Mendeley_SA.ipynb

{"cells":[{"cell_type":"code","execution_count":2,"metadata":{"id":"1U7CFXdNUTW3","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1666461744168,"user_tz":-330,"elapsed":30582,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"5fec4b9c-b515-4ab1-f8c7-dc0b903b9c64"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":3,"metadata":{"id":"EM1_aoupZXqi","executionInfo":{"status":"ok","timestamp":1666461744169,"user_tz":-330,"elapsed":14,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"outputs":[],"source":["import numpy as np\n","import pandas as pd\n","%matplotlib inline\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import sys"]},{"cell_type":"code","source":["data = pd.read_csv('/content/drive/MyDrive/Capstone Project/Data/MENDELEY_DATA.csv')\n","data.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"evnvg7NiNwA7","executionInfo":{"status":"ok","timestamp":1666462162731,"user_tz":-330,"elapsed":4515,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"1a924b63-f22b-4b2d-cd35-91a719cb5c8e"},"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                             OG_Text Bully  \\\n","0  `- This is not ``creative``.  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Those are the dic...   \n","1  ` :: the term ``standard model`` is itself les...   \n","2  True or false, the situation as of March was s...   \n","3  Next, maybe you could work on being less conde...   \n","4                This page will need disambiguation.   \n","\n","                                   Preprocessed_Text  \n","0  creativ dictionari definit term insur ensur pr...  \n","1  term standard model npov think prefer new-ag s...  \n","2  true fals situat march saudi propos land peac ...  \n","3  mayb work condescend suggest read name convent...  \n","4                                page need disambigu  "],"text/html":["\n","  <div id=\"df-5eeedec2-311d-42ce-ac5a-3a74eb47a7ee\">\n","    <div class=\"colab-df-container\">\n","      <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>OG_Text</th>\n","      <th>Bully</th>\n","      <th>Clean_Text</th>\n","      <th>Preprocessed_Text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>`- This is not ``creative``.  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Those are the dic...</td>\n","      <td>creativ dictionari definit term insur ensur pr...</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>`  :: the term ``standard model`` is itself le...</td>\n","      <td>None</td>\n","      <td>` :: the term ``standard model`` is itself les...</td>\n","      <td>term standard model npov think prefer new-ag s...</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>True or false, the situation as of March 200...</td>\n","      <td>None</td>\n","      <td>True or false, the situation as of March was s...</td>\n","      <td>true fals situat march saudi propos land peac ...</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Next, maybe you could work on being less cond...</td>\n","      <td>None</td>\n","      <td>Next, maybe you could work on being less conde...</td>\n","      <td>mayb work condescend suggest read name convent...</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>This page will need disambiguation.</td>\n","      <td>None</td>\n","      <td>This page will need disambiguation.</td>\n","      <td>page need disambigu</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5eeedec2-311d-42ce-ac5a-3a74eb47a7ee')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-5eeedec2-311d-42ce-ac5a-3a74eb47a7ee button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-5eeedec2-311d-42ce-ac5a-3a74eb47a7ee');\n","          const dataTable =\n","            await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                     [key], {});\n","          if (!dataTable) return;\n","\n","          const docLinkHtml = 'Like what you see? Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n","  "]},"metadata":{},"execution_count":16}]},{"cell_type":"code","source":["data = data.astype(str)"],"metadata":{"id":"plDTuFd94kpE","executionInfo":{"status":"ok","timestamp":1666462162732,"user_tz":-330,"elapsed":15,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":17,"outputs":[]},{"cell_type":"code","source":["len(data)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"XVCvpVc6PCR4","executionInfo":{"status":"ok","timestamp":1666462162734,"user_tz":-330,"elapsed":17,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"14b1e3f3-b749-4b60-a30b-4c161cba2fe4"},"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/plain":["331768"]},"metadata":{},"execution_count":18}]},{"cell_type":"markdown","source":["#**IMPORT NLTK**"],"metadata":{"id":"NPOWiDmEWpm8"}},{"cell_type":"code","source":["import nltk\n","nltk.download()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gdtX8XdKWr__","executionInfo":{"status":"ok","timestamp":1666461821733,"user_tz":-330,"elapsed":71862,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"a3788f28-3026-41ef-97cf-1bf8e3a7df9d"},"execution_count":6,"outputs":[{"name":"stdout","output_type":"stream","text":["NLTK Downloader\n","---------------------------------------------------------------------------\n","    d) Download   l) List    u) Update   c) Config   h) Help   q) Quit\n","---------------------------------------------------------------------------\n","Downloader> d\n","\n","Download which package (l=list; x=cancel)?\n","  Identifier> all\n"]},{"output_type":"stream","name":"stderr","text":["    Downloading collection 'all'\n","       | \n","       | Downloading package abc to /root/nltk_data...\n","       |   Unzipping corpora/abc.zip.\n","       | Downloading package alpino to /root/nltk_data...\n","       |   Unzipping corpora/alpino.zip.\n","       | Downloading package averaged_perceptron_tagger to\n","       |     /root/nltk_data...\n","       |   Unzipping taggers/averaged_perceptron_tagger.zip.\n","       | Downloading package averaged_perceptron_tagger_ru to\n","       |     /root/nltk_data...\n","       |   Unzipping taggers/averaged_perceptron_tagger_ru.zip.\n","       | Downloading package basque_grammars to /root/nltk_data...\n","       |   Unzipping grammars/basque_grammars.zip.\n","       | Downloading package biocreative_ppi to /root/nltk_data...\n","       |   Unzipping corpora/biocreative_ppi.zip.\n","       | Downloading package bllip_wsj_no_aux to /root/nltk_data...\n","       |   Unzipping models/bllip_wsj_no_aux.zip.\n","       | Downloading package book_grammars to /root/nltk_data...\n","       |   Unzipping grammars/book_grammars.zip.\n","       | Downloading package brown to /root/nltk_data...\n","       |   Unzipping corpora/brown.zip.\n","       | Downloading package brown_tei to /root/nltk_data...\n","       |   Unzipping corpora/brown_tei.zip.\n","       | Downloading package cess_cat to /root/nltk_data...\n","       |   Unzipping corpora/cess_cat.zip.\n","       | Downloading package cess_esp to /root/nltk_data...\n","       |   Unzipping corpora/cess_esp.zip.\n","       | Downloading package chat80 to /root/nltk_data...\n","       |   Unzipping corpora/chat80.zip.\n","       | Downloading package city_database to /root/nltk_data...\n","       |   Unzipping corpora/city_database.zip.\n","       | Downloading package cmudict to /root/nltk_data...\n","       |   Unzipping corpora/cmudict.zip.\n","       | Downloading package comparative_sentences to\n","       |     /root/nltk_data...\n","       |   Unzipping corpora/comparative_sentences.zip.\n","       | Downloading package comtrans to /root/nltk_data...\n","       | Downloading package conll2000 to /root/nltk_data...\n","       |   Unzipping corpora/conll2000.zip.\n","       | Downloading package conll2002 to /root/nltk_data...\n","       |   Unzipping corpora/conll2002.zip.\n","       | Downloading package conll2007 to /root/nltk_data...\n","       | Downloading package crubadan to 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package mac_morpho to /root/nltk_data...\n","       |   Unzipping corpora/mac_morpho.zip.\n","       | Downloading package machado to /root/nltk_data...\n","       | Downloading package masc_tagged to /root/nltk_data...\n","       | Downloading package maxent_ne_chunker to /root/nltk_data...\n","       |   Unzipping chunkers/maxent_ne_chunker.zip.\n","       | Downloading package maxent_treebank_pos_tagger to\n","       |     /root/nltk_data...