 675 |        "  </thead>\n",
 676 |        "  <tbody>\n",
 677 |        "    <tr>\n",
 678 |        "      <th>7512</th>\n",
 679 |        "      <td>}:</td>\n",
 680 |        "      <td>-2.1</td>\n",
 681 |        "      <td>0.83066</td>\n",
 682 |        "      <td>[-1, -1, -3, -2, -3, -2, -2, -1, -3, -3]</td>\n",
 683 |        "    </tr>\n",
 684 |        "    <tr>\n",
 685 |        "      <th>7513</th>\n",
 686 |        "      <td>}:(</td>\n",
 687 |        "      <td>-2.0</td>\n",
 688 |        "      <td>0.63246</td>\n",
 689 |        "      <td>[-3, -1, -2, -1, -3, -2, -2, -2, -2, -2]</td>\n",
 690 |        "    </tr>\n",
 691 |        "    <tr>\n",
 692 |        "      <th>7514</th>\n",
 693 |        "      <td>}:)</td>\n",
 694 |        "      <td>0.4</td>\n",
 695 |        "      <td>1.42829</td>\n",
 696 |        "      <td>[1, 1, -2, 1, 2, -2, 1, -1, 2, 1]</td>\n",
 697 |        "    </tr>\n",
 698 |        "    <tr>\n",
 699 |        "      <th>7515</th>\n",
 700 |        "      <td>}:-(</td>\n",
 701 |        "      <td>-2.1</td>\n",
 702 |        "      <td>0.70000</td>\n",
 703 |        "      <td>[-2, -1, -2, -2, -2, -4, -2, -2, -2, -2]</td>\n",
 704 |        "    </tr>\n",
 705 |        "    <tr>\n",
 706 |        "      <th>7516</th>\n",
 707 |        "      <td>}:-)</td>\n",
 708 |        "      <td>0.3</td>\n",
 709 |        "      <td>1.61555</td>\n",
 710 |        "      <td>[1, 1, -2, 1, -1, -3, 2, 2, 1, 1]</td>\n",
 711 |        "    </tr>\n",
 712 |        "  </tbody>\n",
 713 |        "</table>\n",
 714 |        "</div>"
 715 |       ],
 716 |       "text/plain": [
 717 |        "         0    1        2                                         3\n",
 718 |        "7512    }: -2.1  0.83066  [-1, -1, -3, -2, -3, -2, -2, -1, -3, -3]\n",
 719 |        "7513   }:( -2.0  0.63246  [-3, -1, -2, -1, -3, -2, -2, -2, -2, -2]\n",
 720 |        "7514   }:)  0.4  1.42829         [1, 1, -2, 1, 2, -2, 1, -1, 2, 1]\n",
 721 |        "7515  }:-( -2.1  0.70000  [-2, -1, -2, -2, -2, -4, -2, -2, -2, -2]\n",
 722 |        "7516  }:-)  0.3  1.61555         [1, 1, -2, 1, -1, -3, 2, 2, 1, 1]"
 723 |       ]
 724 |      },
 725 |      "execution_count": 20,
 726 |      "metadata": {},
 727 |      "output_type": "execute_result"
 728 |     }
 729 |    ],
 730 |    "source": [
 731 |     "vader.tail()"
 732 |    ]
 733 |   },
 734 |   {
 735 |    "cell_type": "markdown",
 736 |    "metadata": {},
 737 |    "source": [
 738 |     "Similies are also included and, in addition to the average sentiment of each word (in column 1) and it's standard deviation (in column 2) it provides the raw human generated scores in column 3. So that we may easily check (and possibly modify) their weights. To extract the raw scores for the word \"love\" we could simply do:"
 739 |    ]
 740 |   },
 741 |   {
 742 |    "cell_type": "code",
 743 |    "execution_count": 21,
 744 |    "metadata": {},
 745 |    "outputs": [
 746 |     {
 747 |      "name": "stdout",
 748 |      "output_type": "stream",
 749 |      "text": [
 750 |       "(7517, 4)\n"
 751 |      ]
 752 |     }
 753 |    ],
 754 |    "source": [
 755 |     "print(vader.shape)"
 756 |    ]
 757 |   },
 758 |   {
 759 |    "cell_type": "code",
 760 |    "execution_count": 22,
 761 |    "metadata": {},
 762 |    "outputs": [
 763 |     {
 764 |      "name": "stdout",
 765 |      "output_type": "stream",
 766 |      "text": [
 767 |       "0                              love\n",
 768 |       "1                               3.2\n",
 769 |       "2                               0.4\n",
 770 |       "3    [3, 3, 3, 3, 3, 3, 3, 4, 4, 3]\n",
 771 |       "Name: 4446, dtype: object\n"
 772 |      ]
 773 |     }
 774 |    ],
 775 |    "source": [
 776 |     "print(vader.iloc[4446])"
 777 |    ]
 778 |   },
 779 |   {
 780 |    "cell_type": "code",
 781 |    "execution_count": 23,
 782 |    "metadata": {},
 783 |    "outputs": [
 784 |     {
 785 |      "name": "stdout",
 786 |      "output_type": "stream",
 787 |      "text": [
 788 |       "[3, 3, 3, 3, 3, 3, 3, 4, 4, 3]\n"
 789 |      ]
 790 |     }
 791 |    ],
 792 |    "source": [
 793 |     "scores = eval(vader.iloc[4446][3])\n",
 794 |     "print(scores)"
 795 |    ]
 796 |   },
 797 |   {
 798 |    "cell_type": "code",
 799 |    "execution_count": 24,
 800 |    "metadata": {},
 801 |    "outputs": [
 802 |     {
 803 |      "data": {
 804 |       "text/plain": [
 805 |        "4"
 806 |       ]
 807 |      },
 808 |      "execution_count": 24,
 809 |      "metadata": {},
 810 |      "output_type": "execute_result"
 811 |     }
 812 |    ],
 813 |    "source": [
 814 |     "scores[8]"
 815 |    ]
 816 |   },
 817 |   {
 818 |    "cell_type": "markdown",
 819 |    "metadata": {},
 820 |    "source": [
 821 |     "And we can see that 8/10 people thought that the word love should receive a score of 3 and two others a score of 4. This gives us insight into how uniform the scores are.  If for some reason, we thought that there was some problem with the 2 values of 4 or perhaps just not appropriate to our purposes we might discard them and recalculate the valence of the word. \n",
 822 |     "\n",
 823 |     "One justification for this might be the fact that the scores for the closely related word, \"loved\", are significantly different with a wider range of variation in the human scores"
 824 |    ]
 825 |   },
 826 |   {
 827 |    "cell_type": "code",
 828 |    "execution_count": 25,
 829 |    "metadata": {},
 830 |    "outputs": [
 831 |     {
 832 |      "data": {
 833 |       "text/plain": [
 834 |        "0                             loved\n",
 835 |        "1                               2.9\n",
 836 |        "2                               0.7\n",
 837 |        "3    [3, 3, 4, 2, 2, 4, 3, 2, 3, 3]\n",
 838 |        "Name: 4447, dtype: object"
 839 |       ]
 840 |      },
 841 |      "execution_count": 25,
 842 |      "metadata": {},
 843 |      "output_type": "execute_result"
 844 |     }
 845 |    ],
 846 |    "source": [
 847 |     "vader.iloc[4447]"
 848 |    ]
 849 |   },
 850 |   {
 851 |    "cell_type": "markdown",
 852 |    "metadata": {},
 853 |    "source": [
 854 |     "Now we convert this dataset into a dictionary similar to the one we used above"
 855 |    ]
 856 |   },
 857 |   {
 858 |    "cell_type": "code",
 859 |    "execution_count": 26,
 860 |    "metadata": {},
 861 |    "outputs": [],
 862 |    "source": [
 863 |     "valence_vader = dict(vader[[0, 1]].values)"
 864 |    ]
 865 |   },
 866 |   {
 867 |    "cell_type": "code",
 868 |    "execution_count": 27,
 869 |    "metadata": {},
 870 |    "outputs": [
 871 |     {
 872 |      "data": {
 873 |       "text/plain": [
 874 |        "3.2"
 875 |       ]
 876 |      },
 877 |      "execution_count": 27,
 878 |      "metadata": {},
 879 |      "output_type": "execute_result"
 880 |     }
 881 |    ],
 882 |    "source": [
 883 |     "valence_vader['love']"
 884 |    ]
 885 |   },
 886 |   {
 887 |    "cell_type": "markdown",
 888 |    "metadata": {},
 889 |    "source": [
 890 |     "To use this new dictionary we just have to modify the arguments to the sentiment_modified function:"
 891 |    ]
 892 |   },
 893 |   {
 894 |    "cell_type": "code",
 895 |    "execution_count": 28,
 896 |    "metadata": {},
 897 |    "outputs": [
 898 |     {
 899 |      "name": "stdout",
 900 |      "output_type": "stream",
 901 |      "text": [
 902 |       "['not', 'not', 'very', 'very', 'good'] 4.2749999999999995\n"
 903 |      ]
 904 |     },
 905 |     {
 906 |      "data": {
 907 |       "text/plain": [
 908 |        "4.2749999999999995"
 909 |       ]
 910 |      },
 911 |      "execution_count": 28,
 912 |      "metadata": {},
 913 |      "output_type": "execute_result"
 914 |     }
 915 |    ],
 916 |    "source": [
 917 |     "sentiment_modified(\"It was not not very very good\", valence_vader, modifiers, verbose=True)"
 918 |    ]
 919 |   },
 920 |   {
 921 |    "cell_type": "markdown",
 922 |    "metadata": {},
 923 |    "source": [
 924 |     "One important detail to keep in mind is that scores obtained through different methods are not comparable. In this example, the score of the sentence \"It was not not very very good\" went from 2.25 to 4.27 when we switched dictionaries. This is due not only to different levels of coverage in differnet dictionaries but also to differnet choices in the possible ranges of values."
 925 |    ]
 926 |   },
 927 |   {
 928 |    "cell_type": "code",
 929 |    "execution_count": 29,
 930 |    "metadata": {},
 931 |    "outputs": [
 932 |     {
 933 |      "name": "stdout",
 934 |      "output_type": "stream",
 935 |      "text": [
 936 |       "I'm very happy : 4.050000000000001\n",
 937 |       "The product is pretty annoying, and I hate it : -2.625\n",
 938 |       "I'm sad : -2.1\n"
 939 |      ]
 940 |     }
 941 |    ],
 942 |    "source": [
 943 |     "texts = [\"I'm very happy\",\n",
 944 |     "         \"The product is pretty annoying, and I hate it\",\n",
 945 |     "         \"I'm sad\",\n",
 946 |     "        ]\n",
 947 |     "\n",
 948 |     "for text in texts:\n",
 949 |     "    print(text, ':', sentiment_modified(text, valence_vader, modifiers))"
 950 |    ]
 951 |   },
 952 |   {
 953 |    "cell_type": "markdown",
 954 |    "metadata": {},
 955 |    "source": [
 956 |     "<center>\n",
 957 |     "     <img src=\"data/D4Sci_logo_full.png\" alt=\"Data For Science, Inc\" align=\"center\" border=\"0\" width=300px> \n",
 958 |     "</center>"
 959 |    ]
 960 |   }
 961 |  ],
 962 |  "metadata": {
 963 |   "anaconda-cloud": {},
 964 |   "kernelspec": {
 965 |    "display_name": "Python 3 (ipykernel)",
 966 |    "language": "python",
 967 |    "name": "python3"
 968 |   },
 969 |   "language_info": {
 970 |    "codemirror_mode": {
 971 |     "name": "ipython",
 972 |     "version": 3
 973 |    },
 974 |    "file_extension": ".py",
 975 |    "mimetype": "text/x-python",
 976 |    "name": "python",
 977 |    "nbconvert_exporter": "python",
 978 |    "pygments_lexer": "ipython3",
 979 |    "version": "3.11.7"
 980 |   },
 981 |   "toc": {
 982 |    "base_numbering": 1,
 983 |    "nav_menu": {},
 984 |    "number_sections": true,
 985 |    "sideBar": true,
 986 |    "skip_h1_title": true,
 987 |    "title_cell": "Table of Contents",
 988 |    "title_sidebar": "Contents",
 989 |    "toc_cell": false,
 990 |    "toc_position": {},
 991 |    "toc_section_display": true,
 992 |    "toc_window_display": false
 993 |   },
 994 |   "varInspector": {
 995 |    "cols": {
 996 |     "lenName": 16,
 997 |     "lenType": 16,
 998 |     "lenVar": 40
 999 |    },
1000 |    "kernels_config": {
1001 |     "python": {
1002 |      "delete_cmd_postfix": "",
1003 |      "delete_cmd_prefix": "del ",
1004 |      "library": "var_list.py",
1005 |      "varRefreshCmd": "print(var_dic_list())"
1006 |     },
1007 |     "r": {
1008 |      "delete_cmd_postfix": ") ",
1009 |      "delete_cmd_prefix": "rm(",
1010 |      "library": "var_list.r",
1011 |      "varRefreshCmd": "cat(var_dic_list()) "
1012 |     }
1013 |    },
1014 |    "types_to_exclude": [
1015 |     "module",
1016 |     "function",
1017 |     "builtin_function_or_method",
1018 |     "instance",
1019 |     "_Feature"
1020 |    ],
1021 |    "window_display": false
1022 |   }
1023 |  },
1024 |  "nbformat": 4,
1025 |  "nbformat_minor": 4
1026 | }
1027 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2019 Data For Science
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


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/README.md:
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 1 | ![GitHub](https://img.shields.io/github/license/DataForScience/NLP)
 2 | [![Twitter @data4sci](https://img.shields.io/twitter/follow/data4sci)](https://twitter.com/intent/follow?screen_name=data4sci)
 3 | ![GitHub top language](https://img.shields.io/github/languages/top/DataForScience/NLP)
 4 | ![GitHub repo size](https://img.shields.io/github/repo-size/DataForScience/NLP)
 5 | ![GitHub last commit](https://img.shields.io/github/last-commit/DataForScience/NLP)
 6 | 
 7 | [![Graphs For Science](https://img.shields.io/badge/Graphs_For_Science-Subscribe-blue)](https://graphs4sci.substack.com/)
 8 | [![Sunday Briefing](https://img.shields.io/badge/Sunday_Briefing-Subscribe-blue)](https://data4science.ck.page/a63d4cc8d9)
 9 | 
10 | 
11 | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/DataForScience/NLP/master)
12 | 
13 | # Natural Language Processing For Everyone
14 | 
15 | ### Code and slides to accompany the online series of webinars: https://data4sci.com/nlp by Data For Science.
16 | 
17 | ### Run the code in Binder: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/DataForScience/NLP/master)
18 | 
19 | The rise of online social platforms has resulted in an explosion of written text in the form of blogs, posts, tweets, wiki pages, and more. This new wealth of data provides a unique opportunity to explore natural language in its many forms, both as a way of automatically extracting information from written text and as a way of artificially producing text that looks natural.
20 | 
21 | In this class we introduce viewers to natural language processing from scratch. Each concept is introduced and explained through coding examples using nothing more than just plain Python and numpy. In this way, attendees learn in depth about the underlying concepts and techniques instead of just learning how to use a specific NLP library.
22 | 
23 | ## Schedule
24 | 
25 | ### 1. Text Representation
26 | - Represent words and numbers
27 | - Use One-Hot Encoding
28 | - Implement Bag of Words
29 | - Apply stopwords
30 | - Understand TF/IDF
31 | - Understand Stemming
32 | 
33 | ### 2. Topic Modeling
34 | - Find topics in documents
35 | - Perform Explicit Semantic Analysis
36 | - Understand Document clustering
37 | - Implement Latent Semantic Analysis
38 | - Implement Non-negative Matrix factorization
39 | 
40 | ### 3. Sentiment Analysis
41 | - Quantify words and feelings
42 | - Use Negations and modifiers
43 | - Understand corpus based approaches
44 | 
45 | ### 4. Applications
46 | - Understand Word2vec word embeddings
47 | - Define GloVe
48 | - Apply Language detection
49 | 
50 | Slides: http://data4sci.com/landing/nlp/
51 | 


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/d4sci.mplstyle:
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 1 | # Data For Science style
 2 | # Author: Bruno Goncalves <bgoncalves@data4sci.com>
 3 | # Modified from the matplotlib FiveThirtyEight style by
 4 | # Author: Cameron Davidson-Pilon, replicated styles from FiveThirtyEight.com
 5 | # See https://www.dataorigami.net/blogs/fivethirtyeight-mpl
 6 | 
 7 | lines.linewidth: 4
 8 | lines.solid_capstyle: butt
 9 | 
10 | legend.fancybox: true
11 | 
12 | axes.prop_cycle: cycler('color', ['51a7f9', 'cf51f9', '70bf41', 'f39019', 'f9e351', 'f9517b', '6d904f', '8b8b8b','810f7c']) 
13 | 
14 | axes.labelsize: large
15 | axes.axisbelow: true
16 | axes.grid: true
17 | axes.edgecolor: f0f0f0
18 | axes.linewidth: 3.0
19 | axes.titlesize: x-large
20 | 
21 | patch.edgecolor: f0f0f0
22 | patch.linewidth: 0.5
23 | 
24 | svg.fonttype: path
25 | 
26 | grid.linestyle: -
27 | grid.linewidth: 1.0
28 | 
29 | xtick.major.size: 0
30 | xtick.minor.size: 0
31 | ytick.major.size: 0
32 | ytick.minor.size: 0
33 | 
34 | font.size: 24.0
35 | 
36 | savefig.edgecolor: f0f0f0
37 | savefig.facecolor: f0f0f0
38 | 
39 | figure.subplot.left: 0.08
40 | figure.subplot.right: 0.95
41 | figure.subplot.bottom: 0.07
42 | figure.figsize: 12.8, 8.8
43 | figure.autolayout: True
44 | figure.dpi: 300
45 | 


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/data/negative-words.txt:
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   1 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
   2 | ; 
   3 | ; Opinion Lexicon: Negative
   4 | ;
   5 | ; This file contains a list of NEGATIVE opinion words (or sentiment words).
   6 | ;
   7 | ; This file and the papers can all be downloaded from 
   8 | ;    http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html
   9 | ;
  10 | ; If you use this list, please cite one of the following two papers:
  11 | ;
  12 | ;   Minqing Hu and Bing Liu. "Mining and Summarizing Customer Reviews." 
  13 | ;       Proceedings of the ACM SIGKDD International Conference on Knowledge 
  14 | ;       Discovery and Data Mining (KDD-2004), Aug 22-25, 2004, Seattle, 
  15 | ;       Washington, USA, 
  16 | ;   Bing Liu, Minqing Hu and Junsheng Cheng. "Opinion Observer: Analyzing 
  17 | ;       and Comparing Opinions on the Web." Proceedings of the 14th 
  18 | ;       International World Wide Web conference (WWW-2005), May 10-14, 
  19 | ;       2005, Chiba, Japan.
  20 | ;
  21 | ; Notes: 
  22 | ;    1. The appearance of an opinion word in a sentence does not necessarily  
  23 | ;       mean that the sentence expresses a positive or negative opinion. 
  24 | ;       See the paper below:
  25 | ;
  26 | ;       Bing Liu. "Sentiment Analysis and Subjectivity." An chapter in 
  27 | ;          Handbook of Natural Language Processing, Second Edition, 
  28 | ;          (editors: N. Indurkhya and F. J. Damerau), 2010.
  29 | ;
  30 | ;    2. You will notice many misspelled words in the list. They are not 
  31 | ;       mistakes. They are included as these misspelled words appear 
  32 | ;       frequently in social media content. 
