11-3-NRC-Chinese-dict.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 基于NRC字典的情感分析\n",
    "\n",
    "NRC词典为加拿大国家研究委员会信息技术研究所(Institute for Information Technology, National Research Council Canada. )组织制作的基于众包方式标注出的词典。\n",
    "\n",
    "Mohammad, Saif M., and Peter D. Turney. \"Crowdsourcing a word–emotion association lexicon.\" Computational Intelligence 29, no. 3 (2013): 436-465.\n",
    "\n",
    "http://sentiment.nrc.ca/lexicons-for-research/ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "THE SENTIMENT AND EMOTION LEXICONS (click to download the complete bundle, 100Mb)\n",
    "\n",
    "Individual lexicons for download:\n",
    "- Manually created lexicons:\u000b",
    "NRC Emotion Lexicon\u000b",
    "NRC Emotion Intensity Lexicon\u000b",
    "NRC Valence, Arousal, and Dominance (VAD) Lexicon\u000b",
    "NRC Sentiment Composition Lexicons (SCL-NMA, SCL-OPP, SemEval-2015 English Twitter, SemEval-2016 Arabic Twitter)\u000b",
    "NRC Word-Colour Association Lexicon\n",
    "- Automatically generated lexicons:\u000b",
    "NRC Hashtag Emotion Lexicon\u000b",
    "NRC Hashtag Sentiment Lexicon\u000b",
    "NRC Hashtag Affirmative Context Sentiment Lexicon and NRC Hashtag Negated Context Sentiment Lexicon\u000b",
    "NRC Emoticon Lexicon (a.k.a. Sentiment140 Lexicon)\u000b",
    "NRC Emoticon Affirmative Context Lexicon and NRC Emoticon Negated Context Lexicon\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vosoughi et al., The spread of true and false news online. Science  359, 1146–1151 (2018) 9 March 2018\n",
    "\n",
    "\n",
    "> We categorized the emotion in the replies by using the leading lexicon curated by the National Research Council Canada (NRC), which provides a comprehensive list of ~140,000 English words and their associations with eight emotions \n",
    "\n",
    "False news was more novel than true news, which suggests that people were more likely to share novel information. Whereas false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust. \n",
    "\n",
    "\n",
    "![image.png](images/NRC.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:33:43.332138Z",
     "start_time": "2020-10-30T12:33:42.964254Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:34:14.030738Z",
     "start_time": "2020-10-30T12:33:50.887640Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>English (en)</th>\n",
       "      <th>Afrikaans (af)</th>\n",
       "      <th>Albanian (sq)</th>\n",
       "      <th>Amharic (am)</th>\n",
       "      <th>Arabic (ar)</th>\n",
       "      <th>Armenian (hy)</th>\n",
       "      <th>Azeerbaijani (az)</th>\n",
       "      <th>Basque (eu)</th>\n",
       "      <th>Belarusian (be)</th>\n",
       "      <th>Bengali (bn)</th>\n",
       "      <th>...</th>\n",
       "      <th>Positive</th>\n",
       "      <th>Negative</th>\n",
       "      <th>Anger</th>\n",
       "      <th>Anticipation</th>\n",
       "      <th>Disgust</th>\n",
       "      <th>Fear</th>\n",
       "      <th>Joy</th>\n",
       "      <th>Sadness</th>\n",
       "      <th>Surprise</th>\n",
       "      <th>Trust</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aback</td>\n",
       "      <td>uit die veld geslaan</td>\n",
       "      <td>prapa</td>\n",
       "      <td>ተጭኗል</td>\n",
       "      <td>الى الوراء</td>\n",
       "      <td>շեղում</td>\n",
       "      <td>sanki</td>\n",
       "      <td>aback</td>\n",
       "      <td>ззаду</td>\n",
       "      <td>পশ্চাতে</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>abacus</td>\n",
       "      <td>abakus</td>\n",
       "      <td>numërator</td>\n",
       "      <td>abacus</td>\n",
       "      <td>طبلية تاج</td>\n",
       "      <td>անբավարարություն</td>\n",
       "      <td>abacus</td>\n",
       "      <td>abako</td>\n",
       "      <td>абака</td>\n",
       "      <td>গণনা-যন্ত্রবিশেষ</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>abandon</td>\n",
       "      <td>verlaat</td>\n",
       "      <td>braktis</td>\n",
       "      <td>ውጣ</td>\n",
       "      <td>تخلى</td>\n",
       "      <td>լքել</td>\n",
       "      <td>tərk et</td>\n",
       "      <td>bertan behera</td>\n",
       "      <td>адмовіцца ад</td>\n",
       "      <td>বর্জিত করা</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>abandoned</td>\n",
       "      <td>verlate</td>\n",
       "      <td>braktisur</td>\n",
       "      <td>ተትቷል</td>\n",