\n","       |   Unzipping taggers/maxent_treebank_pos_tagger.zip.\n","       | Downloading package moses_sample to /root/nltk_data...\n","       |   Unzipping models/moses_sample.zip.\n","       | Downloading package movie_reviews to /root/nltk_data...\n","       |   Unzipping corpora/movie_reviews.zip.\n","       | Downloading package mte_teip5 to /root/nltk_data...\n","       |   Unzipping corpora/mte_teip5.zip.\n","       | Downloading package mwa_ppdb to /root/nltk_data...\n","       |   Unzipping misc/mwa_ppdb.zip.\n","       | Downloading package names to /root/nltk_data...\n","       |   Unzipping corpora/names.zip.\n","       | Downloading package nombank.1.0 to /root/nltk_data...\n","       | Downloading package nonbreaking_prefixes to\n","       |     /root/nltk_data...\n","       |   Unzipping corpora/nonbreaking_prefixes.zip.\n","       | Downloading package nps_chat to /root/nltk_data...\n","       |   Unzipping corpora/nps_chat.zip.\n","       | Downloading package omw to /root/nltk_data...\n","       | Downloading package omw-1.4 to /root/nltk_data...\n","       | Downloading package opinion_lexicon to /root/nltk_data...\n","       |   Unzipping corpora/opinion_lexicon.zip.\n","       | Downloading package panlex_swadesh to /root/nltk_data...\n","       | Downloading package paradigms to /root/nltk_data...\n","       |   Unzipping corpora/paradigms.zip.\n","       | Downloading package pe08 to /root/nltk_data...\n","       |   Unzipping corpora/pe08.zip.\n","       | Downloading package perluniprops to 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to /root/nltk_data...\n","       |   Unzipping models/word2vec_sample.zip.\n","       | Downloading package wordnet to /root/nltk_data...\n","       | Downloading package wordnet2021 to /root/nltk_data...\n","       | Downloading package wordnet31 to /root/nltk_data...\n","       | Downloading package wordnet_ic to /root/nltk_data...\n","       |   Unzipping corpora/wordnet_ic.zip.\n","       | Downloading package words to /root/nltk_data...\n","       |   Unzipping corpora/words.zip.\n","       | Downloading package ycoe to /root/nltk_data...\n","       |   Unzipping corpora/ycoe.zip.\n","       | \n","     Done downloading collection all\n"]},{"name":"stdout","output_type":"stream","text":["\n","---------------------------------------------------------------------------\n","    d) Download   l) List    u) Update   c) Config   h) Help   q) Quit\n","---------------------------------------------------------------------------\n","Downloader> q\n"]},{"output_type":"execute_result","data":{"text/plain":["True"]},"metadata":{},"execution_count":6}]},{"cell_type":"markdown","source":["#**WORD COUNT**"],"metadata":{"id":"VKoDEW6bXMst"}},{"cell_type":"code","source":["data['Word count'] = [len(i) for i in data['Clean_Text']]\n","data.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"4hi-HlGmXSPb","executionInfo":{"status":"ok","timestamp":1666462179631,"user_tz":-330,"elapsed":9,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"da560a5c-472e-4af6-d074-6258acf8757d"},"execution_count":19,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                             OG_Text Bully  \\\n","0  `- This is not ``creative``.  Those are the di...  None   \n","1  `  :: the term ``standard model`` is itself le...  None   \n","2    True or false, the situation as of March 200...  None   \n","3   Next, maybe you could work on being less cond...  None   \n","4               This page will need disambiguation.   None   \n","\n","                                          Clean_Text  \\\n","0  `- This is not ``creative``. Those are the dic...   \n","1  ` :: the term ``standard model`` is itself les...   \n","2  True or false, the situation as of March was s...   \n","3  Next, maybe you could work on being less conde...   \n","4                This page will need disambiguation.   \n","\n","                                   Preprocessed_Text  Word count  \n","0  creativ dictionari definit term insur ensur pr...        2362  \n","1  term standard model npov think prefer new-ag s...         707  \n","2  true fals situat march saudi propos land peac ...         