  33 | ;
  34 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
  35 | 
  36 | 2-faced
  37 | 2-faces
  38 | abnormal
  39 | abolish
  40 | abominable
  41 | abominably
  42 | abominate
  43 | abomination
  44 | abort
  45 | aborted
  46 | aborts
  47 | abrade
  48 | abrasive
  49 | abrupt
  50 | abruptly
  51 | abscond
  52 | absence
  53 | absent-minded
  54 | absentee
  55 | absurd
  56 | absurdity
  57 | absurdly
  58 | absurdness
  59 | abuse
  60 | abused
  61 | abuses
  62 | abusive
  63 | abysmal
  64 | abysmally
  65 | abyss
  66 | accidental
  67 | accost
  68 | accursed
  69 | accusation
  70 | accusations
  71 | accuse
  72 | accuses
  73 | accusing
  74 | accusingly
  75 | acerbate
  76 | acerbic
  77 | acerbically
  78 | ache
  79 | ached
  80 | aches
  81 | achey
  82 | aching
  83 | acrid
  84 | acridly
  85 | acridness
  86 | acrimonious
  87 | acrimoniously
  88 | acrimony
  89 | adamant
  90 | adamantly
  91 | addict
  92 | addicted
  93 | addicting
  94 | addicts
  95 | admonish
  96 | admonisher
  97 | admonishingly
  98 | admonishment
  99 | admonition
 100 | adulterate
 101 | adulterated
 102 | adulteration
 103 | adulterier
 104 | adversarial
 105 | adversary
 106 | adverse
 107 | adversity
 108 | afflict
 109 | affliction
 110 | afflictive
 111 | affront
 112 | afraid
 113 | aggravate
 114 | aggravating
 115 | aggravation
 116 | aggression
 117 | aggressive
 118 | aggressiveness
 119 | aggressor
 120 | aggrieve
 121 | aggrieved
 122 | aggrivation
 123 | aghast
 124 | agonies
 125 | agonize
 126 | agonizing
 127 | agonizingly
 128 | agony
 129 | aground
 130 | ail
 131 | ailing
 132 | ailment
 133 | aimless
 134 | alarm
 135 | alarmed
 136 | alarming
 137 | alarmingly
 138 | alienate
 139 | alienated
 140 | alienation
 141 | allegation
 142 | allegations
 143 | allege
 144 | allergic
 145 | allergies
 146 | allergy
 147 | aloof
 148 | altercation
 149 | ambiguity
 150 | ambiguous
 151 | ambivalence
 152 | ambivalent
 153 | ambush
 154 | amiss
 155 | amputate
 156 | anarchism
 157 | anarchist
 158 | anarchistic
 159 | anarchy
 160 | anemic
 161 | anger
 162 | angrily
 163 | angriness
 164 | angry
 165 | anguish
 166 | animosity
 167 | annihilate
 168 | annihilation
 169 | annoy
 170 | annoyance
 171 | annoyances
 172 | annoyed
 173 | annoying
 174 | annoyingly
 175 | annoys
 176 | anomalous
 177 | anomaly
 178 | antagonism
 179 | antagonist
 180 | antagonistic
 181 | antagonize
 182 | anti-
 183 | anti-american
 184 | anti-israeli
 185 | anti-occupation
 186 | anti-proliferation
 187 | anti-semites
 188 | anti-social
 189 | anti-us
 190 | anti-white
 191 | antipathy
 192 | antiquated
 193 | antithetical
 194 | anxieties
 195 | anxiety
 196 | anxious
 197 | anxiously
 198 | anxiousness
 199 | apathetic
 200 | apathetically
 201 | apathy
 202 | apocalypse
 203 | apocalyptic
 204 | apologist
 205 | apologists
 206 | appal
 207 | appall
 208 | appalled
 209 | appalling
 210 | appallingly
 211 | apprehension
 212 | apprehensions
 213 | apprehensive
 214 | apprehensively
 215 | arbitrary
 216 | arcane
 217 | archaic
 218 | arduous
 219 | arduously
 220 | argumentative
 221 | arrogance
 222 | arrogant
 223 | arrogantly
 224 | ashamed
 225 | asinine
 226 | asininely
 227 | asinininity
 228 | askance
 229 | asperse
 230 | aspersion
 231 | aspersions
 232 | assail
 233 | assassin
 234 | assassinate
 235 | assault
 236 | assult
 237 | astray
 238 | asunder
 239 | atrocious
 240 | atrocities
 241 | atrocity
 242 | atrophy
 243 | attack
 244 | attacks
 245 | audacious
 246 | audaciously
 247 | audaciousness
 248 | audacity
 249 | audiciously
 250 | austere
 251 | authoritarian
 252 | autocrat
 253 | autocratic
 254 | avalanche
 255 | avarice
 256 | avaricious
 257 | avariciously
 258 | avenge
 259 | averse
 260 | aversion
 261 | aweful
 262 | awful
 263 | awfully
 264 | awfulness
 265 | awkward
 266 | awkwardness
 267 | ax
 268 | babble
 269 | back-logged
 270 | back-wood
 271 | back-woods
 272 | backache
 273 | backaches
 274 | backaching
 275 | backbite
 276 | backbiting
 277 | backward
 278 | backwardness
 279 | backwood
 280 | backwoods
 281 | bad
 282 | badly
 283 | baffle
 284 | baffled
 285 | bafflement
 286 | baffling
 287 | bait
 288 | balk
 289 | banal
 290 | banalize
 291 | bane
 292 | banish
 293 | banishment
 294 | bankrupt
 295 | barbarian
 296 | barbaric
 297 | barbarically
 298 | barbarity
 299 | barbarous
 300 | barbarously
 301 | barren
 302 | baseless
 303 | bash
 304 | bashed
 305 | bashful
 306 | bashing
 307 | bastard
 308 | bastards
 309 | battered
 310 | battering
 311 | batty
 312 | bearish
 313 | beastly
 314 | bedlam
 315 | bedlamite
 316 | befoul
 317 | beg
 318 | beggar
 319 | beggarly
 320 | begging
 321 | beguile
 322 | belabor
 323 | belated
 324 | beleaguer
 325 | belie
 326 | belittle
 327 | belittled
 328 | belittling
 329 | bellicose
 330 | belligerence
 331 | belligerent
 332 | belligerently
 333 | bemoan
 334 | bemoaning
 335 | bemused
 336 | bent
 337 | berate
 338 | bereave
 339 | bereavement
 340 | bereft
 341 | berserk
 342 | beseech
 343 | beset
 344 | besiege
 345 | besmirch
 346 | bestial
 347 | betray
 348 | betrayal
 349 | betrayals
 350 | betrayer
 351 | betraying
 352 | betrays
 353 | bewail
 354 | beware
 355 | bewilder
 356 | bewildered
 357 | bewildering
 358 | bewilderingly
 359 | bewilderment
 360 | bewitch
 361 | bias
 362 | biased
 363 | biases
 364 | bicker
 365 | bickering
 366 | bid-rigging
 367 | bigotries
 368 | bigotry
 369 | bitch
 370 | bitchy
 371 | biting
 372 | bitingly
 373 | bitter
 374 | bitterly
 375 | bitterness
 376 | bizarre
 377 | blab
 378 | blabber
 379 | blackmail
 380 | blah
 381 | blame
 382 | blameworthy
 383 | bland
 384 | blandish
 385 | blaspheme
 386 | blasphemous
 387 | blasphemy
 388 | blasted
 389 | blatant
 390 | blatantly
 391 | blather
 392 | bleak
 393 | bleakly
 394 | bleakness
 395 | bleed
 396 | bleeding
 397 | bleeds
 398 | blemish
 399 | blind
 400 | blinding
 401 | blindingly
 402 | blindside
 403 | blister
 404 | blistering
 405 | bloated
 406 | blockage
 407 | blockhead
 408 | bloodshed
 409 | bloodthirsty
 410 | bloody
 411 | blotchy
 412 | blow
 413 | blunder
 414 | blundering
 415 | blunders
 416 | blunt
 417 | blur
 418 | bluring
 419 | blurred
 420 | blurring
 421 | blurry
 422 | blurs
 423 | blurt
 424 | boastful
 425 | boggle
 426 | bogus
 427 | boil
 428 | boiling
 429 | boisterous
 430 | bomb
 431 | bombard
 432 | bombardment
 433 | bombastic
 434 | bondage
 435 | bonkers
 436 | bore
 437 | bored
 438 | boredom
 439 | bores
 440 | boring
 441 | botch
 442 | bother
 443 | bothered
 444 | bothering
 445 | bothers
 446 | bothersome
 447 | bowdlerize
 448 | boycott
 449 | braggart
 450 | bragger
 451 | brainless
 452 | brainwash
 453 | brash
 454 | brashly
 455 | brashness
 456 | brat
 457 | bravado
 458 | brazen
 459 | brazenly
 460 | brazenness
 461 | breach
 462 | break
 463 | break-up
 464 | break-ups
 465 | breakdown
 466 | breaking
 467 | breaks
 468 | breakup
 469 | breakups
 470 | bribery
 471 | brimstone
 472 | bristle
 473 | brittle
 474 | broke
 475 | broken
 476 | broken-hearted
 477 | brood
 478 | browbeat
 479 | bruise
 480 | bruised
 481 | bruises
 482 | bruising
 483 | brusque
 484 | brutal
 485 | brutalising
 486 | brutalities
 487 | brutality
 488 | brutalize
 489 | brutalizing
 490 | brutally
 491 | brute
 492 | brutish
 493 | bs
 494 | buckle
 495 | bug
 496 | bugging
 497 | buggy
 498 | bugs
 499 | bulkier
 500 | bulkiness
 501 | bulky
 502 | bulkyness
 503 | bull****
 504 | bull----
 505 | bullies
 506 | bullshit
 507 | bullshyt
 508 | bully
 509 | bullying
 510 | bullyingly
 511 | bum
 512 | bump
 513 | bumped
 514 | bumping
 515 | bumpping
 516 | bumps
 517 | bumpy
 518 | bungle
 519 | bungler
 520 | bungling
 521 | bunk
 522 | burden
 523 | burdensome
 524 | burdensomely
 525 | burn
 526 | burned
 527 | burning
 528 | burns
 529 | bust
 530 | busts
 531 | busybody
 532 | butcher
 533 | butchery
 534 | buzzing
 535 | byzantine
 536 | cackle
 537 | calamities
 538 | calamitous
 539 | calamitously
 540 | calamity
 541 | callous
 542 | calumniate
 543 | calumniation
 544 | calumnies
 545 | calumnious
 546 | calumniously
 547 | calumny
 548 | cancer
 549 | cancerous
 550 | cannibal
 551 | cannibalize
 552 | capitulate
 553 | capricious
 554 | capriciously
 555 | capriciousness
 556 | capsize
 557 | careless
 558 | carelessness
 559 | caricature
 560 | carnage
 561 | carp
 562 | cartoonish
 563 | cash-strapped
 564 | castigate
 565 | castrated
 566 | casualty
 567 | cataclysm
 568 | cataclysmal
 569 | cataclysmic
 570 | cataclysmically
 571 | catastrophe
 572 | catastrophes
 573 | catastrophic
 574 | catastrophically
 575 | catastrophies
 576 | caustic
 577 | caustically
 578 | cautionary
 579 | cave
 580 | censure
 581 | chafe
 582 | chaff
 583 | chagrin
 584 | challenging
 585 | chaos
 586 | chaotic
 587 | chasten
 588 | chastise
 589 | chastisement
 590 | chatter
 591 | chatterbox
 592 | cheap
 593 | cheapen
 594 | cheaply
 595 | cheat
 596 | cheated
 597 | cheater
 598 | cheating
 599 | cheats
 600 | checkered
 601 | cheerless
 602 | cheesy
 603 | chide
 604 | childish
 605 | chill
 606 | chilly
 607 | chintzy
 608 | choke
 609 | choleric
 610 | choppy
 611 | chore
 612 | chronic
 613 | chunky
 614 | clamor
 615 | clamorous
 616 | clash
 617 | cliche
 618 | cliched
 619 | clique
 620 | clog
 621 | clogged
 622 | clogs
 623 | cloud
 624 | clouding
 625 | cloudy
 626 | clueless
 627 | clumsy
 628 | clunky
 629 | coarse
 630 | cocky
 631 | coerce
 632 | coercion
 633 | coercive
 634 | cold
 635 | coldly
 636 | collapse
 637 | collude
 638 | collusion
 639 | combative
 640 | combust
 641 | comical
 642 | commiserate
 643 | commonplace
 644 | commotion
 645 | commotions
 646 | complacent
 647 | complain
 648 | complained
 649 | complaining
 650 | complains
 651 | complaint
 652 | complaints
 653 | complex
 654 | complicated
 655 | complication
 656 | complicit
 657 | compulsion
 658 | compulsive
 659 | concede
 660 | conceded
 661 | conceit
 662 | conceited
 663 | concen
 664 | concens
 665 | concern
 666 | concerned
 667 | concerns
 668 | concession
 669 | concessions
 670 | condemn
 671 | condemnable
 672 | condemnation
 673 | condemned
 674 | condemns
 675 | condescend
 676 | condescending
 677 | condescendingly
 678 | condescension
 679 | confess
 680 | confession
 681 | confessions
 682 | confined
 683 | conflict
 684 | conflicted
 685 | conflicting
 686 | conflicts
 687 | confound
 688 | confounded
 689 | confounding
 690 | confront
 691 | confrontation
 692 | confrontational
 693 | confuse
 694 | confused
 695 | confuses
 696 | confusing
 697 | confusion
 698 | confusions
 699 | congested
 700 | congestion
 701 | cons
 702 | conscons
 703 | conservative
 704 | conspicuous
 705 | conspicuously
 706 | conspiracies
 707 | conspiracy
 708 | conspirator
 709 | conspiratorial
 710 | conspire
 711 | consternation
 712 | contagious
 713 | contaminate
 714 | contaminated
 715 | contaminates
 716 | contaminating
 717 | contamination
 718 | contempt
 719 | contemptible
 720 | contemptuous
 721 | contemptuously
 722 | contend
 723 | contention
 724 | contentious
 725 | contort
 726 | contortions
 727 | contradict
 728 | contradiction
 729 | contradictory
 730 | contrariness
 731 | contravene
 732 | contrive
 733 | contrived
 734 | controversial
 735 | controversy
 736 | convoluted
 737 | corrode
 738 | corrosion
 739 | corrosions
 740 | corrosive
 741 | corrupt
 742 | corrupted
 743 | corrupting
 744 | corruption
 745 | corrupts
 746 | corruptted
 747 | costlier
 748 | costly
 749 | counter-productive
 750 | counterproductive
 751 | coupists
 752 | covetous
 753 | coward
 754 | cowardly
 755 | crabby
 756 | crack
 757 | cracked
 758 | cracks
 759 | craftily
 760 | craftly
 761 | crafty
 762 | cramp
 763 | cramped
 764 | cramping
 765 | cranky
 766 | crap
 767 | crappy
 768 | craps
 769 | crash
 770 | crashed
 771 | crashes
 772 | crashing
 773 | crass
 774 | craven
 775 | cravenly
 776 | craze
 777 | crazily
 778 | craziness
 779 | crazy
 780 | creak
 781 | creaking
 782 | creaks
 783 | credulous
 784 | creep
 785 | creeping
 786 | creeps
 787 | creepy
 788 | crept
 789 | crime
 790 | criminal
 791 | cringe
 792 | cringed
 793 | cringes
 794 | cripple
 795 | crippled
 796 | cripples
 797 | crippling
 798 | crisis
 799 | critic
 800 | critical
 801 | criticism
 802 | criticisms
 803 | criticize
 804 | criticized
 805 | criticizing
 806 | critics
 807 | cronyism
 808 | crook
 809 | crooked
 810 | crooks
 811 | crowded
 812 | crowdedness
 813 | crude
 814 | cruel
 815 | crueler
 816 | cruelest
 817 | cruelly
 818 | cruelness
 819 | cruelties
 820 | cruelty
 821 | crumble
 822 | crumbling
 823 | crummy
 824 | crumple
 825 | crumpled
 826 | crumples
 827 | crush
 828 | crushed
 829 | crushing
 830 | cry
 831 | culpable
 832 | culprit
 833 | cumbersome
 834 | cunt
 835 | cunts
 836 | cuplrit
 837 | curse
 838 | cursed
 839 | curses
 840 | curt
 841 | cuss
 842 | cussed
 843 | cutthroat
 844 | cynical
 845 | cynicism
 846 | d*mn
 847 | damage
 848 | damaged
 849 | damages
 850 | damaging
 851 | damn
 852 | damnable
 853 | damnably
 854 | damnation
 855 | damned
 856 | damning
 857 | damper
 858 | danger
 859 | dangerous
 860 | dangerousness
 861 | dark
 862 | darken
 863 | darkened
 864 | darker
 865 | darkness
 866 | dastard
 867 | dastardly
 868 | daunt
 869 | daunting
 870 | dauntingly
 871 | dawdle
 872 | daze
 873 | dazed
 874 | dead
 875 | deadbeat
 876 | deadlock
 877 | deadly
 878 | deadweight
 879 | deaf
 880 | dearth
 881 | death
 882 | debacle
 883 | debase
 884 | debasement
 885 | debaser
 886 | debatable
 887 | debauch
 888 | debaucher
 889 | debauchery
 890 | debilitate
 891 | debilitating
 892 | debility
 893 | debt
 894 | debts
 895 | decadence
 896 | decadent
 897 | decay
 898 | decayed
 899 | deceit
 900 | deceitful
 901 | deceitfully
 902 | deceitfulness
 903 | deceive
 904 | deceiver
 905 | deceivers
 906 | deceiving
 907 | deception
 908 | deceptive
 909 | deceptively
 910 | declaim
 911 | decline
 912 | declines
 913 | declining
 914 | decrement
 915 | decrepit
 916 | decrepitude
 917 | decry
 918 | defamation
 919 | defamations
 920 | defamatory
 921 | defame
 922 | defect
 923 | defective
 924 | defects
 925 | defensive
 926 | defiance
 927 | defiant
 928 | defiantly
 929 | deficiencies
 930 | deficiency
 931 | deficient
 932 | defile
 933 | defiler
 934 | deform
 935 | deformed
 936 | defrauding
 937 | defunct
 938 | defy
 939 | degenerate
 940 | degenerately
 941 | degeneration
 942 | degradation
 943 | degrade
 944 | degrading
 945 | degradingly
 946 | dehumanization
 947 | dehumanize
 948 | deign
 949 | deject
 950 | dejected
 951 | dejectedly
 952 | dejection
 953 | delay
 954 | delayed
 955 | delaying
 956 | delays
 957 | delinquency
 958 | delinquent
 959 | delirious
 960 | delirium
 961 | delude
 962 | deluded
 963 | deluge
 964 | delusion
 965 | delusional
 966 | delusions
 967 | demean
 968 | demeaning
 969 | demise
 970 | demolish
 971 | demolisher
 972 | demon
 973 | demonic
 974 | demonize
 975 | demonized
 976 | demonizes
 977 | demonizing
 978 | demoralize
 979 | demoralizing
 980 | demoralizingly
 981 | denial
 982 | denied
 983 | denies
 984 | denigrate
 985 | denounce
 986 | dense
 987 | dent
 988 | dented
 989 | dents
 990 | denunciate
 991 | denunciation
 992 | denunciations
 993 | deny
 994 | denying
 995 | deplete
 996 | deplorable
 997 | deplorably
 998 | deplore
 999 | deploring
1000 | deploringly
1001 | deprave
1002 | depraved
1003 | depravedly
1004 | deprecate
1005 | depress
1006 | depressed
1007 | depressing
1008 | depressingly
1009 | depression
1010 | depressions
1011 | deprive
1012 | deprived
1013 | deride
1014 | derision
1015 | derisive
1016 | derisively
1017 | derisiveness
1018 | derogatory
1019 | desecrate
1020 | desert
1021 | desertion
1022 | desiccate
1023 | desiccated
1024 | desititute
1025 | desolate
1026 | desolately
1027 | desolation
1028 | despair
1029 | despairing
1030 | despairingly
1031 | desperate
1032 | desperately
1033 | desperation
1034 | despicable
1035 | despicably
1036 | despise
1037 | despised
1038 | despoil
1039 | despoiler
1040 | despondence
1041 | despondency
1042 | despondent
1043 | despondently
1044 | despot
1045 | despotic
1046 | despotism
1047 | destabilisation
1048 | destains
1049 | destitute
1050 | destitution
1051 | destroy
1052 | destroyer
1053 | destruction
1054 | destructive
1055 | desultory
1056 | deter