       "      <td>مهجور</td>\n",
       "      <td>լքված</td>\n",
       "      <td>tərk etdi</td>\n",
       "      <td>abandonatutako</td>\n",
       "      <td>закінуты</td>\n",
       "      <td>পরিত্যক্ত</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>abandonment</td>\n",
       "      <td>verlating</td>\n",
       "      <td>braktisje</td>\n",
       "      <td>ማቋረጥ</td>\n",
       "      <td>التخلي عن</td>\n",
       "      <td>հրաժարվելով</td>\n",
       "      <td>ləğv</td>\n",
       "      <td>abandono</td>\n",
       "      <td>пакіданне</td>\n",
       "      <td>বিসর্জন</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 115 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  English (en)        Afrikaans (af) Albanian (sq) Amharic (am) Arabic (ar)  \\\n",
       "0        aback  uit die veld geslaan         prapa         ተጭኗል  الى الوراء   \n",
       "1       abacus                abakus     numërator       abacus   طبلية تاج   \n",
       "2      abandon               verlaat       braktis           ውጣ        تخلى   \n",
       "3    abandoned               verlate     braktisur         ተትቷል       مهجور   \n",
       "4  abandonment             verlating     braktisje         ማቋረጥ   التخلي عن   \n",
       "\n",
       "      Armenian (hy) Azeerbaijani (az)     Basque (eu) Belarusian (be)  \\\n",
       "0            շեղում             sanki           aback           ззаду   \n",
       "1  անբավարարություն            abacus           abako           абака   \n",
       "2              լքել           tərk et   bertan behera    адмовіцца ад   \n",
       "3             լքված         tərk etdi  abandonatutako        закінуты   \n",
       "4       հրաժարվելով              ləğv        abandono       пакіданне   \n",
       "\n",
       "       Bengali (bn)  ... Positive Negative Anger Anticipation Disgust Fear  \\\n",
       "0           পশ্চাতে  ...        0        0     0            0       0    0   \n",
       "1  গণনা-যন্ত্রবিশেষ  ...        0        0     0            0       0    0   \n",
       "2        বর্জিত করা  ...        0        1     0            0       0    1   \n",
       "3         পরিত্যক্ত  ...        0        1     1            0       0    1   \n",
       "4           বিসর্জন  ...        0        1     1            0       0    1   \n",
       "\n",
       "  Joy Sadness Surprise Trust  \n",
       "0   0       0        0     0  \n",
       "1   0       0        0     1  \n",
       "2   0       1        0     0  \n",
       "3   0       1        0     0  \n",
       "4   0       1        1     0  \n",
       "\n",
       "[5 rows x 115 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lexion_df = pd.read_excel('./Textmining/NRC-Emotion-Lexicon-v0.92-In105Languages-Nov2017Translations.xlsx')\n",
    "lexion_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:34:20.419523Z",
     "start_time": "2020-10-30T12:34:20.414047Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['English (en)',\n",
       " 'Afrikaans (af)',\n",
       " 'Albanian (sq)',\n",
       " 'Amharic (am)',\n",
       " 'Arabic (ar)',\n",
       " 'Armenian (hy)',\n",
       " 'Azeerbaijani (az)',\n",
       " 'Basque (eu)',\n",
       " 'Belarusian (be)',\n",
       " 'Bengali (bn)',\n",
       " 'Bosnian (bs)',\n",
       " 'Bulgarian (bg)',\n",
       " 'Catalan (ca)',\n",
       " 'Cebuano (ceb)',\n",
       " 'Chinese (Simplified) (zh-CN)',\n",
       " 'Chinese (Traditional) (zh-TW)',\n",
       " 'Corsican (co)',\n",
       " 'Croatian (hr)',\n",
       " 'Czech (cs)',\n",
       " 'Danish (da)',\n",
       " 'Dutch (nl)',\n",
       " 'English (en).1',\n",
       " 'Esperanto (eo)',\n",
       " 'Estonian (et)',\n",
       " 'Finnish (fi)',\n",
       " 'French (fr)',\n",
       " 'Frisian (fy)',\n",
       " 'Galician (gl)',\n",
       " 'Georgian (ka)',\n",
       " 'German (de)',\n",
       " 'Greek (el)',\n",
       " 'Gujarati (gu)',\n",
       " 'Haitian Creole (ht)',\n",
       " 'Hausa (ha)',\n",
       " 'Hawaiian (haw)',\n",
       " 'Hebrew (iw)',\n",
       " 'Hindi (hi)',\n",
       " 'Hmong (hmn)',\n",
       " 'Hungarian (hu)',\n",
       " 'Icelandic (is)',\n",
       " 'Igbo (ig)',\n",
       " 'Indonesian (id)',\n",
       " 'Irish (ga)',\n",
       " 'Italian (it)',\n",
       " 'Japanese (ja)',\n",
       " 'Javanese (jw)',\n",
       " 'Kannada (kn)',\n",
       " 'Kazakh (kk)',\n",
       " 'Khmer (km)',\n",
       " 'Korean (ko)',\n",