321  \n","3  mayb work condescend suggest read name convent...         421  \n","4                                page need disambigu          35  "],"text/html":["\n","  <div id=\"df-a3435eaf-9633-4bfe-9a56-d6f47137b925\">\n","    <div class=\"colab-df-container\">\n","      <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>OG_Text</th>\n","      <th>Bully</th>\n","      <th>Clean_Text</th>\n","      <th>Preprocessed_Text</th>\n","      <th>Word count</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>`- This is not ``creative``.  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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["# **VADER SENTIMENT ANALYSIS**"],"metadata":{"id":"KHBujEjpViot"}},{"cell_type":"code","source":["!pip install vaderSentiment"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"kQTjrCk4aFyz","executionInfo":{"status":"ok","timestamp":1666462196083,"user_tz":-330,"elapsed":3180,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"233c1eb1-3c2c-4089-8a09-f57847db0114"},"execution_count":21,"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: vaderSentiment in /usr/local/lib/python3.7/dist-packages (3.3.2)\n","Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from vaderSentiment) (2.23.0)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->vaderSentiment) (2022.9.24)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->vaderSentiment) (3.0.4)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->vaderSentiment) (2.10)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->vaderSentiment) (1.24.3)\n"]}]},{"cell_type":"code","source":["from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer"],"metadata":{"id":"QzIBSH5SXCR6","executionInfo":{"status":"ok","timestamp":1666462196084,"user_tz":-330,"elapsed":38,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":22,"outputs":[]},{"cell_type":"markdown","source":["https://analyticsindiamag.com/sentiment-analysis-made-easy-using-vader/\n","\n","The more Compound score closer to +1, the higher the positivity of the text. Above text is 49.2% Positive, 0% Negative, 50.8% Neutral."],"metadata":{"id":"YGLR_5ViaOFi"}},{"cell_type":"code","source":["def sentiment(scores):\n","  del scores['compound']\n","  maxi = max(zip(scores.values(), scores.keys()))[1]\n","  if maxi == 'pos' : return \"Positive\"\n","  elif maxi == 'neg' : return \"Negative\"\n","  elif maxi == 'neu'  : return \"Neutral\"\n","\n","def compound(scores):\n","  return scores['compound']\n","\n","def positive(scores):\n","  return scores['pos']\n","\n","def negative(scores):\n","  return scores['neg']\n","\n","def neutral(scores):\n","  return scores['neu']\n","\n","def vader(doc, col):\n","  analyzer = SentimentIntensityAnalyzer()\n","  doc['Sentiment'] = doc[col].apply(lambda x: sentiment(analyzer.polarity_scores(x)))\n","  doc['Compound Score'] = doc[col].apply(lambda x: compound(analyzer.polarity_scores(x)))\n","  doc['Positive Score'] = doc[col].apply(lambda x: positive(analyzer.polarity_scores(x)))\n","  doc['Negative Score'] = doc[col].apply(lambda x: negative(analyzer.polarity_scores(x)))\n","  doc['Neutral Score'] = doc[col].apply(lambda x: neutral(analyzer.polarity_scores(x)))\n","\n","  return doc"],"metadata":{"id":"E1yTjr3JaKeX","executionInfo":{"status":"ok","timestamp":1666462196085,"user_tz":-330,"elapsed":38,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":23,"outputs":[]},{"cell_type":"code","source":["data_sen = vader(data, 'Clean_Text')"],"metadata":{"id":"GfCceCMxaMeG","executionInfo":{"status":"ok","timestamp":1666463593171,"user_tz":-330,"elapsed":1397123,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":24,"outputs":[]},{"cell_type":"code","source":["data_sen.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":337},"id":"s44GK6byaVeV","executionInfo":{"status":"ok","timestamp":1666463593173,"user_tz":-330,"elapsed":163,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"ea1f0f1c-7417-4d62-a916-e35b416600ae"},"execution_count":25,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                             OG_Text Bully  \\\n","0  `- This is not ``creative``.  Those are the di...  None   \n","1  `  :: the term ``standard model`` is itself le...  