1057 | deteriorate
1058 | deteriorating
1059 | deterioration
1060 | deterrent
1061 | detest
1062 | detestable
1063 | detestably
1064 | detested
1065 | detesting
1066 | detests
1067 | detract
1068 | detracted
1069 | detracting
1070 | detraction
1071 | detracts
1072 | detriment
1073 | detrimental
1074 | devastate
1075 | devastated
1076 | devastates
1077 | devastating
1078 | devastatingly
1079 | devastation
1080 | deviate
1081 | deviation
1082 | devil
1083 | devilish
1084 | devilishly
1085 | devilment
1086 | devilry
1087 | devious
1088 | deviously
1089 | deviousness
1090 | devoid
1091 | diabolic
1092 | diabolical
1093 | diabolically
1094 | diametrically
1095 | diappointed
1096 | diatribe
1097 | diatribes
1098 | dick
1099 | dictator
1100 | dictatorial
1101 | die
1102 | die-hard
1103 | died
1104 | dies
1105 | difficult
1106 | difficulties
1107 | difficulty
1108 | diffidence
1109 | dilapidated
1110 | dilemma
1111 | dilly-dally
1112 | dim
1113 | dimmer
1114 | din
1115 | ding
1116 | dings
1117 | dinky
1118 | dire
1119 | direly
1120 | direness
1121 | dirt
1122 | dirtbag
1123 | dirtbags
1124 | dirts
1125 | dirty
1126 | disable
1127 | disabled
1128 | disaccord
1129 | disadvantage
1130 | disadvantaged
1131 | disadvantageous
1132 | disadvantages
1133 | disaffect
1134 | disaffected
1135 | disaffirm
1136 | disagree
1137 | disagreeable
1138 | disagreeably
1139 | disagreed
1140 | disagreeing
1141 | disagreement
1142 | disagrees
1143 | disallow
1144 | disapointed
1145 | disapointing
1146 | disapointment
1147 | disappoint
1148 | disappointed
1149 | disappointing
1150 | disappointingly
1151 | disappointment
1152 | disappointments
1153 | disappoints
1154 | disapprobation
1155 | disapproval
1156 | disapprove
1157 | disapproving
1158 | disarm
1159 | disarray
1160 | disaster
1161 | disasterous
1162 | disastrous
1163 | disastrously
1164 | disavow
1165 | disavowal
1166 | disbelief
1167 | disbelieve
1168 | disbeliever
1169 | disclaim
1170 | discombobulate
1171 | discomfit
1172 | discomfititure
1173 | discomfort
1174 | discompose
1175 | disconcert
1176 | disconcerted
1177 | disconcerting
1178 | disconcertingly
1179 | disconsolate
1180 | disconsolately
1181 | disconsolation
1182 | discontent
1183 | discontented
1184 | discontentedly
1185 | discontinued
1186 | discontinuity
1187 | discontinuous
1188 | discord
1189 | discordance
1190 | discordant
1191 | discountenance
1192 | discourage
1193 | discouragement
1194 | discouraging
1195 | discouragingly
1196 | discourteous
1197 | discourteously
1198 | discoutinous
1199 | discredit
1200 | discrepant
1201 | discriminate
1202 | discrimination
1203 | discriminatory
1204 | disdain
1205 | disdained
1206 | disdainful
1207 | disdainfully
1208 | disfavor
1209 | disgrace
1210 | disgraced
1211 | disgraceful
1212 | disgracefully
1213 | disgruntle
1214 | disgruntled
1215 | disgust
1216 | disgusted
1217 | disgustedly
1218 | disgustful
1219 | disgustfully
1220 | disgusting
1221 | disgustingly
1222 | dishearten
1223 | disheartening
1224 | dishearteningly
1225 | dishonest
1226 | dishonestly
1227 | dishonesty
1228 | dishonor
1229 | dishonorable
1230 | dishonorablely
1231 | disillusion
1232 | disillusioned
1233 | disillusionment
1234 | disillusions
1235 | disinclination
1236 | disinclined
1237 | disingenuous
1238 | disingenuously
1239 | disintegrate
1240 | disintegrated
1241 | disintegrates
1242 | disintegration
1243 | disinterest
1244 | disinterested
1245 | dislike
1246 | disliked
1247 | dislikes
1248 | disliking
1249 | dislocated
1250 | disloyal
1251 | disloyalty
1252 | dismal
1253 | dismally
1254 | dismalness
1255 | dismay
1256 | dismayed
1257 | dismaying
1258 | dismayingly
1259 | dismissive
1260 | dismissively
1261 | disobedience
1262 | disobedient
1263 | disobey
1264 | disoobedient
1265 | disorder
1266 | disordered
1267 | disorderly
1268 | disorganized
1269 | disorient
1270 | disoriented
1271 | disown
1272 | disparage
1273 | disparaging
1274 | disparagingly
1275 | dispensable
1276 | dispirit
1277 | dispirited
1278 | dispiritedly
1279 | dispiriting
1280 | displace
1281 | displaced
1282 | displease
1283 | displeased
1284 | displeasing
1285 | displeasure
1286 | disproportionate
1287 | disprove
1288 | disputable
1289 | dispute
1290 | disputed
1291 | disquiet
1292 | disquieting
1293 | disquietingly
1294 | disquietude
1295 | disregard
1296 | disregardful
1297 | disreputable
1298 | disrepute
1299 | disrespect
1300 | disrespectable
1301 | disrespectablity
1302 | disrespectful
1303 | disrespectfully
1304 | disrespectfulness
1305 | disrespecting
1306 | disrupt
1307 | disruption
1308 | disruptive
1309 | diss
1310 | dissapointed
1311 | dissappointed
1312 | dissappointing
1313 | dissatisfaction
1314 | dissatisfactory
1315 | dissatisfied
1316 | dissatisfies
1317 | dissatisfy
1318 | dissatisfying
1319 | dissed
1320 | dissemble
1321 | dissembler
1322 | dissension
1323 | dissent
1324 | dissenter
1325 | dissention
1326 | disservice
1327 | disses
1328 | dissidence
1329 | dissident
1330 | dissidents
1331 | dissing
1332 | dissocial
1333 | dissolute
1334 | dissolution
1335 | dissonance
1336 | dissonant
1337 | dissonantly
1338 | dissuade
1339 | dissuasive
1340 | distains
1341 | distaste
1342 | distasteful
1343 | distastefully
1344 | distort
1345 | distorted
1346 | distortion
1347 | distorts
1348 | distract
1349 | distracting
1350 | distraction
1351 | distraught
1352 | distraughtly
1353 | distraughtness
1354 | distress
1355 | distressed
1356 | distressing
1357 | distressingly
1358 | distrust
1359 | distrustful
1360 | distrusting
1361 | disturb
1362 | disturbance
1363 | disturbed
1364 | disturbing
1365 | disturbingly
1366 | disunity
1367 | disvalue
1368 | divergent
1369 | divisive
1370 | divisively
1371 | divisiveness
1372 | dizzing
1373 | dizzingly
1374 | dizzy
1375 | doddering
1376 | dodgey
1377 | dogged
1378 | doggedly
1379 | dogmatic
1380 | doldrums
1381 | domineer
1382 | domineering
1383 | donside
1384 | doom
1385 | doomed
1386 | doomsday
1387 | dope
1388 | doubt
1389 | doubtful
1390 | doubtfully
1391 | doubts
1392 | douchbag
1393 | douchebag
1394 | douchebags
1395 | downbeat
1396 | downcast
1397 | downer
1398 | downfall
1399 | downfallen
1400 | downgrade
1401 | downhearted
1402 | downheartedly
1403 | downhill
1404 | downside
1405 | downsides
1406 | downturn
1407 | downturns
1408 | drab
1409 | draconian
1410 | draconic
1411 | drag
1412 | dragged
1413 | dragging
1414 | dragoon
1415 | drags
1416 | drain
1417 | drained
1418 | draining
1419 | drains
1420 | drastic
1421 | drastically
1422 | drawback
1423 | drawbacks
1424 | dread
1425 | dreadful
1426 | dreadfully
1427 | dreadfulness
1428 | dreary
1429 | dripped
1430 | dripping
1431 | drippy
1432 | drips
1433 | drones
1434 | droop
1435 | droops
1436 | drop-out
1437 | drop-outs
1438 | dropout
1439 | dropouts
1440 | drought
1441 | drowning
1442 | drunk
1443 | drunkard
1444 | drunken
1445 | dubious
1446 | dubiously
1447 | dubitable
1448 | dud
1449 | dull
1450 | dullard
1451 | dumb
1452 | dumbfound
1453 | dump
1454 | dumped
1455 | dumping
1456 | dumps
1457 | dunce
1458 | dungeon
1459 | dungeons
1460 | dupe
1461 | dust
1462 | dusty
1463 | dwindling
1464 | dying
1465 | earsplitting
1466 | eccentric
1467 | eccentricity
1468 | effigy
1469 | effrontery
1470 | egocentric
1471 | egomania
1472 | egotism
1473 | egotistical
1474 | egotistically
1475 | egregious
1476 | egregiously
1477 | election-rigger
1478 | elimination
1479 | emaciated
1480 | emasculate
1481 | embarrass
1482 | embarrassing
1483 | embarrassingly
1484 | embarrassment
1485 | embattled
1486 | embroil
1487 | embroiled
1488 | embroilment
1489 | emergency
1490 | emphatic
1491 | emphatically
1492 | emptiness
1493 | encroach
1494 | encroachment
1495 | endanger
1496 | enemies
1497 | enemy
1498 | enervate
1499 | enfeeble
1500 | enflame
1501 | engulf
1502 | enjoin
1503 | enmity
1504 | enrage
1505 | enraged
1506 | enraging
1507 | enslave
1508 | entangle
1509 | entanglement
1510 | entrap
1511 | entrapment
1512 | envious
1513 | enviously
1514 | enviousness
1515 | epidemic
1516 | equivocal
1517 | erase
1518 | erode
1519 | erodes
1520 | erosion
1521 | err
1522 | errant
1523 | erratic
1524 | erratically
1525 | erroneous
1526 | erroneously
1527 | error
1528 | errors
1529 | eruptions
1530 | escapade
1531 | eschew
1532 | estranged
1533 | evade
1534 | evasion
1535 | evasive
1536 | evil
1537 | evildoer
1538 | evils
1539 | eviscerate
1540 | exacerbate
1541 | exagerate
1542 | exagerated
1543 | exagerates
1544 | exaggerate
1545 | exaggeration
1546 | exasperate
1547 | exasperated
1548 | exasperating
1549 | exasperatingly
1550 | exasperation
1551 | excessive
1552 | excessively
1553 | exclusion
1554 | excoriate
1555 | excruciating
1556 | excruciatingly
1557 | excuse
1558 | excuses
1559 | execrate
1560 | exhaust
1561 | exhausted
1562 | exhaustion
1563 | exhausts
1564 | exhorbitant
1565 | exhort
1566 | exile
1567 | exorbitant
1568 | exorbitantance
1569 | exorbitantly
1570 | expel
1571 | expensive
1572 | expire
1573 | expired
1574 | explode
1575 | exploit
1576 | exploitation
1577 | explosive
1578 | expropriate
1579 | expropriation
1580 | expulse
1581 | expunge
1582 | exterminate
1583 | extermination
1584 | extinguish
1585 | extort
1586 | extortion
1587 | extraneous
1588 | extravagance
1589 | extravagant
1590 | extravagantly
1591 | extremism
1592 | extremist
1593 | extremists
1594 | eyesore
1595 | f**k
1596 | fabricate
1597 | fabrication
1598 | facetious
1599 | facetiously
1600 | fail
1601 | failed
1602 | failing
1603 | fails
1604 | failure
1605 | failures
1606 | faint
1607 | fainthearted
1608 | faithless
1609 | fake
1610 | fall
1611 | fallacies
1612 | fallacious
1613 | fallaciously
1614 | fallaciousness
1615 | fallacy
1616 | fallen
1617 | falling
1618 | fallout
1619 | falls
1620 | false
1621 | falsehood
1622 | falsely
1623 | falsify
1624 | falter
1625 | faltered
1626 | famine
1627 | famished
1628 | fanatic
1629 | fanatical
1630 | fanatically
1631 | fanaticism
1632 | fanatics
1633 | fanciful
1634 | far-fetched
1635 | farce
1636 | farcical
1637 | farcical-yet-provocative
1638 | farcically
1639 | farfetched
1640 | fascism
1641 | fascist
1642 | fastidious
1643 | fastidiously
1644 | fastuous
1645 | fat
1646 | fat-cat
1647 | fat-cats
1648 | fatal
1649 | fatalistic
1650 | fatalistically
1651 | fatally
1652 | fatcat
1653 | fatcats
1654 | fateful
1655 | fatefully
1656 | fathomless
1657 | fatigue
1658 | fatigued
1659 | fatique
1660 | fatty
1661 | fatuity
1662 | fatuous
1663 | fatuously
1664 | fault
1665 | faults
1666 | faulty
1667 | fawningly
1668 | faze
1669 | fear
1670 | fearful
1671 | fearfully
1672 | fears
1673 | fearsome
1674 | feckless
1675 | feeble
1676 | feeblely
1677 | feebleminded
1678 | feign
1679 | feint
1680 | fell
1681 | felon
1682 | felonious
1683 | ferociously
1684 | ferocity
1685 | fetid
1686 | fever
1687 | feverish
1688 | fevers
1689 | fiasco
1690 | fib
1691 | fibber
1692 | fickle
1693 | fiction
1694 | fictional
1695 | fictitious
1696 | fidget
1697 | fidgety
1698 | fiend
1699 | fiendish
1700 | fierce
1701 | figurehead
1702 | filth
1703 | filthy
1704 | finagle
1705 | finicky
1706 | fissures
1707 | fist
1708 | flabbergast
1709 | flabbergasted
1710 | flagging
1711 | flagrant
1712 | flagrantly
1713 | flair
1714 | flairs
1715 | flak
1716 | flake
1717 | flakey
1718 | flakieness
1719 | flaking
1720 | flaky
1721 | flare
1722 | flares
1723 | flareup
1724 | flareups
1725 | flat-out
1726 | flaunt
1727 | flaw
1728 | flawed
1729 | flaws
1730 | flee
1731 | fleed
1732 | fleeing
1733 | fleer
1734 | flees
1735 | fleeting
1736 | flicering
1737 | flicker
1738 | flickering
1739 | flickers
1740 | flighty
1741 | flimflam
1742 | flimsy
1743 | flirt
1744 | flirty
1745 | floored
1746 | flounder
1747 | floundering
1748 | flout
1749 | fluster
1750 | foe
1751 | fool
1752 | fooled
1753 | foolhardy
1754 | foolish
1755 | foolishly
1756 | foolishness
1757 | forbid
1758 | forbidden
1759 | forbidding
1760 | forceful
1761 | foreboding
1762 | forebodingly
1763 | forfeit
1764 | forged
1765 | forgetful
1766 | forgetfully
1767 | forgetfulness
1768 | forlorn
1769 | forlornly
1770 | forsake
1771 | forsaken
1772 | forswear
1773 | foul
1774 | foully
1775 | foulness
1776 | fractious
1777 | fractiously
1778 | fracture
1779 | fragile
1780 | fragmented
1781 | frail
1782 | frantic
1783 | frantically
1784 | franticly
1785 | fraud
1786 | fraudulent
1787 | fraught
1788 | frazzle
1789 | frazzled
1790 | freak
1791 | freaking
1792 | freakish
1793 | freakishly
1794 | freaks
1795 | freeze
1796 | freezes
1797 | freezing
1798 | frenetic
1799 | frenetically
1800 | frenzied
1801 | frenzy
1802 | fret
1803 | fretful
1804 | frets
1805 | friction
1806 | frictions
1807 | fried
1808 | friggin
1809 | frigging
1810 | fright
1811 | frighten
1812 | frightening
1813 | frighteningly
1814 | frightful
1815 | frightfully
1816 | frigid
1817 | frost
1818 | frown
1819 | froze
1820 | frozen
1821 | fruitless
1822 | fruitlessly
1823 | frustrate
1824 | frustrated
1825 | frustrates
1826 | frustrating
1827 | frustratingly
1828 | frustration
1829 | frustrations
1830 | fuck
1831 | fucking
1832 | fudge
1833 | fugitive
1834 | full-blown
1835 | fulminate
1836 | fumble
1837 | fume
1838 | fumes
1839 | fundamentalism
1840 | funky
1841 | funnily
1842 | funny
1843 | furious
1844 | furiously
1845 | furor
1846 | fury
1847 | fuss
1848 | fussy
1849 | fustigate
1850 | fusty
1851 | futile
1852 | futilely
1853 | futility
1854 | fuzzy
1855 | gabble
1856 | gaff
1857 | gaffe
1858 | gainsay
1859 | gainsayer
1860 | gall
1861 | galling
1862 | gallingly
1863 | galls
1864 | gangster
1865 | gape
1866 | garbage
1867 | garish
1868 | gasp
1869 | gauche
1870 | gaudy
1871 | gawk
1872 | gawky
1873 | geezer
1874 | genocide
1875 | get-rich
1876 | ghastly
1877 | ghetto
1878 | ghosting
1879 | gibber
1880 | gibberish
1881 | gibe
1882 | giddy
1883 | gimmick
1884 | gimmicked
1885 | gimmicking
1886 | gimmicks
1887 | gimmicky
1888 | glare
1889 | glaringly
1890 | glib
1891 | glibly
1892 | glitch
1893 | glitches
1894 | gloatingly
1895 | gloom
1896 | gloomy
1897 | glower
1898 | glum
1899 | glut
1900 | gnawing
1901 | goad
1902 | goading
1903 | god-awful
1904 | goof
1905 | goofy
1906 | goon
1907 | gossip
1908 | graceless
1909 | gracelessly
1910 | graft
1911 | grainy
1912 | grapple
1913 | grate
1914 | grating
1915 | gravely
1916 | greasy
1917 | greed
1918 | greedy
1919 | grief
1920 | grievance
1921 | grievances
1922 | grieve
1923 | grieving
1924 | grievous
1925 | grievously
1926 | grim
1927 | grimace
1928 | grind
1929 | gripe
1930 | gripes
1931 | grisly
1932 | gritty
1933 | gross
1934 | grossly
1935 | grotesque
1936 | grouch
1937 | grouchy
1938 | groundless
1939 | grouse
1940 | growl
1941 | grudge
1942 | grudges
1943 | grudging
1944 | grudgingly
1945 | gruesome
1946 | gruesomely
1947 | gruff
1948 | grumble
1949 | grumpier
1950 | grumpiest
1951 | grumpily
1952 | grumpish
1953 | grumpy
1954 | guile
1955 | guilt
1956 | guiltily
1957 | guilty
1958 | gullible
1959 | gutless
1960 | gutter
1961 | hack
1962 | hacks
1963 | haggard
1964 | haggle
1965 | hairloss
1966 | halfhearted
1967 | halfheartedly
1968 | hallucinate
1969 | hallucination
1970 | hamper
1971 | hampered
1972 | handicapped
1973 | hang
1974 | hangs
1975 | haphazard
1976 | hapless
1977 | harangue
1978 | harass
1979 | harassed
1980 | harasses
1981 | harassment
1982 | harboring
1983 | harbors
1984 | hard
1985 | hard-hit
1986 | hard-line
1987 | hard-liner
1988 | hardball
1989 | harden
1990 | hardened
1991 | hardheaded
1992 | hardhearted
1993 | hardliner
1994 | hardliners
1995 | hardship
1996 | hardships
1997 | harm
1998 | harmed
1999 | harmful
2000 | harms
2001 | harpy
2002 | harridan
2003 | harried
2004 | harrow
2005 | harsh
2006 | harshly
2007 | hasseling
2008 | hassle
2009 | hassled
2010 | hassles
2011 | haste
2012 | hastily
2013 | hasty
2014 | hate
2015 | hated
2016 | hateful
2017 | hatefully
2018 | hatefulness
2019 | hater
2020 | haters
2021 | hates
2022 | hating
2023 | hatred
2024 | haughtily
2025 | haughty
2026 | haunt
2027 | haunting
2028 | havoc
2029 | hawkish
2030 | haywire
2031 | hazard
2032 | hazardous
2033 | haze
2034 | hazy
2035 | head-aches
2036 | headache
2037 | headaches
2038 | heartbreaker
2039 | heartbreaking
2040 | heartbreakingly
2041 | heartless
2042 | heathen
2043 | heavy-handed
2044 | heavyhearted
2045 | heck
2046 | heckle
2047 | heckled
2048 | heckles
2049 | hectic
2050 | hedge
2051 | hedonistic
2052 | heedless
2053 | hefty
2054 | hegemonism
2055 | hegemonistic
2056 | hegemony
2057 | heinous
2058 | hell
2059 | hell-bent
2060 | hellion
2061 | hells
2062 | helpless
2063 | helplessly
2064 | helplessness
2065 | heresy