       " 'Kurdish (ku)',\n",
       " 'Kyrgyz (ky)',\n",
       " 'Lao (lo)',\n",
       " 'Latin (la)',\n",
       " 'Latvian (lv)',\n",
       " 'Lithuanian (lt)',\n",
       " 'Luxembourgish (lb)',\n",
       " 'Macedonian (mk)',\n",
       " 'Malagasy (mg)',\n",
       " 'Malay (ms)',\n",
       " 'Malayalam (ml)',\n",
       " 'Maltese (mt)',\n",
       " 'Maori (mi)',\n",
       " 'Marathi (mr)',\n",
       " 'Mongolian (mn)',\n",
       " 'Myanmar (Burmese) (my)',\n",
       " 'Nepali (ne)',\n",
       " 'Norwegian (no)',\n",
       " 'Nyanja (Chichewa) (ny)',\n",
       " 'Pashto (ps)',\n",
       " 'Persian (fa)',\n",
       " 'Polish (pl)',\n",
       " 'Portuguese (Portugal, Brazil) (pt)',\n",
       " 'Punjabi (pa)',\n",
       " 'Romanian (ro)',\n",
       " 'Russian (ru)',\n",
       " 'Samoan (sm)',\n",
       " 'Scots Gaelic (gd)',\n",
       " 'Serbian (sr)',\n",
       " 'Sesotho (st)',\n",
       " 'Shona (sn)',\n",
       " 'Sindhi (sd)',\n",
       " 'Sinhala (Sinhalese) (si)',\n",
       " 'Slovak (sk)',\n",
       " 'Slovenian (sl)',\n",
       " 'Somali (so)',\n",
       " 'Spanish (es)',\n",
       " 'Sundanese (su)',\n",
       " 'Swahili (sw)',\n",
       " 'Swedish (sv)',\n",
       " 'Tagalog (Filipino) (tl)',\n",
       " 'Tajik (tg)',\n",
       " 'Tamil (ta)',\n",
       " 'Telugu (te)',\n",
       " 'Thai (th)',\n",
       " 'Turkish (tr)',\n",
       " 'Ukrainian (uk)',\n",
       " 'Urdu (ur)',\n",
       " 'Uzbek (uz)',\n",
       " 'Vietnamese (vi)',\n",
       " 'Welsh (cy)',\n",
       " 'Xhosa (xh)',\n",
       " 'Yiddish (yi)',\n",
       " 'Yoruba (yo)',\n",
       " 'Zulu (zu)',\n",
       " 'Positive',\n",
       " 'Negative',\n",
       " 'Anger',\n",
       " 'Anticipation',\n",
       " 'Disgust',\n",
       " 'Fear',\n",
       " 'Joy',\n",
       " 'Sadness',\n",
       " 'Surprise',\n",
       " 'Trust']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lexion_df.columns.tolist()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:34:32.511980Z",
     "start_time": "2020-10-30T12:34:32.498259Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Chinese (Simplified) (zh-CN)</th>\n",
       "      <th>Positive</th>\n",
       "      <th>Negative</th>\n",
       "      <th>Anger</th>\n",
       "      <th>Anticipation</th>\n",
       "      <th>Disgust</th>\n",
       "      <th>Fear</th>\n",
       "      <th>Joy</th>\n",
       "      <th>Sadness</th>\n",
       "      <th>Surprise</th>\n",
       "      <th>Trust</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>吓了一跳</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>算盘</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>放弃</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>弃</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>放弃</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Chinese (Simplified) (zh-CN)  Positive  Negative  Anger  Anticipation  \\\n",
       "0                         吓了一跳         0         0      0             0   \n",
       "1                           算盘         0         0      0             0   \n",
       "2                           放弃         0         1      0             0   \n",
       "3                            弃         0         1      1             0   \n",
       "4                           放弃         0         1      1             0   \n",
       "\n",
       "   Disgust  Fear  Joy  Sadness  Surprise  Trust  \n",
       "0        0     0    0        0         0      0  \n",
       "1        0     0    0        0         0      1  \n",
       "2        0     1    0        1         0      0  \n",
       "3        0     1    0        1         0      0  \n",
       "4        0     1    0        1         1      0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chinese_df = lexion_df[['Chinese (Simplified) (zh-CN)', 'Positive', 'Negative', \n",
    "                 'Anger','Anticipation', 'Disgust', 'Fear', 'Joy', 'Sadness', 'Surprise', 'Trust']]\n",
    "chinese_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:34:42.781766Z",
     "start_time": "2020-10-30T12:34:39.767491Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "词语列表构建完成\n"
     ]
    }
   ],
   "source": [
    "# 构建情感词列表\n",
    "\n",
    "Positive, Negative, Anger, Anticipation, Disgust, Fear, Joy, Sadness, Surprise, Trust= [[] for i in range(10)]\n",
    "for idx, row in chinese_df.iterrows():\n",
    "    if row['Positive']==1:\n",