None   \n","2    True or false, the situation as of March 200...  None   \n","3   Next, maybe you could work on being less cond...  None   \n","4               This page will need disambiguation.   None   \n","\n","                                          Clean_Text  \\\n","0  `- This is not ``creative``. Those are the dic...   \n","1  ` :: the term ``standard model`` is itself les...   \n","2  True or false, the situation as of March was s...   \n","3  Next, maybe you could work on being less conde...   \n","4                This page will need disambiguation.   \n","\n","                                   Preprocessed_Text  Word count Sentiment  \\\n","0  creativ dictionari definit term insur ensur pr...        2362   Neutral   \n","1  term standard model npov think prefer new-ag s...         707   Neutral   \n","2  true fals situat march saudi propos land peac ...         321   Neutral   \n","3  mayb work condescend suggest read name convent...         421   Neutral   \n","4                                page need disambigu          35   Neutral   \n","\n","   Compound Score  Positive Score  Negative Score  Neutral Score  \n","0         -0.9895           0.092           0.164          0.744  \n","1          0.7015           0.077           0.041          0.882  \n","2          0.7430           0.101           0.000          0.899  \n","3         -0.6269           0.100           0.157          0.744  \n","4          0.0000           0.000           0.000          1.000  "],"text/html":["\n","  <div id=\"df-c7a50fcf-f7c0-4fff-9fb7-4a87fa3d8973\">\n","    <div class=\"colab-df-container\">\n","      <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>OG_Text</th>\n","      <th>Bully</th>\n","      <th>Clean_Text</th>\n","      <th>Preprocessed_Text</th>\n","      <th>Word count</th>\n","      <th>Sentiment</th>\n","      <th>Compound Score</th>\n","      <th>Positive Score</th>\n","      <th>Negative Score</th>\n","      <th>Neutral Score</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>`- This is not ``creative``.  Those are the di...</td>\n","      <td>None</td>\n","      <td>`- This is not ``creative``. Those are the dic...</td>\n","      <td>creativ dictionari definit term insur ensur pr...</td>\n","      <td>2362</td>\n","      <td>Neutral</td>\n","      <td>-0.9895</td>\n","      <td>0.092</td>\n","      <td>0.164</td>\n","      <td>0.744</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>`  :: the term ``standard model`` is itself le...</td>\n","      <td>None</td>\n","      <td>` :: the term ``standard model`` is itself les...</td>\n","      <td>term standard model npov think prefer new-ag s...</td>\n","      <td>707</td>\n","      <td>Neutral</td>\n","      <td>0.7015</td>\n","      <td>0.077</td>\n","      <td>0.041</td>\n","      <td>0.882</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>True or false, the situation as of March 200...</td>\n","      <td>None</td>\n","      <td>True or false, the situation as of March was s...</td>\n","      <td>true fals situat march saudi propos land peac ...</td>\n","      <td>321</td>\n","      <td>Neutral</td>\n","      <td>0.7430</td>\n","      <td>0.101</td>\n","      <td>0.000</td>\n","      <td>0.899</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Next, maybe you could work on being less cond...</td>\n","      <td>None</td>\n","      <td>Next, maybe you could work on being less conde...</td>\n","      <td>mayb work condescend suggest read name convent...</td>\n","      <td>421</td>\n","      <td>Neutral</td>\n","      <td>-0.6269</td>\n","      <td>0.100</td>\n","      <td>0.157</td>\n","      <td>0.744</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>This page will need disambiguation.</td>\n","      <td>None</td>\n","      <td>This page will need disambiguation.