2066 | heretic
2067 | heretical
2068 | hesitant
2069 | hestitant
2070 | hideous
2071 | hideously
2072 | hideousness
2073 | high-priced
2074 | hiliarious
2075 | hinder
2076 | hindrance
2077 | hiss
2078 | hissed
2079 | hissing
2080 | ho-hum
2081 | hoard
2082 | hoax
2083 | hobble
2084 | hogs
2085 | hollow
2086 | hoodium
2087 | hoodwink
2088 | hooligan
2089 | hopeless
2090 | hopelessly
2091 | hopelessness
2092 | horde
2093 | horrendous
2094 | horrendously
2095 | horrible
2096 | horrid
2097 | horrific
2098 | horrified
2099 | horrifies
2100 | horrify
2101 | horrifying
2102 | horrifys
2103 | hostage
2104 | hostile
2105 | hostilities
2106 | hostility
2107 | hotbeds
2108 | hothead
2109 | hotheaded
2110 | hothouse
2111 | hubris
2112 | huckster
2113 | hum
2114 | humid
2115 | humiliate
2116 | humiliating
2117 | humiliation
2118 | humming
2119 | hung
2120 | hurt
2121 | hurted
2122 | hurtful
2123 | hurting
2124 | hurts
2125 | hustler
2126 | hype
2127 | hypocricy
2128 | hypocrisy
2129 | hypocrite
2130 | hypocrites
2131 | hypocritical
2132 | hypocritically
2133 | hysteria
2134 | hysteric
2135 | hysterical
2136 | hysterically
2137 | hysterics
2138 | idiocies
2139 | idiocy
2140 | idiot
2141 | idiotic
2142 | idiotically
2143 | idiots
2144 | idle
2145 | ignoble
2146 | ignominious
2147 | ignominiously
2148 | ignominy
2149 | ignorance
2150 | ignorant
2151 | ignore
2152 | ill-advised
2153 | ill-conceived
2154 | ill-defined
2155 | ill-designed
2156 | ill-fated
2157 | ill-favored
2158 | ill-formed
2159 | ill-mannered
2160 | ill-natured
2161 | ill-sorted
2162 | ill-tempered
2163 | ill-treated
2164 | ill-treatment
2165 | ill-usage
2166 | ill-used
2167 | illegal
2168 | illegally
2169 | illegitimate
2170 | illicit
2171 | illiterate
2172 | illness
2173 | illogic
2174 | illogical
2175 | illogically
2176 | illusion
2177 | illusions
2178 | illusory
2179 | imaginary
2180 | imbalance
2181 | imbecile
2182 | imbroglio
2183 | immaterial
2184 | immature
2185 | imminence
2186 | imminently
2187 | immobilized
2188 | immoderate
2189 | immoderately
2190 | immodest
2191 | immoral
2192 | immorality
2193 | immorally
2194 | immovable
2195 | impair
2196 | impaired
2197 | impasse
2198 | impatience
2199 | impatient
2200 | impatiently
2201 | impeach
2202 | impedance
2203 | impede
2204 | impediment
2205 | impending
2206 | impenitent
2207 | imperfect
2208 | imperfection
2209 | imperfections
2210 | imperfectly
2211 | imperialist
2212 | imperil
2213 | imperious
2214 | imperiously
2215 | impermissible
2216 | impersonal
2217 | impertinent
2218 | impetuous
2219 | impetuously
2220 | impiety
2221 | impinge
2222 | impious
2223 | implacable
2224 | implausible
2225 | implausibly
2226 | implicate
2227 | implication
2228 | implode
2229 | impolite
2230 | impolitely
2231 | impolitic
2232 | importunate
2233 | importune
2234 | impose
2235 | imposers
2236 | imposing
2237 | imposition
2238 | impossible
2239 | impossiblity
2240 | impossibly
2241 | impotent
2242 | impoverish
2243 | impoverished
2244 | impractical
2245 | imprecate
2246 | imprecise
2247 | imprecisely
2248 | imprecision
2249 | imprison
2250 | imprisonment
2251 | improbability
2252 | improbable
2253 | improbably
2254 | improper
2255 | improperly
2256 | impropriety
2257 | imprudence
2258 | imprudent
2259 | impudence
2260 | impudent
2261 | impudently
2262 | impugn
2263 | impulsive
2264 | impulsively
2265 | impunity
2266 | impure
2267 | impurity
2268 | inability
2269 | inaccuracies
2270 | inaccuracy
2271 | inaccurate
2272 | inaccurately
2273 | inaction
2274 | inactive
2275 | inadequacy
2276 | inadequate
2277 | inadequately
2278 | inadverent
2279 | inadverently
2280 | inadvisable
2281 | inadvisably
2282 | inane
2283 | inanely
2284 | inappropriate
2285 | inappropriately
2286 | inapt
2287 | inaptitude
2288 | inarticulate
2289 | inattentive
2290 | inaudible
2291 | incapable
2292 | incapably
2293 | incautious
2294 | incendiary
2295 | incense
2296 | incessant
2297 | incessantly
2298 | incite
2299 | incitement
2300 | incivility
2301 | inclement
2302 | incognizant
2303 | incoherence
2304 | incoherent
2305 | incoherently
2306 | incommensurate
2307 | incomparable
2308 | incomparably
2309 | incompatability
2310 | incompatibility
2311 | incompatible
2312 | incompetence
2313 | incompetent
2314 | incompetently
2315 | incomplete
2316 | incompliant
2317 | incomprehensible
2318 | incomprehension
2319 | inconceivable
2320 | inconceivably
2321 | incongruous
2322 | incongruously
2323 | inconsequent
2324 | inconsequential
2325 | inconsequentially
2326 | inconsequently
2327 | inconsiderate
2328 | inconsiderately
2329 | inconsistence
2330 | inconsistencies
2331 | inconsistency
2332 | inconsistent
2333 | inconsolable
2334 | inconsolably
2335 | inconstant
2336 | inconvenience
2337 | inconveniently
2338 | incorrect
2339 | incorrectly
2340 | incorrigible
2341 | incorrigibly
2342 | incredulous
2343 | incredulously
2344 | inculcate
2345 | indecency
2346 | indecent
2347 | indecently
2348 | indecision
2349 | indecisive
2350 | indecisively
2351 | indecorum
2352 | indefensible
2353 | indelicate
2354 | indeterminable
2355 | indeterminably
2356 | indeterminate
2357 | indifference
2358 | indifferent
2359 | indigent
2360 | indignant
2361 | indignantly
2362 | indignation
2363 | indignity
2364 | indiscernible
2365 | indiscreet
2366 | indiscreetly
2367 | indiscretion
2368 | indiscriminate
2369 | indiscriminately
2370 | indiscriminating
2371 | indistinguishable
2372 | indoctrinate
2373 | indoctrination
2374 | indolent
2375 | indulge
2376 | ineffective
2377 | ineffectively
2378 | ineffectiveness
2379 | ineffectual
2380 | ineffectually
2381 | ineffectualness
2382 | inefficacious
2383 | inefficacy
2384 | inefficiency
2385 | inefficient
2386 | inefficiently
2387 | inelegance
2388 | inelegant
2389 | ineligible
2390 | ineloquent
2391 | ineloquently
2392 | inept
2393 | ineptitude
2394 | ineptly
2395 | inequalities
2396 | inequality
2397 | inequitable
2398 | inequitably
2399 | inequities
2400 | inescapable
2401 | inescapably
2402 | inessential
2403 | inevitable
2404 | inevitably
2405 | inexcusable
2406 | inexcusably
2407 | inexorable
2408 | inexorably
2409 | inexperience
2410 | inexperienced
2411 | inexpert
2412 | inexpertly
2413 | inexpiable
2414 | inexplainable
2415 | inextricable
2416 | inextricably
2417 | infamous
2418 | infamously
2419 | infamy
2420 | infected
2421 | infection
2422 | infections
2423 | inferior
2424 | inferiority
2425 | infernal
2426 | infest
2427 | infested
2428 | infidel
2429 | infidels
2430 | infiltrator
2431 | infiltrators
2432 | infirm
2433 | inflame
2434 | inflammation
2435 | inflammatory
2436 | inflammed
2437 | inflated
2438 | inflationary
2439 | inflexible
2440 | inflict
2441 | infraction
2442 | infringe
2443 | infringement
2444 | infringements
2445 | infuriate
2446 | infuriated
2447 | infuriating
2448 | infuriatingly
2449 | inglorious
2450 | ingrate
2451 | ingratitude
2452 | inhibit
2453 | inhibition
2454 | inhospitable
2455 | inhospitality
2456 | inhuman
2457 | inhumane
2458 | inhumanity
2459 | inimical
2460 | inimically
2461 | iniquitous
2462 | iniquity
2463 | injudicious
2464 | injure
2465 | injurious
2466 | injury
2467 | injustice
2468 | injustices
2469 | innuendo
2470 | inoperable
2471 | inopportune
2472 | inordinate
2473 | inordinately
2474 | insane
2475 | insanely
2476 | insanity
2477 | insatiable
2478 | insecure
2479 | insecurity
2480 | insensible
2481 | insensitive
2482 | insensitively
2483 | insensitivity
2484 | insidious
2485 | insidiously
2486 | insignificance
2487 | insignificant
2488 | insignificantly
2489 | insincere
2490 | insincerely
2491 | insincerity
2492 | insinuate
2493 | insinuating
2494 | insinuation
2495 | insociable
2496 | insolence
2497 | insolent
2498 | insolently
2499 | insolvent
2500 | insouciance
2501 | instability
2502 | instable
2503 | instigate
2504 | instigator
2505 | instigators
2506 | insubordinate
2507 | insubstantial
2508 | insubstantially
2509 | insufferable
2510 | insufferably
2511 | insufficiency
2512 | insufficient
2513 | insufficiently
2514 | insular
2515 | insult
2516 | insulted
2517 | insulting
2518 | insultingly
2519 | insults
2520 | insupportable
2521 | insupportably
2522 | insurmountable
2523 | insurmountably
2524 | insurrection
2525 | intefere
2526 | inteferes
2527 | intense
2528 | interfere
2529 | interference
2530 | interferes
2531 | intermittent
2532 | interrupt
2533 | interruption
2534 | interruptions
2535 | intimidate
2536 | intimidating
2537 | intimidatingly
2538 | intimidation
2539 | intolerable
2540 | intolerablely
2541 | intolerance
2542 | intoxicate
2543 | intractable
2544 | intransigence
2545 | intransigent
2546 | intrude
2547 | intrusion
2548 | intrusive
2549 | inundate
2550 | inundated
2551 | invader
2552 | invalid
2553 | invalidate
2554 | invalidity
2555 | invasive
2556 | invective
2557 | inveigle
2558 | invidious
2559 | invidiously
2560 | invidiousness
2561 | invisible
2562 | involuntarily
2563 | involuntary
2564 | irascible
2565 | irate
2566 | irately
2567 | ire
2568 | irk
2569 | irked
2570 | irking
2571 | irks
2572 | irksome
2573 | irksomely
2574 | irksomeness
2575 | irksomenesses
2576 | ironic
2577 | ironical
2578 | ironically
2579 | ironies
2580 | irony
2581 | irragularity
2582 | irrational
2583 | irrationalities
2584 | irrationality
2585 | irrationally
2586 | irrationals
2587 | irreconcilable
2588 | irrecoverable
2589 | irrecoverableness
2590 | irrecoverablenesses
2591 | irrecoverably
2592 | irredeemable
2593 | irredeemably
2594 | irreformable
2595 | irregular
2596 | irregularity
2597 | irrelevance
2598 | irrelevant
2599 | irreparable
2600 | irreplacible
2601 | irrepressible
2602 | irresolute
2603 | irresolvable
2604 | irresponsible
2605 | irresponsibly
2606 | irretating
2607 | irretrievable
2608 | irreversible
2609 | irritable
2610 | irritably
2611 | irritant
2612 | irritate
2613 | irritated
2614 | irritating
2615 | irritation
2616 | irritations
2617 | isolate
2618 | isolated
2619 | isolation
2620 | issue
2621 | issues
2622 | itch
2623 | itching
2624 | itchy
2625 | jabber
2626 | jaded
2627 | jagged
2628 | jam
2629 | jarring
2630 | jaundiced
2631 | jealous
2632 | jealously
2633 | jealousness
2634 | jealousy
2635 | jeer
2636 | jeering
2637 | jeeringly
2638 | jeers
2639 | jeopardize
2640 | jeopardy
2641 | jerk
2642 | jerky
2643 | jitter
2644 | jitters
2645 | jittery
2646 | job-killing
2647 | jobless
2648 | joke
2649 | joker
2650 | jolt
2651 | judder
2652 | juddering
2653 | judders
2654 | jumpy
2655 | junk
2656 | junky
2657 | junkyard
2658 | jutter
2659 | jutters
2660 | kaput
2661 | kill
2662 | killed
2663 | killer
2664 | killing
2665 | killjoy
2666 | kills
2667 | knave
2668 | knife
2669 | knock
2670 | knotted
2671 | kook
2672 | kooky
2673 | lack
2674 | lackadaisical
2675 | lacked
2676 | lackey
2677 | lackeys
2678 | lacking
2679 | lackluster
2680 | lacks
2681 | laconic
2682 | lag
2683 | lagged
2684 | lagging
2685 | laggy
2686 | lags
2687 | laid-off
2688 | lambast
2689 | lambaste
2690 | lame
2691 | lame-duck
2692 | lament
2693 | lamentable
2694 | lamentably
2695 | languid
2696 | languish
2697 | languor
2698 | languorous
2699 | languorously
2700 | lanky
2701 | lapse
2702 | lapsed
2703 | lapses
2704 | lascivious
2705 | last-ditch
2706 | latency
2707 | laughable
2708 | laughably
2709 | laughingstock
2710 | lawbreaker
2711 | lawbreaking
2712 | lawless
2713 | lawlessness
2714 | layoff
2715 | layoff-happy
2716 | lazy
2717 | leak
2718 | leakage
2719 | leakages
2720 | leaking
2721 | leaks
2722 | leaky
2723 | lech
2724 | lecher
2725 | lecherous
2726 | lechery
2727 | leech
2728 | leer
2729 | leery
2730 | left-leaning
2731 | lemon
2732 | lengthy
2733 | less-developed
2734 | lesser-known
2735 | letch
2736 | lethal
2737 | lethargic
2738 | lethargy
2739 | lewd
2740 | lewdly
2741 | lewdness
2742 | liability
2743 | liable
2744 | liar
2745 | liars
2746 | licentious
2747 | licentiously
2748 | licentiousness
2749 | lie
2750 | lied
2751 | lier
2752 | lies
2753 | life-threatening
2754 | lifeless
2755 | limit
2756 | limitation
2757 | limitations
2758 | limited
2759 | limits
2760 | limp
2761 | listless
2762 | litigious
2763 | little-known
2764 | livid
2765 | lividly
2766 | loath
2767 | loathe
2768 | loathing
2769 | loathly
2770 | loathsome
2771 | loathsomely
2772 | lone
2773 | loneliness
2774 | lonely
2775 | loner
2776 | lonesome
2777 | long-time
2778 | long-winded
2779 | longing
2780 | longingly
2781 | loophole
2782 | loopholes
2783 | loose
2784 | loot
2785 | lorn
2786 | lose
2787 | loser
2788 | losers
2789 | loses
2790 | losing
2791 | loss
2792 | losses
2793 | lost
2794 | loud
2795 | louder
2796 | lousy
2797 | loveless
2798 | lovelorn
2799 | low-rated
2800 | lowly
2801 | ludicrous
2802 | ludicrously
2803 | lugubrious
2804 | lukewarm
2805 | lull
2806 | lumpy
2807 | lunatic
2808 | lunaticism
2809 | lurch
2810 | lure
2811 | lurid
2812 | lurk
2813 | lurking
2814 | lying
2815 | macabre
2816 | mad
2817 | madden
2818 | maddening
2819 | maddeningly
2820 | madder
2821 | madly
2822 | madman
2823 | madness
2824 | maladjusted
2825 | maladjustment
2826 | malady
2827 | malaise
2828 | malcontent
2829 | malcontented
2830 | maledict
2831 | malevolence
2832 | malevolent
2833 | malevolently
2834 | malice
2835 | malicious
2836 | maliciously
2837 | maliciousness
2838 | malign
2839 | malignant
2840 | malodorous
2841 | maltreatment
2842 | mangle
2843 | mangled
2844 | mangles
2845 | mangling
2846 | mania
2847 | maniac
2848 | maniacal
2849 | manic
2850 | manipulate
2851 | manipulation
2852 | manipulative
2853 | manipulators
2854 | mar
2855 | marginal
2856 | marginally
2857 | martyrdom
2858 | martyrdom-seeking
2859 | mashed
2860 | massacre
2861 | massacres
2862 | matte
2863 | mawkish
2864 | mawkishly
2865 | mawkishness
2866 | meager
2867 | meaningless
2868 | meanness
2869 | measly
2870 | meddle
2871 | meddlesome
2872 | mediocre
2873 | mediocrity
2874 | melancholy
2875 | melodramatic
2876 | melodramatically
2877 | meltdown
2878 | menace
2879 | menacing
2880 | menacingly
2881 | mendacious
2882 | mendacity
2883 | menial
2884 | merciless
2885 | mercilessly
2886 | mess
2887 | messed
2888 | messes
2889 | messing
2890 | messy
2891 | midget
2892 | miff
2893 | militancy
2894 | mindless
2895 | mindlessly
2896 | mirage
2897 | mire
2898 | misalign
2899 | misaligned
2900 | misaligns
2901 | misapprehend
2902 | misbecome
2903 | misbecoming
2904 | misbegotten
2905 | misbehave
2906 | misbehavior
2907 | miscalculate
2908 | miscalculation
2909 | miscellaneous
2910 | mischief
2911 | mischievous
2912 | mischievously
2913 | misconception
2914 | misconceptions
2915 | miscreant
2916 | miscreants
2917 | misdirection
2918 | miser
2919 | miserable
2920 | miserableness
2921 | miserably
2922 | miseries
2923 | miserly
2924 | misery
2925 | misfit
2926 | misfortune
2927 | misgiving
2928 | misgivings
2929 | misguidance
2930 | misguide
2931 | misguided
2932 | mishandle
2933 | mishap
2934 | misinform
2935 | misinformed
2936 | misinterpret
2937 | misjudge
2938 | misjudgment
2939 | mislead
2940 | misleading
2941 | misleadingly
2942 | mislike
2943 | mismanage
2944 | mispronounce
2945 | mispronounced
2946 | mispronounces
2947 | misread
2948 | misreading
2949 | misrepresent
2950 | misrepresentation
2951 | miss
2952 | missed
2953 | misses
2954 | misstatement
2955 | mist
2956 | mistake
2957 | mistaken
2958 | mistakenly
2959 | mistakes
2960 | mistified
2961 | mistress
2962 | mistrust
2963 | mistrustful
2964 | mistrustfully
2965 | mists
2966 | misunderstand
2967 | misunderstanding
2968 | misunderstandings
2969 | misunderstood
2970 | misuse
2971 | moan
2972 | mobster
2973 | mock
2974 | mocked
2975 | mockeries
2976 | mockery
2977 | mocking
2978 | mockingly
2979 | mocks
2980 | molest
2981 | molestation
2982 | monotonous
2983 | monotony
2984 | monster
2985 | monstrosities
2986 | monstrosity
2987 | monstrous
2988 | monstrously
2989 | moody
2990 | moot
2991 | mope
2992 | morbid
2993 | morbidly
2994 | mordant
2995 | mordantly
2996 | moribund
2997 | moron
2998 | moronic
2999 | morons
3000 | mortification
3001 | mortified
3002 | mortify
3003 | mortifying
3004 | motionless
3005 | motley
3006 | mourn
3007 | mourner
3008 | mournful
3009 | mournfully
3010 | muddle
3011 | muddy
3012 | mudslinger
3013 | mudslinging
3014 | mulish
3015 | multi-polarization
3016 | mundane
3017 | murder
3018 | murderer
3019 | murderous
3020 | murderously
3021 | murky
3022 | muscle-flexing
3023 | mushy
3024 | musty
3025 | mysterious
3026 | mysteriously
3027 | mystery
3028 | mystify
3029 | myth
3030 | nag
3031 | nagging
3032 | naive
3033 | naively
3034 | narrower
3035 | nastily
3036 | nastiness