    "        Positive.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Negative']==1:\n",
    "        Negative.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Anger']==1:\n",
    "        Anger.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Anticipation']==1:\n",
    "        Anticipation.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Disgust']==1:\n",
    "        Disgust.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Fear']==1:\n",
    "        Fear.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Joy']==1:\n",
    "        Joy.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Sadness']==1:\n",
    "        Sadness.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Surprise']==1:\n",
    "        Surprise.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "    if row['Trust']==1:\n",
    "        Trust.append(row['Chinese (Simplified) (zh-CN)'])\n",
    "\n",
    "print('词语列表构建完成')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:34:47.206966Z",
     "start_time": "2020-10-30T12:34:47.202981Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['弃', '放弃', '痛恨', '可恶', '废除', '厌恶', '滥用', '诅咒', '指控', '被告']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Anger[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T05:27:49.407406Z",
     "start_time": "2020-10-30T05:27:49.401825Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 0]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "positive, negative, anger, anticipation, disgust, fear, joy, sadness, surprise, trust = [0 for i in range(10)]\n",
    "[positive, negative]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:34:58.145527Z",
     "start_time": "2020-10-30T12:34:57.856527Z"
    }
   },
   "outputs": [],
   "source": [
    "import jieba\n",
    "import time\n",
    "\n",
    "\n",
    "def emotion_caculate(text):\n",
    "    positive, negative, anger, anticipation, disgust, fear, joy, sadness, surprise, trust = [0 for i in range(10)]\n",
    "    \n",
    "    wordlist = jieba.lcut(text)\n",
    "    wordset = set(wordlist)\n",
    "    wordfreq = []\n",
    "    for word in wordset:\n",
    "        freq = wordlist.count(word)\n",
    "        if word in Positive:\n",
    "            positive+=freq\n",
    "        if word in Negative:\n",
    "            negative+=freq\n",
    "        if word in Anger:\n",
    "            anger+=freq  \n",
    "        if word in Anticipation:\n",
    "            anticipation+=freq\n",
    "        if word in Disgust:\n",
    "            disgust+=freq\n",
    "        if word in Fear:\n",
    "            fear+=freq\n",
    "        if word in Joy:\n",
    "            joy+=freq\n",
    "        if word in Sadness:\n",
    "            sadness+=freq\n",
    "        if word in Surprise:\n",
    "            surprise+=freq\n",
    "        if word in Trust:\n",
    "            trust+=freq\n",
    "            \n",
    "    emotion_info = {\n",
    "        'positive': positive,\n",
    "        'negative': negative,\n",
    "        'anger': anger,\n",
    "        'anticipation': anticipation,\n",
    "        'disgust': disgust,\n",
    "        'fear':fear,\n",
    "        'joy':joy,\n",
    "        'sadness':sadness,\n",
    "        'surprise':surprise,\n",
    "        'trust':trust,\n",
    "        'length':len(wordlist)\n",
    "    }\n",
    "    indexs = ['length', 'positive', 'negative', 'anger', 'anticipation','disgust','fear','joy','sadness','surprise','trust']\n",
    "    return pd.Series(emotion_info, index=indexs)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-30T12:35:02.118704Z",
     "start_time": "2020-10-30T12:35:01.372815Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Loading model from cache /var/folders/8b/hhnbt0nd4zsg2qhxc28q23w80000gn/T/jieba.cache\n",
      "Loading model cost 0.730 seconds.\n",
      "Prefix dict has been built successfully.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "length          25\n",
       "positive         1\n",
       "negative         2\n",
       "anger            1\n",
       "anticipation     0\n",
       "disgust          1\n",
       "fear             1\n",
       "joy              0\n",
       "sadness          1\n",
       "surprise         0\n",
       "trust            3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "emotion_caculate(text='这个国家再对这些制造假冒伪劣食品药品的人手软的话，那后果真的会相当糟糕。坐牢？从快判个死刑')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}