3037 | nasty
3038 | naughty
3039 | nauseate
3040 | nauseates
3041 | nauseating
3042 | nauseatingly
3043 | naÔve
3044 | nebulous
3045 | nebulously
3046 | needless
3047 | needlessly
3048 | needy
3049 | nefarious
3050 | nefariously
3051 | negate
3052 | negation
3053 | negative
3054 | negatives
3055 | negativity
3056 | neglect
3057 | neglected
3058 | negligence
3059 | negligent
3060 | nemesis
3061 | nepotism
3062 | nervous
3063 | nervously
3064 | nervousness
3065 | nettle
3066 | nettlesome
3067 | neurotic
3068 | neurotically
3069 | niggle
3070 | niggles
3071 | nightmare
3072 | nightmarish
3073 | nightmarishly
3074 | nitpick
3075 | nitpicking
3076 | noise
3077 | noises
3078 | noisier
3079 | noisy
3080 | non-confidence
3081 | nonexistent
3082 | nonresponsive
3083 | nonsense
3084 | nosey
3085 | notoriety
3086 | notorious
3087 | notoriously
3088 | noxious
3089 | nuisance
3090 | numb
3091 | obese
3092 | object
3093 | objection
3094 | objectionable
3095 | objections
3096 | oblique
3097 | obliterate
3098 | obliterated
3099 | oblivious
3100 | obnoxious
3101 | obnoxiously
3102 | obscene
3103 | obscenely
3104 | obscenity
3105 | obscure
3106 | obscured
3107 | obscures
3108 | obscurity
3109 | obsess
3110 | obsessive
3111 | obsessively
3112 | obsessiveness
3113 | obsolete
3114 | obstacle
3115 | obstinate
3116 | obstinately
3117 | obstruct
3118 | obstructed
3119 | obstructing
3120 | obstruction
3121 | obstructs
3122 | obtrusive
3123 | obtuse
3124 | occlude
3125 | occluded
3126 | occludes
3127 | occluding
3128 | odd
3129 | odder
3130 | oddest
3131 | oddities
3132 | oddity
3133 | oddly
3134 | odor
3135 | offence
3136 | offend
3137 | offender
3138 | offending
3139 | offenses
3140 | offensive
3141 | offensively
3142 | offensiveness
3143 | officious
3144 | ominous
3145 | ominously
3146 | omission
3147 | omit
3148 | one-sided
3149 | onerous
3150 | onerously
3151 | onslaught
3152 | opinionated
3153 | opponent
3154 | opportunistic
3155 | oppose
3156 | opposition
3157 | oppositions
3158 | oppress
3159 | oppression
3160 | oppressive
3161 | oppressively
3162 | oppressiveness
3163 | oppressors
3164 | ordeal
3165 | orphan
3166 | ostracize
3167 | outbreak
3168 | outburst
3169 | outbursts
3170 | outcast
3171 | outcry
3172 | outlaw
3173 | outmoded
3174 | outrage
3175 | outraged
3176 | outrageous
3177 | outrageously
3178 | outrageousness
3179 | outrages
3180 | outsider
3181 | over-acted
3182 | over-awe
3183 | over-balanced
3184 | over-hyped
3185 | over-priced
3186 | over-valuation
3187 | overact
3188 | overacted
3189 | overawe
3190 | overbalance
3191 | overbalanced
3192 | overbearing
3193 | overbearingly
3194 | overblown
3195 | overdo
3196 | overdone
3197 | overdue
3198 | overemphasize
3199 | overheat
3200 | overkill
3201 | overloaded
3202 | overlook
3203 | overpaid
3204 | overpayed
3205 | overplay
3206 | overpower
3207 | overpriced
3208 | overrated
3209 | overreach
3210 | overrun
3211 | overshadow
3212 | oversight
3213 | oversights
3214 | oversimplification
3215 | oversimplified
3216 | oversimplify
3217 | oversize
3218 | overstate
3219 | overstated
3220 | overstatement
3221 | overstatements
3222 | overstates
3223 | overtaxed
3224 | overthrow
3225 | overthrows
3226 | overturn
3227 | overweight
3228 | overwhelm
3229 | overwhelmed
3230 | overwhelming
3231 | overwhelmingly
3232 | overwhelms
3233 | overzealous
3234 | overzealously
3235 | overzelous
3236 | pain
3237 | painful
3238 | painfull
3239 | painfully
3240 | pains
3241 | pale
3242 | pales
3243 | paltry
3244 | pan
3245 | pandemonium
3246 | pander
3247 | pandering
3248 | panders
3249 | panic
3250 | panick
3251 | panicked
3252 | panicking
3253 | panicky
3254 | paradoxical
3255 | paradoxically
3256 | paralize
3257 | paralyzed
3258 | paranoia
3259 | paranoid
3260 | parasite
3261 | pariah
3262 | parody
3263 | partiality
3264 | partisan
3265 | partisans
3266 | passe
3267 | passive
3268 | passiveness
3269 | pathetic
3270 | pathetically
3271 | patronize
3272 | paucity
3273 | pauper
3274 | paupers
3275 | payback
3276 | peculiar
3277 | peculiarly
3278 | pedantic
3279 | peeled
3280 | peeve
3281 | peeved
3282 | peevish
3283 | peevishly
3284 | penalize
3285 | penalty
3286 | perfidious
3287 | perfidity
3288 | perfunctory
3289 | peril
3290 | perilous
3291 | perilously
3292 | perish
3293 | pernicious
3294 | perplex
3295 | perplexed
3296 | perplexing
3297 | perplexity
3298 | persecute
3299 | persecution
3300 | pertinacious
3301 | pertinaciously
3302 | pertinacity
3303 | perturb
3304 | perturbed
3305 | pervasive
3306 | perverse
3307 | perversely
3308 | perversion
3309 | perversity
3310 | pervert
3311 | perverted
3312 | perverts
3313 | pessimism
3314 | pessimistic
3315 | pessimistically
3316 | pest
3317 | pestilent
3318 | petrified
3319 | petrify
3320 | pettifog
3321 | petty
3322 | phobia
3323 | phobic
3324 | phony
3325 | picket
3326 | picketed
3327 | picketing
3328 | pickets
3329 | picky
3330 | pig
3331 | pigs
3332 | pillage
3333 | pillory
3334 | pimple
3335 | pinch
3336 | pique
3337 | pitiable
3338 | pitiful
3339 | pitifully
3340 | pitiless
3341 | pitilessly
3342 | pittance
3343 | pity
3344 | plagiarize
3345 | plague
3346 | plasticky
3347 | plaything
3348 | plea
3349 | pleas
3350 | plebeian
3351 | plight
3352 | plot
3353 | plotters
3354 | ploy
3355 | plunder
3356 | plunderer
3357 | pointless
3358 | pointlessly
3359 | poison
3360 | poisonous
3361 | poisonously
3362 | pokey
3363 | poky
3364 | polarisation
3365 | polemize
3366 | pollute
3367 | polluter
3368 | polluters
3369 | polution
3370 | pompous
3371 | poor
3372 | poorer
3373 | poorest
3374 | poorly
3375 | posturing
3376 | pout
3377 | poverty
3378 | powerless
3379 | prate
3380 | pratfall
3381 | prattle
3382 | precarious
3383 | precariously
3384 | precipitate
3385 | precipitous
3386 | predatory
3387 | predicament
3388 | prejudge
3389 | prejudice
3390 | prejudices
3391 | prejudicial
3392 | premeditated
3393 | preoccupy
3394 | preposterous
3395 | preposterously
3396 | presumptuous
3397 | presumptuously
3398 | pretence
3399 | pretend
3400 | pretense
3401 | pretentious
3402 | pretentiously
3403 | prevaricate
3404 | pricey
3405 | pricier
3406 | prick
3407 | prickle
3408 | prickles
3409 | prideful
3410 | prik
3411 | primitive
3412 | prison
3413 | prisoner
3414 | problem
3415 | problematic
3416 | problems
3417 | procrastinate
3418 | procrastinates
3419 | procrastination
3420 | profane
3421 | profanity
3422 | prohibit
3423 | prohibitive
3424 | prohibitively
3425 | propaganda
3426 | propagandize
3427 | proprietary
3428 | prosecute
3429 | protest
3430 | protested
3431 | protesting
3432 | protests
3433 | protracted
3434 | provocation
3435 | provocative
3436 | provoke
3437 | pry
3438 | pugnacious
3439 | pugnaciously
3440 | pugnacity
3441 | punch
3442 | punish
3443 | punishable
3444 | punitive
3445 | punk
3446 | puny
3447 | puppet
3448 | puppets
3449 | puzzled
3450 | puzzlement
3451 | puzzling
3452 | quack
3453 | qualm
3454 | qualms
3455 | quandary
3456 | quarrel
3457 | quarrellous
3458 | quarrellously
3459 | quarrels
3460 | quarrelsome
3461 | quash
3462 | queer
3463 | questionable
3464 | quibble
3465 | quibbles
3466 | quitter
3467 | rabid
3468 | racism
3469 | racist
3470 | racists
3471 | racy
3472 | radical
3473 | radicalization
3474 | radically
3475 | radicals
3476 | rage
3477 | ragged
3478 | raging
3479 | rail
3480 | raked
3481 | rampage
3482 | rampant
3483 | ramshackle
3484 | rancor
3485 | randomly
3486 | rankle
3487 | rant
3488 | ranted
3489 | ranting
3490 | rantingly
3491 | rants
3492 | rape
3493 | raped
3494 | raping
3495 | rascal
3496 | rascals
3497 | rash
3498 | rattle
3499 | rattled
3500 | rattles
3501 | ravage
3502 | raving
3503 | reactionary
3504 | rebellious
3505 | rebuff
3506 | rebuke
3507 | recalcitrant
3508 | recant
3509 | recession
3510 | recessionary
3511 | reckless
3512 | recklessly
3513 | recklessness
3514 | recoil
3515 | recourses
3516 | redundancy
3517 | redundant
3518 | refusal
3519 | refuse
3520 | refused
3521 | refuses
3522 | refusing
3523 | refutation
3524 | refute
3525 | refuted
3526 | refutes
3527 | refuting
3528 | regress
3529 | regression
3530 | regressive
3531 | regret
3532 | regreted
3533 | regretful
3534 | regretfully
3535 | regrets
3536 | regrettable
3537 | regrettably
3538 | regretted
3539 | reject
3540 | rejected
3541 | rejecting
3542 | rejection
3543 | rejects
3544 | relapse
3545 | relentless
3546 | relentlessly
3547 | relentlessness
3548 | reluctance
3549 | reluctant
3550 | reluctantly
3551 | remorse
3552 | remorseful
3553 | remorsefully
3554 | remorseless
3555 | remorselessly
3556 | remorselessness
3557 | renounce
3558 | renunciation
3559 | repel
3560 | repetitive
3561 | reprehensible
3562 | reprehensibly
3563 | reprehension
3564 | reprehensive
3565 | repress
3566 | repression
3567 | repressive
3568 | reprimand
3569 | reproach
3570 | reproachful
3571 | reprove
3572 | reprovingly
3573 | repudiate
3574 | repudiation
3575 | repugn
3576 | repugnance
3577 | repugnant
3578 | repugnantly
3579 | repulse
3580 | repulsed
3581 | repulsing
3582 | repulsive
3583 | repulsively
3584 | repulsiveness
3585 | resent
3586 | resentful
3587 | resentment
3588 | resignation
3589 | resigned
3590 | resistance
3591 | restless
3592 | restlessness
3593 | restrict
3594 | restricted
3595 | restriction
3596 | restrictive
3597 | resurgent
3598 | retaliate
3599 | retaliatory
3600 | retard
3601 | retarded
3602 | retardedness
3603 | retards
3604 | reticent
3605 | retract
3606 | retreat
3607 | retreated
3608 | revenge
3609 | revengeful
3610 | revengefully
3611 | revert
3612 | revile
3613 | reviled
3614 | revoke
3615 | revolt
3616 | revolting
3617 | revoltingly
3618 | revulsion
3619 | revulsive
3620 | rhapsodize
3621 | rhetoric
3622 | rhetorical
3623 | ricer
3624 | ridicule
3625 | ridicules
3626 | ridiculous
3627 | ridiculously
3628 | rife
3629 | rift
3630 | rifts
3631 | rigid
3632 | rigidity
3633 | rigidness
3634 | rile
3635 | riled
3636 | rip
3637 | rip-off
3638 | ripoff
3639 | ripped
3640 | risk
3641 | risks
3642 | risky
3643 | rival
3644 | rivalry
3645 | roadblocks
3646 | rocky
3647 | rogue
3648 | rollercoaster
3649 | rot
3650 | rotten
3651 | rough
3652 | rremediable
3653 | rubbish
3654 | rude
3655 | rue
3656 | ruffian
3657 | ruffle
3658 | ruin
3659 | ruined
3660 | ruining
3661 | ruinous
3662 | ruins
3663 | rumbling
3664 | rumor
3665 | rumors
3666 | rumours
3667 | rumple
3668 | run-down
3669 | runaway
3670 | rupture
3671 | rust
3672 | rusts
3673 | rusty
3674 | rut
3675 | ruthless
3676 | ruthlessly
3677 | ruthlessness
3678 | ruts
3679 | sabotage
3680 | sack
3681 | sacrificed
3682 | sad
3683 | sadden
3684 | sadly
3685 | sadness
3686 | sag
3687 | sagged
3688 | sagging
3689 | saggy
3690 | sags
3691 | salacious
3692 | sanctimonious
3693 | sap
3694 | sarcasm
3695 | sarcastic
3696 | sarcastically
3697 | sardonic
3698 | sardonically
3699 | sass
3700 | satirical
3701 | satirize
3702 | savage
3703 | savaged
3704 | savagery
3705 | savages
3706 | scaly
3707 | scam
3708 | scams
3709 | scandal
3710 | scandalize
3711 | scandalized
3712 | scandalous
3713 | scandalously
3714 | scandals
3715 | scandel
3716 | scandels
3717 | scant
3718 | scapegoat
3719 | scar
3720 | scarce
3721 | scarcely
3722 | scarcity
3723 | scare
3724 | scared
3725 | scarier
3726 | scariest
3727 | scarily
3728 | scarred
3729 | scars
3730 | scary
3731 | scathing
3732 | scathingly
3733 | sceptical
3734 | scoff
3735 | scoffingly
3736 | scold
3737 | scolded
3738 | scolding
3739 | scoldingly
3740 | scorching
3741 | scorchingly
3742 | scorn
3743 | scornful
3744 | scornfully
3745 | scoundrel
3746 | scourge
3747 | scowl
3748 | scramble
3749 | scrambled
3750 | scrambles
3751 | scrambling
3752 | scrap
3753 | scratch
3754 | scratched
3755 | scratches
3756 | scratchy
3757 | scream
3758 | screech
3759 | screw-up
3760 | screwed
3761 | screwed-up
3762 | screwy
3763 | scuff
3764 | scuffs
3765 | scum
3766 | scummy
3767 | second-class
3768 | second-tier
3769 | secretive
3770 | sedentary
3771 | seedy
3772 | seethe
3773 | seething
3774 | self-coup
3775 | self-criticism
3776 | self-defeating
3777 | self-destructive
3778 | self-humiliation
3779 | self-interest
3780 | self-interested
3781 | self-serving
3782 | selfinterested
3783 | selfish
3784 | selfishly
3785 | selfishness
3786 | semi-retarded
3787 | senile
3788 | sensationalize
3789 | senseless
3790 | senselessly
3791 | seriousness
3792 | sermonize
3793 | servitude
3794 | set-up
3795 | setback
3796 | setbacks
3797 | sever
3798 | severe
3799 | severity
3800 | sh*t
3801 | shabby
3802 | shadowy
3803 | shady
3804 | shake
3805 | shaky
3806 | shallow
3807 | sham
3808 | shambles
3809 | shame
3810 | shameful
3811 | shamefully
3812 | shamefulness
3813 | shameless
3814 | shamelessly
3815 | shamelessness
3816 | shark
3817 | sharply
3818 | shatter
3819 | shemale
3820 | shimmer
3821 | shimmy
3822 | shipwreck
3823 | shirk
3824 | shirker
3825 | shit
3826 | shiver
3827 | shock
3828 | shocked
3829 | shocking
3830 | shockingly
3831 | shoddy
3832 | short-lived
3833 | shortage
3834 | shortchange
3835 | shortcoming
3836 | shortcomings
3837 | shortness
3838 | shortsighted
3839 | shortsightedness
3840 | showdown
3841 | shrew
3842 | shriek
3843 | shrill
3844 | shrilly
3845 | shrivel
3846 | shroud
3847 | shrouded
3848 | shrug
3849 | shun
3850 | shunned
3851 | sick
3852 | sicken
3853 | sickening
3854 | sickeningly
3855 | sickly
3856 | sickness
3857 | sidetrack
3858 | sidetracked
3859 | siege
3860 | sillily
3861 | silly
3862 | simplistic
3863 | simplistically
3864 | sin
3865 | sinful
3866 | sinfully
3867 | sinister
3868 | sinisterly
3869 | sink
3870 | sinking
3871 | skeletons
3872 | skeptic
3873 | skeptical
3874 | skeptically
3875 | skepticism
3876 | sketchy
3877 | skimpy
3878 | skinny
3879 | skittish
3880 | skittishly
3881 | skulk
3882 | slack
3883 | slander
3884 | slanderer
3885 | slanderous
3886 | slanderously
3887 | slanders
3888 | slap
3889 | slashing
3890 | slaughter
3891 | slaughtered
3892 | slave
3893 | slaves
3894 | sleazy
3895 | slime
3896 | slog
3897 | slogged
3898 | slogging
3899 | slogs
3900 | sloooooooooooooow
3901 | sloooow
3902 | slooow
3903 | sloow
3904 | sloppily
3905 | sloppy
3906 | sloth
3907 | slothful
3908 | slow
3909 | slow-moving
3910 | slowed
3911 | slower
3912 | slowest
3913 | slowly
3914 | sloww
3915 | slowww
3916 | slowwww
3917 | slug
3918 | sluggish
3919 | slump
3920 | slumping
3921 | slumpping
3922 | slur
3923 | slut
3924 | sluts
3925 | sly
3926 | smack
3927 | smallish
3928 | smash
3929 | smear
3930 | smell
3931 | smelled
3932 | smelling
3933 | smells
3934 | smelly
3935 | smelt
3936 | smoke
3937 | smokescreen
3938 | smolder
3939 | smoldering
3940 | smother
3941 | smoulder
3942 | smouldering
3943 | smudge
3944 | smudged
3945 | smudges
3946 | smudging
3947 | smug
3948 | smugly
3949 | smut
3950 | smuttier
3951 | smuttiest
3952 | smutty
3953 | snag
3954 | snagged
3955 | snagging
3956 | snags
3957 | snappish
3958 | snappishly
3959 | snare
3960 | snarky
3961 | snarl
3962 | sneak
3963 | sneakily
3964 | sneaky
3965 | sneer
3966 | sneering
3967 | sneeringly
3968 | snob
3969 | snobbish
3970 | snobby
3971 | snobish
3972 | snobs
3973 | snub
3974 | so-cal
3975 | soapy
3976 | sob
3977 | sober
3978 | sobering
3979 | solemn
3980 | solicitude
3981 | somber
3982 | sore
3983 | sorely
3984 | soreness
3985 | sorrow
3986 | sorrowful
3987 | sorrowfully
3988 | sorry
3989 | sour
3990 | sourly
3991 | spade
3992 | spank
3993 | spendy
3994 | spew
3995 | spewed
3996 | spewing
3997 | spews
3998 | spilling
3999 | spinster
4000 | spiritless
4001 | spite
4002 | spiteful
4003 | spitefully
4004 | spitefulness
4005 | splatter
4006 | split
4007 | splitting
4008 | spoil
4009 | spoilage
4010 | spoilages
4011 | spoiled
4012 | spoilled
4013 | spoils
4014 | spook
4015 | spookier
4016 | spookiest
4017 | spookily
4018 | spooky
4019 | spoon-fed
4020 | spoon-feed
4021 | spoonfed
4022 | sporadic
4023 | spotty
4024 | spurious
4025 | spurn
4026 | sputter
4027 | squabble
4028 | squabbling
4029 | squander
4030 | squash
4031 | squeak
4032 | squeaks
4033 | squeaky
4034 | squeal
4035 | squealing
4036 | squeals
4037 | squirm
4038 | stab
4039 | stagnant
4040 | stagnate
4041 | stagnation
4042 | staid
4043 | stain
4044 | stains
4045 | stale
4046 | stalemate
4047 | stall
4048 | stalls
4049 | stammer
4050 | stampede
4051 | standstill
4052 | stark
4053 | starkly
4054 | startle
4055 | startling
4056 | startlingly
4057 | starvation
4058 | starve
4059 | static
4060 | steal
4061 | stealing
4062 | steals
4063 | steep
4064 | steeply
4065 | stench
4066 | stereotype
4067 | stereotypical
4068 | stereotypically
4069 | stern
4070 | stew
4071 | sticky
4072 | stiff
4073 | stiffness
4074 | stifle
4075 | stifling
4076 | stiflingly
4077 | stigma
4078 | stigmatize
4079 | sting
4080 | stinging
4081 | stingingly
4082 | stingy
4083 | stink
4084 | stinks
4085 | stodgy
4086 | stole
4087 | stolen
4088 | stooge
4089 | stooges
4090 | stormy
4091 | straggle
4092 | straggler
4093 | strain
4094 | strained
4095 | straining
4096 | strange
4097 | strangely
4098 | stranger
4099 | strangest
4100 | strangle
4101 | streaky
4102 | strenuous
4103 | stress
4104 | stresses
4105 | stressful
4106 | stressfully
4107 | stricken
4108 | strict
4109 | strictly
4110 | strident
4111 | stridently
4112 | strife
4113 | strike
4114 | stringent
4115 | stringently
4116 | struck
4117 | struggle
4118 | struggled
4119 | struggles
4120 | struggling
4121 | strut
4122 | stubborn
4123 | stubbornly
4124 | stubbornness
4125 | stuck
4126 | stuffy
4127 | stumble
4128 | stumbled
4129 | stumbles
4130 | stump
4131 | stumped
4132 | stumps
4133 | stun
4134 | stunt
4135 | stunted
4136 | stupid
4137 | stupidest
4138 | stupidity
4139 | stupidly
4140 | stupified
4141 | stupify
4142 | stupor
4143 | stutter
4144 | stuttered
4145 | stuttering
4146 | stutters
4147 | sty
4148 | stymied
4149 | sub-par
4150 | subdued
4151 | subjected
4152 | subjection
4153 | subjugate
4154 | subjugation
4155 | submissive
4156 | subordinate
4157 | subpoena
4158 | subpoenas
4159 | subservience
4160 | subservient
4161 | substandard
4162 | subtract
4163 | subversion
4164 | subversive
4165 | subversively
4166 | subvert
4167 | succumb
4168 | suck
4169 | sucked
4170 | sucker
4171 | sucks
4172 | sucky
4173 | sue
4174 | sued
4175 | sueing
4176 | sues
4177 | suffer
4178 | suffered
4179 | sufferer
4180 | sufferers
4181 | suffering
4182 | suffers
4183 | suffocate
4184 | sugar-coat
4185 | sugar-coated
4186 | sugarcoated
4187 | suicidal
4188 | suicide
4189 | sulk
4190 | sullen
4191 | sully
4192 | sunder
4193 | sunk
4194 | sunken
4195 | superficial
4196 | superficiality
4197 | superficially
4198 | superfluous
4199 | superstition
4200 | superstitious
4201 | suppress
4202 | suppression
4203 | surrender
4204 | susceptible
4205 | suspect
4206 | suspicion
4207 | suspicions
4208 | suspicious
4209 | suspiciously
4210 | swagger
4211 | swamped
4212 | sweaty
4213 | swelled
4214 | swelling
4215 | swindle
4216 | swipe
4217 | swollen
4218 | symptom
4219 | symptoms
4220 | syndrome
4221 | taboo
4222 | tacky
4223 | taint
4224 | tainted
4225 | tamper
4226 | tangle
4227 | tangled
4228 | tangles
4229 | tank
4230 | tanked
4231 | tanks
4232 | tantrum
4233 | tardy
4234 | tarnish
4235 | tarnished
4236 | tarnishes
4237 | tarnishing
4238 | tattered
4239 | taunt
4240 | taunting
4241 | tauntingly
4242 | taunts
4243 | taut
4244 | tawdry
4245 | taxing
4246 | tease
4247 | teasingly
4248 | tedious
4249 | tediously
4250 | temerity
4251 | temper
4252 | tempest
4253 | temptation
4254 | tenderness
4255 | tense
4256 | tension
4257 | tentative
4258 | tentatively
4259 | tenuous
4260 | tenuously
4261 | tepid
4262 | terrible
4263 | terribleness
4264 | terribly
4265 | terror
4266 | terror-genic
4267 | terrorism
4268 | terrorize
4269 | testily
4270 | testy
4271 | tetchily
4272 | tetchy
4273 | thankless
4274 | thicker
4275 | thirst
4276 | thorny
4277 | thoughtless
4278 | thoughtlessly
4279 | thoughtlessness
4280 | thrash
4281 | threat
4282 | threaten
4283 | threatening
4284 | threats
4285 | threesome
4286 | throb
4287 | throbbed
4288 | throbbing
4289 | throbs
4290 | throttle
4291 | thug
4292 | thumb-down
4293 | thumbs-down
4294 | thwart
4295 | time-consuming
4296 | timid
4297 | timidity
4298 | timidly
4299 | timidness
4300 | tin-y
4301 | tingled
4302 | tingling
4303 | tired
4304 | tiresome
4305 | tiring
4306 | tiringly
4307 | toil
4308 | toll
4309 | top-heavy
4310 | topple
4311 | torment
4312 | tormented
4313 | torrent
4314 | tortuous
4315 | torture
4316 | tortured
4317 | tortures
4318 | torturing
4319 | torturous
4320 | torturously
4321 | totalitarian
4322 | touchy
4323 | toughness
4324 | tout
4325 | touted
4326 | touts
4327 | toxic
4328 | traduce
4329 | tragedy
4330 | tragic
4331 | tragically
4332 | traitor
4333 | traitorous
4334 | traitorously
4335 | tramp
4336 | trample
4337 | transgress
4338 | transgression
4339 | trap
4340 | traped
4341 | trapped
4342 | trash
4343 | trashed
4344 | trashy
4345 | trauma
4346 | traumatic
4347 | traumatically
4348 | traumatize
4349 | traumatized
4350 | travesties
4351 | travesty
4352 | treacherous
4353 | treacherously
4354 | treachery
4355 | treason
4356 | treasonous
4357 | trick
4358 | tricked
4359 | trickery
4360 | tricky
4361 | trivial
4362 | trivialize
4363 | trouble
4364 | troubled
4365 | troublemaker
4366 | troubles
4367 | troublesome
4368 | troublesomely
4369 | troubling
4370 | troublingly
4371 | truant
4372 | tumble
4373 | tumbled
4374 | tumbles
4375 | tumultuous
4376 | turbulent
4377 | turmoil
4378 | twist
4379 | twisted
4380 | twists
4381 | two-faced
4382 | two-faces
4383 | tyrannical
4384 | tyrannically
4385 | tyranny
4386 | tyrant
4387 | ugh
4388 | uglier
4389 | ugliest
4390 | ugliness
4391 | ugly
4392 | ulterior
4393 | ultimatum
4394 | ultimatums
4395 | ultra-hardline
4396 | un-viewable
4397 | unable
4398 | unacceptable
4399 | unacceptablely
4400 | unacceptably
4401 | unaccessible
4402 | unaccustomed
4403 | unachievable
4404 | unaffordable
4405 | unappealing
4406 | unattractive
4407 | unauthentic
4408 | unavailable
4409 | unavoidably
4410 | unbearable
4411 | unbearablely
4412 | unbelievable
4413 | unbelievably
4414 | uncaring
4415 | uncertain
4416 | uncivil
4417 | uncivilized
4418 | unclean
4419 | unclear
4420 | uncollectible
4421 | uncomfortable
4422 | uncomfortably
4423 | uncomfy
4424 | uncompetitive
4425 | uncompromising
4426 | uncompromisingly
4427 | unconfirmed
4428 | unconstitutional
4429 | uncontrolled
4430 | unconvincing
4431 | unconvincingly
4432 | uncooperative
4433 | uncouth
4434 | uncreative
4435 | undecided
4436 | undefined
4437 | undependability
4438 | undependable
4439 | undercut
4440 | undercuts
4441 | undercutting
4442 | underdog
4443 | underestimate
4444 | underlings
4445 | undermine
4446 | undermined
4447 | undermines
4448 | undermining
4449 | underpaid
4450 | underpowered
4451 | undersized
4452 | undesirable
4453 | undetermined
4454 | undid
4455 | undignified
4456 | undissolved
4457 | undocumented
4458 | undone
4459 | undue
4460 | unease
4461 | uneasily
4462 | uneasiness
4463 | uneasy
4464 | uneconomical
4465 | unemployed
4466 | unequal
4467 | unethical
4468 | uneven
4469 | uneventful
4470 | unexpected
4471 | unexpectedly
4472 | unexplained
4473 | unfairly
4474 | unfaithful
4475 | unfaithfully
4476 | unfamiliar
4477 | unfavorable
4478 | unfeeling
4479 | unfinished
4480 | unfit
4481 | unforeseen
4482 | unforgiving
4483 | unfortunate
4484 | unfortunately
4485 | unfounded
4486 | unfriendly
4487 | unfulfilled
4488 | unfunded
4489 | ungovernable
4490 | ungrateful
4491 | unhappily
4492 | unhappiness
4493 | unhappy
4494 | unhealthy
4495 | unhelpful
4496 | unilateralism
4497 | unimaginable
4498 | unimaginably
4499 | unimportant
4500 | uninformed
4501 | uninsured
4502 | unintelligible
4503 | unintelligile
4504 | unipolar
4505 | unjust
4506 | unjustifiable
4507 | unjustifiably
4508 | unjustified
4509 | unjustly
4510 | unkind
4511 | unkindly
4512 | unknown
4513 | unlamentable
4514 | unlamentably
4515 | unlawful
4516 | unlawfully
4517 | unlawfulness
4518 | unleash
4519 | unlicensed
4520 | unlikely
4521 | unlucky
4522 | unmoved
4523 | unnatural
4524 | unnaturally
4525 | unnecessary
4526 | unneeded
4527 | unnerve
4528 | unnerved
4529 | unnerving
4530 | unnervingly
4531 | unnoticed
4532 | unobserved
4533 | unorthodox
4534 | unorthodoxy
4535 | unpleasant
4536 | unpleasantries
4537 | unpopular
4538 | unpredictable
4539 | unprepared
4540 | unproductive
4541 | unprofitable
4542 | unprove
4543 | unproved
4544 | unproven
4545 | unproves
4546 | unproving
4547 | unqualified
4548 | unravel
4549 | unraveled
4550 | unreachable
4551 | unreadable
4552 | unrealistic
4553 | unreasonable
4554 | unreasonably
4555 | unrelenting
4556 | unrelentingly
4557 | unreliability
4558 | unreliable
4559 | unresolved
4560 | unresponsive
4561 | unrest
4562 | unruly
4563 | unsafe
4564 | unsatisfactory
4565 | unsavory
4566 | unscrupulous
4567 | unscrupulously
4568 | unsecure
4569 | unseemly
4570 | unsettle
4571 | unsettled
4572 | unsettling
4573 | unsettlingly
4574 | unskilled
4575 | unsophisticated
4576 | unsound
4577 | unspeakable
4578 | unspeakablely
4579 | unspecified
4580 | unstable
4581 | unsteadily
4582 | unsteadiness
4583 | unsteady
4584 | unsuccessful
4585 | unsuccessfully
4586 | unsupported
4587 | unsupportive
4588 | unsure
4589 | unsuspecting
4590 | unsustainable
4591 | untenable
4592 | untested
4593 | unthinkable
4594 | unthinkably
4595 | untimely
4596 | untouched
4597 | untrue
4598 | untrustworthy
4599 | untruthful
4600 | unusable
4601 | unusably
4602 | unuseable
4603 | unuseably
4604 | unusual
4605 | unusually
4606 | unviewable
4607 | unwanted
4608 | unwarranted
4609 | unwatchable
4610 | unwelcome
4611 | unwell
4612 | unwieldy
4613 | unwilling
4614 | unwillingly
4615 | unwillingness
4616 | unwise
4617 | unwisely
4618 | unworkable
4619 | unworthy
4620 | unyielding
4621 | upbraid
4622 | upheaval
4623 | uprising
4624 | uproar
4625 | uproarious
4626 | uproariously
4627 | uproarous
4628 | uproarously
4629 | uproot
4630 | upset
4631 | upseting
4632 | upsets
4633 | upsetting
4634 | upsettingly
4635 | urgent
4636 | useless
4637 | usurp
4638 | usurper
4639 | utterly
4640 | vagrant
4641 | vague
4642 | vagueness
4643 | vain
4644 | vainly
4645 | vanity
4646 | vehement
4647 | vehemently
4648 | vengeance
4649 | vengeful
4650 | vengefully
4651 | vengefulness
4652 | venom
4653 | venomous
4654 | venomously
4655 | vent
4656 | vestiges
4657 | vex
4658 | vexation
4659 | vexing
4660 | vexingly
4661 | vibrate
4662 | vibrated
4663 | vibrates
4664 | vibrating
4665 | vibration
4666 | vice
4667 | vicious
4668 | viciously
4669 | viciousness
4670 | victimize
4671 | vile
4672 | vileness
4673 | vilify
4674 | villainous
4675 | villainously
4676 | villains
4677 | villian
4678 | villianous
4679 | villianously
4680 | villify
4681 | vindictive
4682 | vindictively
4683 | vindictiveness
4684 | violate
4685 | violation
4686 | violator
4687 | violators
4688 | violent
4689 | violently
4690 | viper
4691 | virulence
4692 | virulent
4693 | virulently
4694 | virus
4695 | vociferous
4696 | vociferously
4697 | volatile
4698 | volatility
4699 | vomit
4700 | vomited
4701 | vomiting
4702 | vomits
4703 | vulgar
4704 | vulnerable
4705 | wack
4706 | wail
4707 | wallow
4708 | wane
4709 | waning
4710 | wanton
4711 | war-like
4712 | warily
4713 | wariness
4714 | warlike
4715 | warned
4716 | warning
4717 | warp
4718 | warped
4719 | wary
4720 | washed-out
4721 | waste
4722 | wasted
4723 | wasteful
4724 | wastefulness
4725 | wasting
4726 | water-down
4727 | watered-down
4728 | wayward
4729 | weak
4730 | weaken
4731 | weakening
4732 | weaker
4733 | weakness
4734 | weaknesses
4735 | weariness
4736 | wearisome
4737 | weary
4738 | wedge
4739 | weed
4740 | weep
4741 | weird
4742 | weirdly
4743 | wheedle
4744 | whimper
4745 | whine
4746 | whining
4747 | whiny
4748 | whips
4749 | whore
4750 | whores
4751 | wicked
4752 | wickedly
4753 | wickedness
4754 | wild
4755 | wildly
4756 | wiles
4757 | wilt
4758 | wily
4759 | wimpy
4760 | wince
4761 | wobble
4762 | wobbled
4763 | wobbles
4764 | woe
4765 | woebegone
4766 | woeful
4767 | woefully
4768 | womanizer
4769 | womanizing
4770 | worn
4771 | worried
4772 | worriedly
4773 | worrier
4774 | worries
4775 | worrisome
4776 | worry
4777 | worrying
4778 | worryingly
4779 | worse
4780 | worsen
4781 | worsening
4782 | worst
4783 | worthless
4784 | worthlessly
4785 | worthlessness
4786 | wound
4787 | wounds
4788 | wrangle
4789 | wrath
4790 | wreak
4791 | wreaked
4792 | wreaks
4793 | wreck
4794 | wrest
4795 | wrestle
4796 | wretch
4797 | wretched
4798 | wretchedly
4799 | wretchedness
4800 | wrinkle
4801 | wrinkled
4802 | wrinkles
4803 | wrip
4804 | wripped
4805 | wripping
4806 | writhe
4807 | wrong
4808 | wrongful
4809 | wrongly
4810 | wrought
4811 | yawn
4812 | zap
4813 | zapped
4814 | zaps
4815 | zealot
4816 | zealous
4817 | zealously
4818 | zombie
4819 | 


--------------------------------------------------------------------------------
/data/nltk_stopwords.txt:
--------------------------------------------------------------------------------
  1 | i
  2 | me
  3 | my
  4 | myself
  5 | we
  6 | our
  7 | ours
  8 | ourselves
  9 | you
 10 | you're
 11 | you've
 12 | you'll
 13 | you'd
 14 | your
 15 | yours
 16 | yourself
 17 | yourselves
 18 | he
 19 | him
 20 | his
 21 | himself
 22 | she
 23 | she's
 24 | her
 25 | hers
 26 | herself
 27 | it
 28 | it's
 29 | its
 30 | itself
 31 | they
 32 | them
 33 | their
 34 | theirs
 35 | themselves
 36 | what
 37 | which
 38 | who
 39 | whom
 40 | this
 41 | that
 42 | that'll
 43 | these
 44 | those
 45 | am
 46 | is
 47 | are
 48 | was
 49 | were
 50 | be
 51 | been
 52 | being
 53 | have
 54 | has
 55 | had
 56 | having
 57 | do
 58 | does
 59 | did
 60 | doing
 61 | a
 62 | an
 63 | the
 64 | and
 65 | but
 66 | if
 67 | or
 68 | because
 69 | as
 70 | until
 71 | while
 72 | of
 73 | at
 74 | by
 75 | for
 76 | with
 77 | about
 78 | against
 79 | between
 80 | into
 81 | through
 82 | during
 83 | before
 84 | after
 85 | above
 86 | below
 87 | to
 88 | from
 89 | up
 90 | down
 91 | in
 92 | out
 93 | on
 94 | off
 95 | over
 96 | under
 97 | again
 98 | further
 99 | then
100 | once
101 | here
102 | there
103 | when
104 | where
105 | why
106 | how
107 | all
108 | any
109 | both
110 | each
111 | few
112 | more
113 | most
114 | other
115 | some
116 | such
117 | no
118 | nor
119 | not
120 | only
121 | own
122 | same
123 | so
124 | than
125 | too
126 | very
127 | s
128 | t
129 | can
130 | will
131 | just
132 | don
133 | don't
134 | should
135 | should've
136 | now
137 | d
138 | ll
139 | m
140 | o
141 | re
142 | ve
143 | y
144 | ain
145 | aren
146 | aren't
147 | couldn
148 | couldn't
149 | didn
150 | didn't
151 | doesn
152 | doesn't
153 | hadn
154 | hadn't
155 | hasn
156 | hasn't
157 | haven
158 | haven't
159 | isn
160 | isn't
161 | ma
162 | mightn
163 | mightn't
164 | mustn
165 | mustn't
166 | needn
167 | needn't
168 | shan
169 | shan't
170 | shouldn
171 | shouldn't
172 | wasn
173 | wasn't
174 | weren
175 | weren't
176 | won
177 | won't
178 | wouldn
179 | wouldn't
180 | 


--------------------------------------------------------------------------------
/data/polyglot-en.pkl:
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https://raw.githubusercontent.com/DataForScience/NLP/849b1ab04336336035eaa2a09b482142fa9c12d3/data/polyglot-en.pkl


--------------------------------------------------------------------------------
/data/positive-words.txt:
--------------------------------------------------------------------------------
   1 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
   2 | ; 
   3 | ; Opinion Lexicon: Positive
   4 | ;
   5 | ; This file contains a list of POSITIVE opinion words (or sentiment words).
   6 | ;
   7 | ; This file and the papers can all be downloaded from 
   8 | ;    http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html
   9 | ;
  10 | ; If you use this list, please cite one of the following two papers:
  11 | ;
  12 | ;   Minqing Hu and Bing Liu. "Mining and Summarizing Customer Reviews." 
  13 | ;       Proceedings of the ACM SIGKDD International Conference on Knowledge 
  14 | ;       Discovery and Data Mining (KDD-2004), Aug 22-25, 2004, Seattle, 
  15 | ;       Washington, USA, 
  16 | ;   Bing Liu, Minqing Hu and Junsheng Cheng. "Opinion Observer: Analyzing 
  17 | ;       and Comparing Opinions on the Web." Proceedings of the 14th 
  18 | ;       International World Wide Web conference (WWW-2005), May 10-14, 
  19 | ;       2005, Chiba, Japan.
  20 | ;
  21 | ; Notes: 
  22 | ;    1. The appearance of an opinion word in a sentence does not necessarily  
  23 | ;       mean that the sentence expresses a positive or negative opinion. 
  24 | ;       See the paper below:
  25 | ;
  26 | ;       Bing Liu. "Sentiment Analysis and Subjectivity." An chapter in 
  27 | ;          Handbook of Natural Language Processing, Second Edition, 
  28 | ;          (editors: N. Indurkhya and F. J. Damerau), 2010.
  29 | ;
  30 | ;    2. You will notice many misspelled words in the list. They are not 
  31 | ;       mistakes. They are included as these misspelled words appear 
  32 | ;       frequently in social media content. 
  33 | ;
  34 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
  35 | 
  36 | a+
  37 | abound
  38 | abounds
  39 | abundance
  40 | abundant
  41 | accessable
  42 | accessible
  43 | acclaim
  44 | acclaimed
  45 | acclamation
  46 | accolade
  47 | accolades
  48 | accommodative
  49 | accomodative
  50 | accomplish
  51 | accomplished
  52 | accomplishment
  53 | accomplishments
  54 | accurate
  55 | accurately
  56 | achievable
  57 | achievement
  58 | achievements
  59 | achievible
  60 | acumen
  61 | adaptable
  62 | adaptive
  63 | adequate
  64 | adjustable
  65 | admirable
  66 | admirably
  67 | admiration
  68 | admire
  69 | admirer
  70 | admiring
  71 | admiringly
  72 | adorable
  73 | adore
  74 | adored
  75 | adorer
  76 | adoring
  77 | adoringly
  78 | adroit
  79 | adroitly
  80 | adulate
  81 | adulation
  82 | adulatory
  83 | advanced
  84 | advantage
  85 | advantageous
  86 | advantageously
  87 | advantages
  88 | adventuresome
  89 | adventurous
  90 | advocate
  91 | advocated
  92 | advocates
  93 | affability
  94 | affable
  95 | affably
  96 | affectation
  97 | affection
  98 | affectionate
  99 | affinity
 100 | affirm
 101 | affirmation
 102 | affirmative
 103 | affluence
 104 | affluent
 105 | afford
 106 | affordable
 107 | affordably
 108 | afordable
 109 | agile
 110 | agilely
 111 | agility
 112 | agreeable
 113 | agreeableness
 114 | agreeably
 115 | all-around
 116 | alluring
 117 | alluringly
 118 | altruistic
 119 | altruistically
 120 | amaze
 121 | amazed
 122 | amazement
 123 | amazes
 124 | amazing
 125 | amazingly
 126 | ambitious
 127 | ambitiously
 128 | ameliorate
 129 | amenable
 130 | amenity
 131 | amiability
 132 | amiabily
 133 | amiable
 134 | amicability
 135 | amicable
 136 | amicably
 137 | amity
 138 | ample
 139 | amply
 140 | amuse
 141 | amusing
 142 | amusingly
 143 | angel
 144 | angelic
 145 | apotheosis
 146 | appeal
 147 | appealing
 148 | applaud
 149 | appreciable
 150 | appreciate
 151 | appreciated
 152 | appreciates
 153 | appreciative
 154 | appreciatively
 155 | appropriate
 156 | approval
 157 | approve
 158 | ardent
 159 | ardently
 160 | ardor
 161 | articulate
 162 | aspiration
 163 | aspirations
 164 | aspire
 165 | assurance
 166 | assurances
 167 | assure
 168 | assuredly
 169 | assuring
 170 | astonish
 171 | astonished
 172 | astonishing
 173 | astonishingly
 174 | astonishment
 175 | astound
 176 | astounded
 177 | astounding
 178 | astoundingly
 179 | astutely
 180 | attentive
 181 | attraction
 182 | attractive
 183 | attractively
 184 | attune
 185 | audible
 186 | audibly
 187 | auspicious
 188 | authentic
 189 | authoritative
 190 | autonomous
 191 | available
 192 | aver
 193 | avid
 194 | avidly
 195 | award
 196 | awarded
 197 | awards
 198 | awe
 199 | awed
 200 | awesome
 201 | awesomely
 202 | awesomeness
 203 | awestruck
 204 | awsome
 205 | backbone
 206 | balanced
 207 | bargain
 208 | beauteous
 209 | beautiful
 210 | beautifullly
 211 | beautifully
 212 | beautify
 213 | beauty
 214 | beckon
 215 | beckoned
 216 | beckoning
 217 | beckons
 218 | believable
 219 | believeable
 220 | beloved
 221 | benefactor
 222 | beneficent
 223 | beneficial
 224 | beneficially
 225 | beneficiary
 226 | benefit
 227 | benefits
 228 | benevolence
 229 | benevolent
 230 | benifits
 231 | best
 232 | best-known
 233 | best-performing
 234 | best-selling
 235 | better
 236 | better-known
 237 | better-than-expected
 238 | beutifully
 239 | blameless
 240 | bless
 241 | blessing
 242 | bliss
 243 | blissful
 244 | blissfully
 245 | blithe
 246 | blockbuster
 247 | bloom
 248 | blossom
 249 | bolster
 250 | bonny
 251 | bonus
 252 | bonuses
 253 | boom
 254 | booming
 255 | boost
 256 | boundless
 257 | bountiful
 258 | brainiest
 259 | brainy
 260 | brand-new
 261 | brave
 262 | bravery
 263 | bravo
 264 | breakthrough
 265 | breakthroughs
 266 | breathlessness
 267 | breathtaking
 268 | breathtakingly
 269 | breeze
 270 | bright
 271 | brighten
 272 | brighter
 273 | brightest
 274 | brilliance
 275 | brilliances
 276 | brilliant
 277 | brilliantly
 278 | brisk
 279 | brotherly
 280 | bullish
 281 | buoyant
 282 | cajole
 283 | calm
 284 | calming
 285 | calmness
 286 | capability
 287 | capable
 288 | capably
 289 | captivate
 290 | captivating
 291 | carefree
 292 | cashback
 293 | cashbacks
 294 | catchy
 295 | celebrate
 296 | celebrated
 297 | celebration
 298 | celebratory
 299 | champ
 300 | champion
 301 | charisma
 302 | charismatic
 303 | charitable
 304 | charm
 305 | charming
 306 | charmingly
 307 | chaste
 308 | cheaper
 309 | cheapest
 310 | cheer
 311 | cheerful
 312 | cheery
 313 | cherish
 314 | cherished
 315 | cherub
 316 | chic
 317 | chivalrous
 318 | chivalry
 319 | civility
 320 | civilize
 321 | clarity
 322 | classic
 323 | classy
 324 | clean
 325 | cleaner
 326 | cleanest
 327 | cleanliness
 328 | cleanly
 329 | clear
 330 | clear-cut
 331 | cleared
 332 | clearer
 333 | clearly
 334 | clears
 335 | clever
 336 | cleverly
 337 | cohere
 338 | coherence
 339 | coherent
 340 | cohesive
 341 | colorful
 342 | comely
 343 | comfort
 344 | comfortable
 345 | comfortably
 346 | comforting
 347 | comfy
 348 | commend
 349 | commendable
 350 | commendably
 351 | commitment
 352 | commodious
 353 | compact
 354 | compactly
 355 | compassion
 356 | compassionate
 357 | compatible
 358 | competitive
 359 | complement
 360 | complementary
 361 | complemented
 362 | complements
 363 | compliant
 364 | compliment
 365 | complimentary
 366 | comprehensive
 367 | conciliate
 368 | conciliatory
 369 | concise
 370 | confidence
 371 | confident
 372 | congenial
 373 | congratulate
 374 | congratulation
 375 | congratulations
 376 | congratulatory
 377 | conscientious
 378 | considerate
 379 | consistent
 380 | consistently
 381 | constructive
 382 | consummate
 383 | contentment
 384 | continuity
 385 | contrasty
 386 | contribution
 387 | convenience
 388 | convenient
 389 | conveniently
 390 | convience
 391 | convienient
 392 | convient
 393 | convincing
 394 | convincingly
 395 | cool
 396 | coolest
 397 | cooperative
 398 | cooperatively
 399 | cornerstone
 400 | correct
 401 | correctly
 402 | cost-effective
 403 | cost-saving
 404 | counter-attack
 405 | counter-attacks
 406 | courage
 407 | courageous
 408 | courageously
 409 | courageousness
 410 | courteous
 411 | courtly
 412 | covenant
 413 | cozy
 414 | creative
 415 | credence
 416 | credible
 417 | crisp
 418 | crisper
 419 | cure
 420 | cure-all
 421 | cushy
 422 | cute
 423 | cuteness
 424 | danke
 425 | danken
 426 | daring
 427 | daringly
 428 | darling
 429 | dashing
 430 | dauntless
 431 | dawn
 432 | dazzle
 433 | dazzled
 434 | dazzling
 435 | dead-cheap
 436 | dead-on
 437 | decency
 438 | decent
 439 | decisive
 440 | decisiveness
 441 | dedicated
 442 | defeat
 443 | defeated
 444 | defeating
 445 | defeats
 446 | defender
 447 | deference
 448 | deft
 449 | deginified
 450 | delectable
 451 | delicacy
 452 | delicate
 453 | delicious
 454 | delight
 455 | delighted
 456 | delightful
 457 | delightfully
 458 | delightfulness
 459 | dependable
 460 | dependably
 461 | deservedly
 462 | deserving
 463 | desirable
 464 | desiring
 465 | desirous
 466 | destiny
 467 | detachable
 468 | devout
 469 | dexterous
 470 | dexterously
 471 | dextrous
 472 | dignified
 473 | dignify
 474 | dignity
 475 | diligence
 476 | diligent
 477 | diligently
 478 | diplomatic
 479 | dirt-cheap
 480 | distinction
 481 | distinctive
 482 | distinguished
 483 | diversified
 484 | divine
 485 | divinely
 486 | dominate
 487 | dominated
 488 | dominates
 489 | dote
 490 | dotingly
 491 | doubtless
 492 | dreamland
 493 | dumbfounded
 494 | dumbfounding
 495 | dummy-proof
 496 | durable
 497 | dynamic
 498 | eager
 499 | eagerly
 500 | eagerness
 501 | earnest
 502 | earnestly
 503 | earnestness
 504 | ease
 505 | eased
 506 | eases
 507 | easier
 508 | easiest
 509 | easiness
 510 | easing
 511 | easy
 512 | easy-to-use
 513 | easygoing
 514 | ebullience
 515 | ebullient
 516 | ebulliently
 517 | ecenomical
 518 | economical
 519 | ecstasies
 520 | ecstasy
 521 | ecstatic
 522 | ecstatically
 523 | edify
 524 | educated
 525 | effective
 526 | effectively
 527 | effectiveness
 528 | effectual
 529 | efficacious
 530 | efficient
 531 | efficiently
 532 | effortless
 533 | effortlessly
 534 | effusion
 535 | effusive
 536 | effusively
 537 | effusiveness
 538 | elan
 539 | elate
 540 | elated
 541 | elatedly
 542 | elation
 543 | electrify
 544 | elegance
 545 | elegant
 546 | elegantly
 547 | elevate
 548 | elite
 549 | eloquence
 550 | eloquent
 551 | eloquently
 552 | embolden
 553 | eminence
 554 | eminent
 555 | empathize
 556 | empathy
 557 | empower
 558 | empowerment
 559 | enchant
 560 | enchanted
 561 | enchanting
 562 | enchantingly
 563 | encourage
 564 | encouragement
 565 | encouraging
 566 | encouragingly
 567 | endear
 568 | endearing
 569 | endorse
 570 | endorsed
 571 | endorsement
 572 | endorses
 573 | endorsing
 574 | energetic
 575 | energize
 576 | energy-efficient
 577 | energy-saving
 578 | engaging
 579 | engrossing
 580 | enhance
 581 | enhanced
 582 | enhancement
 583 | enhances
 584 | enjoy
 585 | enjoyable
 586 | enjoyably
 587 | enjoyed
 588 | enjoying
 589 | enjoyment
 590 | enjoys
 591 | enlighten
 592 | enlightenment
 593 | enliven
 594 | ennoble
 595 | enough
 596 | enrapt
 597 | enrapture
 598 | enraptured
 599 | enrich
 600 | enrichment
 601 | enterprising
 602 | entertain
 603 | entertaining
 604 | entertains
 605 | enthral
 606 | enthrall
 607 | enthralled
 608 | enthuse
 609 | enthusiasm
 610 | enthusiast
 611 | enthusiastic
 612 | enthusiastically
 613 | entice
 614 | enticed
 615 | enticing
 616 | enticingly
 617 | entranced
 618 | entrancing
 619 | entrust
 620 | enviable
 621 | enviably
 622 | envious
 623 | enviously
 624 | enviousness
 625 | envy
 626 | equitable
 627 | ergonomical
 628 | err-free
 629 | erudite
 630 | ethical
 631 | eulogize
 632 | euphoria
 633 | euphoric
 634 | euphorically
 635 | evaluative
 636 | evenly
 637 | eventful
 638 | everlasting
 639 | evocative
 640 | exalt
 641 | exaltation
 642 | exalted
 643 | exaltedly
 644 | exalting
 645 | exaltingly
 646 | examplar
 647 | examplary
 648 | excallent
 649 | exceed
 650 | exceeded
 651 | exceeding
 652 | exceedingly
 653 | exceeds
 654 | excel
 655 | exceled
 656 | excelent
 657 | excellant
 658 | excelled
 659 | excellence
 660 | excellency
 661 | excellent
 662 | excellently
 663 | excels
 664 | exceptional
 665 | exceptionally
 666 | excite
 667 | excited
 668 | excitedly
 669 | excitedness
 670 | excitement
 671 | excites
 672 | exciting
 673 | excitingly
 674 | exellent
 675 | exemplar
 676 | exemplary
 677 | exhilarate
 678 | exhilarating
 679 | exhilaratingly
 680 | exhilaration
 681 | exonerate
 682 | expansive
 683 | expeditiously
 684 | expertly
 685 | exquisite
 686 | exquisitely
 687 | extol
 688 | extoll
 689 | extraordinarily
 690 | extraordinary
 691 | exuberance
 692 | exuberant
 693 | exuberantly
 694 | exult
 695 | exultant
 696 | exultation
 697 | exultingly
 698 | eye-catch
 699 | eye-catching
 700 | eyecatch
 701 | eyecatching
 702 | fabulous
 703 | fabulously
 704 | facilitate
 705 | fair
 706 | fairly
 707 | fairness
 708 | faith
 709 | faithful
 710 | faithfully
 711 | faithfulness
 712 | fame
 713 | famed
 714 | famous
 715 | famously
 716 | fancier
 717 | fancinating
 718 | fancy
 719 | fanfare
 720 | fans
 721 | fantastic
 722 | fantastically
 723 | fascinate
 724 | fascinating
 725 | fascinatingly
 726 | fascination
 727 | fashionable
 728 | fashionably
 729 | fast
 730 | fast-growing
 731 | fast-paced
 732 | faster
 733 | fastest
 734 | fastest-growing
 735 | faultless
 736 | fav
 737 | fave
 738 | favor
 739 | favorable
 740 | favored
 741 | favorite
 742 | favorited
 743 | favour
 744 | fearless
 745 | fearlessly
 746 | feasible
 747 | feasibly
 748 | feat
 749 | feature-rich
 750 | fecilitous
 751 | feisty
 752 | felicitate
 753 | felicitous
 754 | felicity
 755 | fertile
 756 | fervent
 757 | fervently
 758 | fervid
 759 | fervidly
 760 | fervor
 761 | festive
 762 | fidelity
 763 | fiery
 764 | fine
 765 | fine-looking
 766 | finely
 767 | finer
 768 | finest
 769 | firmer
 770 | first-class
 771 | first-in-class
 772 | first-rate
 773 | flashy
 774 | flatter
 775 | flattering
 776 | flatteringly
 777 | flawless
 778 | flawlessly
 779 | flexibility
 780 | flexible
 781 | flourish
 782 | flourishing
 783 | fluent
 784 | flutter
 785 | fond
 786 | fondly
 787 | fondness
 788 | foolproof
 789 | foremost
 790 | foresight
 791 | formidable
 792 | fortitude
 793 | fortuitous
 794 | fortuitously
 795 | fortunate
 796 | fortunately
 797 | fortune
 798 | fragrant
 799 | free
 800 | freed
 801 | freedom
 802 | freedoms
 803 | fresh
 804 | fresher
 805 | freshest
 806 | friendliness
 807 | friendly
 808 | frolic
 809 | frugal
 810 | fruitful
 811 | ftw
 812 | fulfillment
 813 | fun
 814 | futurestic
 815 | futuristic
 816 | gaiety
 817 | gaily
 818 | gain
 819 | gained
 820 | gainful
 821 | gainfully
 822 | gaining
 823 | gains
 824 | gallant
 825 | gallantly
 826 | galore
 827 | geekier
 828 | geeky
 829 | gem
 830 | gems
 831 | generosity
 832 | generous
 833 | generously
 834 | genial
 835 | genius
 836 | gentle
 837 | gentlest
 838 | genuine
 839 | gifted
 840 | glad
 841 | gladden
 842 | gladly
 843 | gladness
 844 | glamorous
 845 | glee
 846 | gleeful
 847 | gleefully
 848 | glimmer
 849 | glimmering
 850 | glisten
 851 | glistening
 852 | glitter
 853 | glitz
 854 | glorify
 855 | glorious
 856 | gloriously
 857 | glory
 858 | glow
 859 | glowing
 860 | glowingly
 861 | god-given
 862 | god-send
 863 | godlike
 864 | godsend
 865 | gold
 866 | golden
 867 | good
 868 | goodly
 869 | goodness
 870 | goodwill
 871 | goood
 872 | gooood
 873 | gorgeous
 874 | gorgeously
 875 | grace
 876 | graceful
 877 | gracefully
 878 | gracious
 879 | graciously
 880 | graciousness
 881 | grand
 882 | grandeur
 883 | grateful
 884 | gratefully
 885 | gratification
 886 | gratified
 887 | gratifies
 888 | gratify
 889 | gratifying
 890 | gratifyingly
 891 | gratitude
 892 | great
 893 | greatest
 894 | greatness
 895 | grin
 896 | groundbreaking
 897 | guarantee
 898 | guidance
 899 | guiltless
 900 | gumption
 901 | gush
 902 | gusto
 903 | gutsy
 904 | hail
 905 | halcyon
 906 | hale
 907 | hallmark
 908 | hallmarks
 909 | hallowed
 910 | handier
 911 | handily
 912 | hands-down
 913 | handsome
 914 | handsomely
 915 | handy
 916 | happier
 917 | happily
 918 | happiness
 919 | happy
 920 | hard-working
 921 | hardier
 922 | hardy
 923 | harmless
 924 | harmonious
 925 | harmoniously
 926 | harmonize
 927 | harmony
 928 | headway
 929 | heal
 930 | healthful
 931 | healthy
 932 | hearten
 933 | heartening
 934 | heartfelt
 935 | heartily
 936 | heartwarming
 937 | heaven
 938 | heavenly
 939 | helped
 940 | helpful
 941 | helping
 942 | hero
 943 | heroic
 944 | heroically
 945 | heroine
 946 | heroize
 947 | heros
 948 | high-quality
 949 | high-spirited
 950 | hilarious
 951 | holy
 952 | homage
 953 | honest
 954 | honesty
 955 | honor
 956 | honorable
 957 | honored
 958 | honoring
 959 | hooray
 960 | hopeful
 961 | hospitable
 962 | hot
 963 | hotcake
 964 | hotcakes
 965 | hottest
 966 | hug
 967 | humane
 968 | humble
 969 | humility
 970 | humor
 971 | humorous
 972 | humorously
 973 | humour
 974 | humourous
 975 | ideal
 976 | idealize
 977 | ideally
 978 | idol
 979 | idolize
 980 | idolized
 981 | idyllic
 982 | illuminate
 983 | illuminati
 984 | illuminating
 985 | illumine
 986 | illustrious
 987 | ilu
 988 | imaculate
 989 | imaginative
 990 | immaculate
 991 | immaculately
 992 | immense
 993 | impartial
 994 | impartiality
 995 | impartially
 996 | impassioned
 997 | impeccable
 998 | impeccably
 999 | important
1000 | impress
1001 | impressed
1002 | impresses
1003 | impressive
1004 | impressively
1005 | impressiveness
1006 | improve
1007 | improved
1008 | improvement
1009 | improvements
1010 | improves
1011 | improving
1012 | incredible
1013 | incredibly
1014 | indebted
1015 | individualized
1016 | indulgence
1017 | indulgent
1018 | industrious
1019 | inestimable
1020 | inestimably
1021 | inexpensive
1022 | infallibility
1023 | infallible
1024 | infallibly
1025 | influential
1026 | ingenious
1027 | ingeniously
1028 | ingenuity
1029 | ingenuous
1030 | ingenuously
1031 | innocuous
1032 | innovation
1033 | innovative
1034 | inpressed
1035 | insightful
1036 | insightfully
1037 | inspiration
1038 | inspirational
1039 | inspire
1040 | inspiring
1041 | instantly
1042 | instructive
1043 | instrumental
1044 | integral
1045 | integrated
1046 | intelligence
1047 | intelligent
1048 | intelligible
1049 | interesting
1050 | interests
1051 | intimacy
1052 | intimate
1053 | intricate
1054 | intrigue
1055 | intriguing
1056 | intriguingly
1057 | intuitive
1058 | invaluable
1059 | invaluablely
1060 | inventive
1061 | invigorate
1062 | invigorating
1063 | invincibility
1064 | invincible
1065 | inviolable
1066 | inviolate
1067 | invulnerable
1068 | irreplaceable
1069 | irreproachable
1070 | irresistible
1071 | irresistibly
1072 | issue-free
1073 | jaw-droping
1074 | jaw-dropping
1075 | jollify
1076 | jolly
1077 | jovial
1078 | joy
1079 | joyful
1080 | joyfully
1081 | joyous
1082 | joyously
1083 | jubilant
1084 | jubilantly
1085 | jubilate
1086 | jubilation
1087 | jubiliant
1088 | judicious
1089 | justly
1090 | keen
1091 | keenly
1092 | keenness
1093 | kid-friendly
1094 | kindliness
1095 | kindly
1096 | kindness
1097 | knowledgeable
1098 | kudos
1099 | large-capacity
1100 | laud
1101 | laudable
1102 | laudably
1103 | lavish
1104 | lavishly
1105 | law-abiding
1106 | lawful
1107 | lawfully
1108 | lead
1109 | leading
1110 | leads
1111 | lean
1112 | led
1113 | legendary
1114 | leverage
1115 | levity
1116 | liberate
1117 | liberation
1118 | liberty
1119 | lifesaver
1120 | light-hearted
1121 | lighter
1122 | likable
1123 | like
1124 | liked
1125 | likes
1126 | liking
1127 | lionhearted
1128 | lively
1129 | logical
1130 | long-lasting
1131 | lovable
1132 | lovably
1133 | love
1134 | loved
1135 | loveliness
1136 | lovely
1137 | lover
1138 | loves
1139 | loving
1140 | low-cost
1141 | low-price
1142 | low-priced
1143 | low-risk
1144 | lower-priced
1145 | loyal
1146 | loyalty
1147 | lucid
1148 | lucidly
1149 | luck
1150 | luckier
1151 | luckiest
1152 | luckiness
1153 | lucky
1154 | lucrative
1155 | luminous
1156 | lush
1157 | luster
1158 | lustrous
1159 | luxuriant
1160 | luxuriate
1161 | luxurious
1162 | luxuriously
1163 | luxury
1164 | lyrical
1165 | magic
1166 | magical
1167 | magnanimous
1168 | magnanimously
1169 | magnificence
1170 | magnificent
1171 | magnificently
1172 | majestic
1173 | majesty
1174 | manageable
1175 | maneuverable
1176 | marvel
1177 | marveled
1178 | marvelled
1179 | marvellous
1180 | marvelous
1181 | marvelously
1182 | marvelousness
1183 | marvels
1184 | master
1185 | masterful
1186 | masterfully
1187 | masterpiece
1188 | masterpieces
1189 | masters
1190 | mastery
1191 | matchless
1192 | mature
1193 | maturely
1194 | maturity
1195 | meaningful
1196 | memorable
1197 | merciful
1198 | mercifully
1199 | mercy
1200 | merit
1201 | meritorious
1202 | merrily
1203 | merriment
1204 | merriness
1205 | merry
1206 | mesmerize
1207 | mesmerized
1208 | mesmerizes
1209 | mesmerizing
1210 | mesmerizingly
1211 | meticulous
1212 | meticulously
1213 | mightily
1214 | mighty
1215 | mind-blowing
1216 | miracle
1217 | miracles
1218 | miraculous
1219 | miraculously
1220 | miraculousness
1221 | modern
1222 | modest
1223 | modesty
1224 | momentous
1225 | monumental
1226 | monumentally
1227 | morality
1228 | motivated
1229 | multi-purpose
1230 | navigable
1231 | neat
1232 | neatest
1233 | neatly
1234 | nice
1235 | nicely
1236 | nicer
1237 | nicest
1238 | nifty
1239 | nimble
1240 | noble
1241 | nobly
1242 | noiseless
1243 | non-violence
1244 | non-violent
1245 | notably
1246 | noteworthy
1247 | nourish
1248 | nourishing
1249 | nourishment
1250 | novelty
1251 | nurturing
1252 | oasis
1253 | obsession
1254 | obsessions
1255 | obtainable
1256 | openly
1257 | openness
1258 | optimal
1259 | optimism
1260 | optimistic
1261 | opulent
1262 | orderly
1263 | originality
1264 | outdo
1265 | outdone
1266 | outperform
1267 | outperformed
1268 | outperforming
1269 | outperforms
1270 | outshine
1271 | outshone
1272 | outsmart
1273 | outstanding
1274 | outstandingly
1275 | outstrip
1276 | outwit
1277 | ovation
1278 | overjoyed
1279 | overtake
1280 | overtaken
1281 | overtakes
1282 | overtaking
1283 | overtook
1284 | overture
1285 | pain-free
1286 | painless
1287 | painlessly
1288 | palatial
1289 | pamper
1290 | pampered
1291 | pamperedly
1292 | pamperedness
1293 | pampers
1294 | panoramic
1295 | paradise
1296 | paramount
1297 | pardon
1298 | passion
1299 | passionate
1300 | passionately
1301 | patience
1302 | patient
1303 | patiently
1304 | patriot
1305 | patriotic
1306 | peace
1307 | peaceable
1308 | peaceful
1309 | peacefully
1310 | peacekeepers
1311 | peach
1312 | peerless
1313 | pep
1314 | pepped
1315 | pepping
1316 | peppy
1317 | peps
1318 | perfect
1319 | perfection
1320 | perfectly
1321 | permissible
1322 | perseverance
1323 | persevere
1324 | personages
1325 | personalized
1326 | phenomenal
1327 | phenomenally
1328 | picturesque
1329 | piety
1330 | pinnacle
1331 | playful
1332 | playfully
1333 | pleasant
1334 | pleasantly
1335 | pleased
1336 | pleases
1337 | pleasing
1338 | pleasingly
1339 | pleasurable
1340 | pleasurably
1341 | pleasure
1342 | plentiful
1343 | pluses
1344 | plush
1345 | plusses
1346 | poetic
1347 | poeticize
1348 | poignant
1349 | poise
1350 | poised
1351 | polished
1352 | polite
1353 | politeness
1354 | popular
1355 | portable
1356 | posh
1357 | positive
1358 | positively
1359 | positives
1360 | powerful
1361 | powerfully
1362 | praise
1363 | praiseworthy
1364 | praising
1365 | pre-eminent
1366 | precious
1367 | precise
1368 | precisely
1369 | preeminent
1370 | prefer
1371 | preferable
1372 | preferably
1373 | prefered
1374 | preferred
1375 | preferes
1376 | preferring
1377 | prefers
1378 | premier
1379 | prestige
1380 | prestigious
1381 | prettily
1382 | pretty
1383 | priceless
1384 | pride
1385 | principled
1386 | privilege
1387 | privileged
1388 | prize
1389 | proactive
1390 | problem-free
1391 | problem-solver
1392 | prodigious
1393 | prodigiously
1394 | prodigy
1395 | productive
1396 | productively
1397 | proficient
1398 | proficiently
1399 | profound
1400 | profoundly
1401 | profuse
1402 | profusion
1403 | progress
1404 | progressive
1405 | prolific
1406 | prominence
1407 | prominent
1408 | promise
1409 | promised
1410 | promises
1411 | promising
1412 | promoter
1413 | prompt
1414 | promptly
1415 | proper
1416 | properly
1417 | propitious
1418 | propitiously
1419 | pros
1420 | prosper
1421 | prosperity
1422 | prosperous
1423 | prospros
1424 | protect
1425 | protection
1426 | protective
1427 | proud
1428 | proven
1429 | proves
1430 | providence
1431 | proving
1432 | prowess
1433 | prudence
1434 | prudent
1435 | prudently
1436 | punctual
1437 | pure
1438 | purify
1439 | purposeful
1440 | quaint
1441 | qualified
1442 | qualify
1443 | quicker
1444 | quiet
1445 | quieter
1446 | radiance
1447 | radiant
1448 | rapid
1449 | rapport
1450 | rapt
1451 | rapture
1452 | raptureous
1453 | raptureously
1454 | rapturous
1455 | rapturously
1456 | rational
1457 | razor-sharp
1458 | reachable
1459 | readable
1460 | readily
1461 | ready
1462 | reaffirm
1463 | reaffirmation
1464 | realistic
1465 | realizable
1466 | reasonable
1467 | reasonably
1468 | reasoned
1469 | reassurance
1470 | reassure
1471 | receptive
1472 | reclaim
1473 | recomend
1474 | recommend
1475 | recommendation
1476 | recommendations
1477 | recommended
1478 | reconcile
1479 | reconciliation
1480 | record-setting
1481 | recover
1482 | recovery
1483 | rectification
1484 | rectify
1485 | rectifying
1486 | redeem
1487 | redeeming
1488 | redemption
1489 | refine
1490 | refined
1491 | refinement
1492 | reform
1493 | reformed
1494 | reforming
1495 | reforms
1496 | refresh
1497 | refreshed
1498 | refreshing
1499 | refund
1500 | refunded
1501 | regal
1502 | regally
1503 | regard
1504 | rejoice
1505 | rejoicing
1506 | rejoicingly
1507 | rejuvenate
1508 | rejuvenated
1509 | rejuvenating
1510 | relaxed
1511 | relent
1512 | reliable
1513 | reliably
1514 | relief
1515 | relish
1516 | remarkable
1517 | remarkably
1518 | remedy
1519 | remission
1520 | remunerate
1521 | renaissance
1522 | renewed
1523 | renown
1524 | renowned
1525 | replaceable
1526 | reputable
1527 | reputation
1528 | resilient
1529 | resolute
1530 | resound
1531 | resounding
1532 | resourceful
1533 | resourcefulness
1534 | respect
1535 | respectable
1536 | respectful
1537 | respectfully
1538 | respite
1539 | resplendent
1540 | responsibly
1541 | responsive
1542 | restful
1543 | restored
1544 | restructure
1545 | restructured
1546 | restructuring
1547 | retractable
1548 | revel
1549 | revelation
1550 | revere
1551 | reverence
1552 | reverent
1553 | reverently
1554 | revitalize
1555 | revival
1556 | revive
1557 | revives
1558 | revolutionary
1559 | revolutionize
1560 | revolutionized
1561 | revolutionizes
1562 | reward
1563 | rewarding
1564 | rewardingly
1565 | rich
1566 | richer
1567 | richly
1568 | richness
1569 | right
1570 | righten
1571 | righteous
1572 | righteously
1573 | righteousness
1574 | rightful
1575 | rightfully
1576 | rightly
1577 | rightness
1578 | risk-free
1579 | robust
1580 | rock-star
1581 | rock-stars
1582 | rockstar
1583 | rockstars
1584 | romantic
1585 | romantically
1586 | romanticize
1587 | roomier
1588 | roomy
1589 | rosy
1590 | safe
1591 | safely
1592 | sagacity
1593 | sagely
1594 | saint
1595 | saintliness
1596 | saintly
1597 | salutary
1598 | salute
1599 | sane
1600 | satisfactorily
1601 | satisfactory
1602 | satisfied
1603 | satisfies
1604 | satisfy
1605 | satisfying
1606 | satisified
1607 | saver
1608 | savings
1609 | savior
1610 | savvy
1611 | scenic
1612 | seamless
1613 | seasoned
1614 | secure
1615 | securely
1616 | selective
1617 | self-determination
1618 | self-respect
1619 | self-satisfaction
1620 | self-sufficiency
1621 | self-sufficient
1622 | sensation
1623 | sensational
1624 | sensationally
1625 | sensations
1626 | sensible
1627 | sensibly
1628 | sensitive
1629 | serene
1630 | serenity
1631 | sexy
1632 | sharp
1633 | sharper
1634 | sharpest
1635 | shimmering
1636 | shimmeringly
1637 | shine
1638 | shiny
1639 | significant
1640 | silent
1641 | simpler
1642 | simplest
1643 | simplified
1644 | simplifies
1645 | simplify
1646 | simplifying
1647 | sincere
1648 | sincerely
1649 | sincerity
1650 | skill
1651 | skilled
1652 | skillful
1653 | skillfully
1654 | slammin
1655 | sleek
1656 | slick
1657 | smart
1658 | smarter
1659 | smartest
1660 | smartly
1661 | smile
1662 | smiles
1663 | smiling
1664 | smilingly
1665 | smitten
1666 | smooth
1667 | smoother
1668 | smoothes
1669 | smoothest
1670 | smoothly
1671 | snappy
1672 | snazzy
1673 | sociable
1674 | soft
1675 | softer
1676 | solace
1677 | solicitous
1678 | solicitously
1679 | solid
1680 | solidarity
1681 | soothe
1682 | soothingly
1683 | sophisticated
1684 | soulful
1685 | soundly
1686 | soundness
1687 | spacious
1688 | sparkle
1689 | sparkling
1690 | spectacular
1691 | spectacularly
1692 | speedily
1693 | speedy
1694 | spellbind
1695 | spellbinding
1696 | spellbindingly
1697 | spellbound
1698 | spirited
1699 | spiritual
1700 | splendid
1701 | splendidly
1702 | splendor
1703 | spontaneous
1704 | sporty
1705 | spotless
1706 | sprightly
1707 | stability
1708 | stabilize
1709 | stable
1710 | stainless
1711 | standout
1712 | state-of-the-art
1713 | stately
1714 | statuesque
1715 | staunch
1716 | staunchly
1717 | staunchness
1718 | steadfast
1719 | steadfastly
1720 | steadfastness
1721 | steadiest
1722 | steadiness
1723 | steady
1724 | stellar
1725 | stellarly
1726 | stimulate
1727 | stimulates
1728 | stimulating
1729 | stimulative
1730 | stirringly
1731 | straighten
1732 | straightforward
1733 | streamlined
1734 | striking
1735 | strikingly
1736 | striving
1737 | strong
1738 | stronger
1739 | strongest
1740 | stunned
1741 | stunning
1742 | stunningly
1743 | stupendous
1744 | stupendously
1745 | sturdier
1746 | sturdy
1747 | stylish
1748 | stylishly
1749 | stylized
1750 | suave
1751 | suavely
1752 | sublime
1753 | subsidize
1754 | subsidized
1755 | subsidizes
1756 | subsidizing
1757 | substantive
1758 | succeed
1759 | succeeded
1760 | succeeding
1761 | succeeds
1762 | succes
1763 | success
1764 | successes
1765 | successful
1766 | successfully
1767 | suffice
1768 | sufficed
1769 | suffices
1770 | sufficient
1771 | sufficiently
1772 | suitable
1773 | sumptuous
1774 | sumptuously
1775 | sumptuousness
1776 | super
1777 | superb
1778 | superbly
1779 | superior
1780 | superiority
1781 | supple
1782 | support
1783 | supported
1784 | supporter
1785 | supporting
1786 | supportive
1787 | supports
1788 | supremacy
1789 | supreme
1790 | supremely
1791 | supurb
1792 | supurbly
1793 | surmount
1794 | surpass
1795 | surreal
1796 | survival
1797 | survivor
1798 | sustainability
1799 | sustainable
1800 | swank
1801 | swankier
1802 | swankiest
1803 | swanky
1804 | sweeping
1805 | sweet
1806 | sweeten
1807 | sweetheart
1808 | sweetly
1809 | sweetness
1810 | swift
1811 | swiftness
1812 | talent
1813 | talented
1814 | talents
1815 | tantalize
1816 | tantalizing
1817 | tantalizingly
1818 | tempt
1819 | tempting
1820 | temptingly
1821 | tenacious
1822 | tenaciously
1823 | tenacity
1824 | tender
1825 | tenderly
1826 | terrific
1827 | terrifically
1828 | thank
1829 | thankful
1830 | thinner
1831 | thoughtful
1832 | thoughtfully
1833 | thoughtfulness
1834 | thrift
1835 | thrifty
1836 | thrill
1837 | thrilled
1838 | thrilling
1839 | thrillingly
1840 | thrills
1841 | thrive
1842 | thriving
1843 | thumb-up
1844 | thumbs-up
1845 | tickle
1846 | tidy
1847 | time-honored
1848 | timely
1849 | tingle
1850 | titillate
1851 | titillating
1852 | titillatingly
1853 | togetherness
1854 | tolerable
1855 | toll-free
1856 | top
1857 | top-notch
1858 | top-quality
1859 | topnotch
1860 | tops
1861 | tough
1862 | tougher
1863 | toughest
1864 | traction
1865 | tranquil
1866 | tranquility
1867 | transparent
1868 | treasure
1869 | tremendously
1870 | trendy
1871 | triumph
1872 | triumphal
1873 | triumphant
1874 | triumphantly
1875 | trivially
1876 | trophy
1877 | trouble-free
1878 | trump
1879 | trumpet
1880 | trust
1881 | trusted
1882 | trusting
1883 | trustingly
1884 | trustworthiness
1885 | trustworthy
1886 | trusty
1887 | truthful
1888 | truthfully
1889 | truthfulness
1890 | twinkly
1891 | ultra-crisp
1892 | unabashed
1893 | unabashedly
1894 | unaffected
1895 | unassailable
1896 | unbeatable
1897 | unbiased
1898 | unbound
1899 | uncomplicated
1900 | unconditional
1901 | undamaged
1902 | undaunted
1903 | understandable
1904 | undisputable
1905 | undisputably
1906 | undisputed
1907 | unencumbered
1908 | unequivocal
1909 | unequivocally
1910 | unfazed
1911 | unfettered
1912 | unforgettable
1913 | unity
1914 | unlimited
1915 | unmatched
1916 | unparalleled
1917 | unquestionable
1918 | unquestionably
1919 | unreal
1920 | unrestricted
1921 | unrivaled
1922 | unselfish
1923 | unwavering
1924 | upbeat
1925 | upgradable
1926 | upgradeable
1927 | upgraded
1928 | upheld
1929 | uphold
1930 | uplift
1931 | uplifting
1932 | upliftingly
1933 | upliftment
1934 | upscale
1935 | usable
1936 | useable
1937 | useful
1938 | user-friendly
1939 | user-replaceable
1940 | valiant
1941 | valiantly
1942 | valor
1943 | valuable
1944 | variety
1945 | venerate
1946 | verifiable
1947 | veritable
1948 | versatile
1949 | versatility
1950 | vibrant
1951 | vibrantly
1952 | victorious
1953 | victory
1954 | viewable
1955 | vigilance
1956 | vigilant
1957 | virtue
1958 | virtuous
1959 | virtuously
1960 | visionary
1961 | vivacious
1962 | vivid
1963 | vouch
1964 | vouchsafe
1965 | warm
1966 | warmer
1967 | warmhearted
1968 | warmly
1969 | warmth
1970 | wealthy
1971 | welcome
1972 | well
1973 | well-backlit
1974 | well-balanced
1975 | well-behaved
1976 | well-being
1977 | well-bred
1978 | well-connected
1979 | well-educated
1980 | well-established
1981 | well-informed
1982 | well-intentioned
1983 | well-known
1984 | well-made
1985 | well-managed
1986 | well-mannered
1987 | well-positioned
1988 | well-received
1989 | well-regarded
1990 | well-rounded
1991 | well-run
1992 | well-wishers
1993 | wellbeing
1994 | whoa
1995 | wholeheartedly
1996 | wholesome
1997 | whooa
1998 | whoooa
1999 | wieldy
2000 | willing
2001 | willingly
2002 | willingness
2003 | win
2004 | windfall
2005 | winnable
2006 | winner
2007 | winners
2008 | winning
2009 | wins
2010 | wisdom
2011 | wise
2012 | wisely
2013 | witty
2014 | won
2015 | wonder
2016 | wonderful
2017 | wonderfully
2018 | wonderous
2019 | wonderously
2020 | wonders
2021 | wondrous
2022 | woo
2023 | work
2024 | workable
2025 | worked
2026 | works
2027 | world-famous
2028 | worth
2029 | worth-while
2030 | worthiness
2031 | worthwhile
2032 | worthy
2033 | wow
2034 | wowed
2035 | wowing
2036 | wows
2037 | yay
2038 | youthful
2039 | zeal
2040 | zenith
2041 | zest
2042 | zippy
2043 | 


--------------------------------------------------------------------------------
/data/table_langs.dat:
--------------------------------------------------------------------------------
 1 | letter eng fre ger ita spa
 2 | a 0.0808783414208 0.079273025705 0.0568582875156 0.1060031229 0.118567414491
 3 | b 0.0149950113502 0.0092479604668 0.0192519980017 0.00919519581228 0.012695276417
 4 | c 0.0336029658098 0.0342575070419 0.029708356129 0.0433579460651 0.041907944126
 5 | d 0.0379933775582 0.0422686237749 0.055100382796 0.0397373974222 0.0568073474155
 6 | e 0.124356078548 0.159318020755 0.171682680247 0.120917565478 0.141614692623
 7 | f 0.0237416733255 0.0113065860952 0.0142226130909 0.0112867556637 0.00775281578278
 8 | g 0.0188408895246 0.00935384525938 0.0291633379749 0.0173940086624 0.0107247478907
 9 | h 0.0500154160339 0.00794796267702 0.0433463299748 0.00935158965745 0.00765374645203
10 | i 0.0759370579447 0.074125468632 0.086132188668 0.11507204904 0.0635059635731
11 | j 0.00164965470904 0.00326286353724 0.00216341245919 0.000282162069447 0.0041157233961
12 | k 0.00567882113207 0.000659558715746 0.0124250996316 0.000399660011311 0.000328782735455
13 | l 0.0410312996421 0.0573586586354 0.0367288351619 0.0616877719016 0.0607166586804
14 | m 0.0253212637287 0.0258101565257 0.0245885948406 0.0268612465663 0.0254824077396
15 | n 0.072304648957 0.0764937181942 0.103787476648 0.0728869438196 0.0691817071832
16 | o 0.0761468415252 0.0595239565172 0.0290637090653 0.0906044293764 0.0883320353023
17 | p 0.0214697245349 0.0294623507425 0.00876402098758 0.0276401642725 0.0258004813041
18 | q 0.00122887673405 0.0105442071602 0.000377970342343 0.00487303230998 0.00905148564896
19 | r 0.0630102949732 0.0643232512635 0.0704593427187 0.0646314937914 0.0672708654336
20 | s 0.0652173871887 0.0859151648317 0.0660878501979 0.0532710870302 0.0764805377382
21 | t 0.0919160242842 0.0703747299066 0.0600099773573 0.0662925198438 0.0461031344608
22 | u 0.0275286512584 0.0646008560686 0.0407986194019 0.0303684795337 0.040217887286
23 | v 0.0105671625339 0.0144851496214 0.00990369600532 0.0159794436523 0.00996526145819
24 | w 0.0165338939469 0.000523606146355 0.0149539341852 0.000404743085526 0.00029734184325
25 | x 0.002368584909 0.00519174358013 0.000762948680815 0.000544979257253 0.00190895688811
26 | y 0.0166228996184 0.00322920037757 0.00150947910449 0.000533075566006 0.0101561916343
27 | z 0.00104315880807 0.0011418277687 0.0121488588132 0.0104231372113 0.00336059249619
28 | 


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/data/text8.gz:
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https://raw.githubusercontent.com/DataForScience/NLP/849b1ab04336336035eaa2a09b482142fa9c12d3/data/text8.gz


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/requirements.txt:
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1 | pandas==1.0.1
2 | watermark==2.0.2
3 | numpy==1.18.1
4 | matplotlib==3.1.3
5 | scikit_learn==0.22.2.post1
6 | 


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/slides/NLP.pdf:
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https://raw.githubusercontent.com/DataForScience/NLP/849b1ab04336336035eaa2a09b482142fa9c12d3/slides/NLP.pdf


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