</td>\n","      <td>page need disambigu</td>\n","      <td>35</td>\n","      <td>Neutral</td>\n","      <td>0.0000</td>\n","      <td>0.000</td>\n","      <td>0.000</td>\n","      <td>1.000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c7a50fcf-f7c0-4fff-9fb7-4a87fa3d8973')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-c7a50fcf-f7c0-4fff-9fb7-4a87fa3d8973 button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["#**COMPARISON**"],"metadata":{"id":"S5BtuW5FqXnW"}},{"cell_type":"code","source":["comp = data_sen"],"metadata":{"id":"79sBK_MdqjF8","executionInfo":{"status":"ok","timestamp":1666463593199,"user_tz":-330,"elapsed":155,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":28,"outputs":[]},{"cell_type":"code","source":["label = {'Positive':'Proper', 'Neutral':'Proper', 'Negative':'Improper'}\n","comp['SA'] = comp['Sentiment'].apply(lambda x: label[x])"],"metadata":{"id":"jBedRywbqWuM","executionInfo":{"status":"ok","timestamp":1666463593200,"user_tz":-330,"elapsed":155,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":29,"outputs":[]},{"cell_type":"code","source":["label = {'None': 'Proper', 'Toxic':'Improper', 'Aggression':'Improper', 'Sexism':'Improper', 'Racism':'Improper', 'Misconduct':'Improper'}\n","comp['OG'] = comp['Bully'].apply(lambda x: label[x])"],"metadata":{"id":"lg4IA8EtqQeP","executionInfo":{"status":"ok","timestamp":1666463593202,"user_tz":-330,"elapsed":156,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":30,"outputs":[]},{"cell_type":"code","source":["comp['SA'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"V9SlWf6brjb9","executionInfo":{"status":"ok","timestamp":1666463593203,"user_tz":-330,"elapsed":155,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"79d4dca4-8ca5-4062-ac4e-1c13054295ff"},"execution_count":31,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Proper      325492\n","Improper      6276\n","Name: SA, dtype: int64"]},"metadata":{},"execution_count":31}]},{"cell_type":"code","source":["comp['SA'].value_counts().plot.pie(explode = [0,0.1], autopct ='%1.1f%%').set_title('Proper vs. Improper')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":281},"id":"8nxUQnwPrjYg","executionInfo":{"status":"ok","timestamp":1666463593949,"user_tz":-330,"elapsed":896,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"c3c6c4ef-83fc-4389-bdb3-c194233a7c49"},"execution_count":32,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Proper vs. Improper')"]},"metadata":{},"execution_count":32},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 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\n"},"metadata":{}}]},{"cell_type":"code","source":["comp['OG'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"rYwE4Qg1rjV9","executionInfo":{"status":"ok","timestamp":1666463593952,"user_tz":-330,"elapsed":118,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"fee36480-abbb-4688-e5f9-263f58a23102"},"execution_count":33,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Proper      289056\n","Improper     42712\n","Name: OG, dtype: int64"]},"metadata":{},"execution_count":33}]},{"cell_type":"code","source":["comp['OG'].value_counts().plot.pie(explode = [0,0.1], autopct ='%1.1f%%').set_title('Proper vs. Improper')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":281},"id":"tiNBpZeqrjTV","executionInfo":{"status":"ok","timestamp":1666463593955,"user_tz":-330,"elapsed":115,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}},"outputId":"90d45aee-3147-43c7-f857-daa3d26b0585"},"execution_count":34,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Proper vs. Improper')"]},"metadata":{},"execution_count":34},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["#**HIDE**"],"metadata":{"id":"Ygy5lo9_sFHx"}},{"cell_type":"code","source":["data_mod = data_sen"],"metadata":{"id":"yCPA316hmJlP","executionInfo":{"status":"aborted","timestamp":1666461665587,"user_tz":-330,"elapsed":54,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["count = 0\n","for i in range(len(data_mod)):\n","  if data_mod.Sentiment[i] == 'Neutral' and data_mod.Bully[i] != 'None' and data_mod.Bully[i] != '': \n","    data_mod.Sentiment[i] = 'Negative'\n","    count = count+1\n","  elif data_mod.Sentiment[i] == 'Positive' and data_mod.Bully[i] != 'None' and data_mod.Bully[i] != '': \n","    data_mod.Sentiment[i] = 'Negative'\n","    count = count+1\n","\n","print(count)"],"metadata":{"id":"qe80vdUrbRYS","executionInfo":{"status":"aborted","timestamp":1666461665588,"user_tz":-330,"elapsed":55,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["data_mod['Sentiment'].value_counts()"],"metadata":{"id":"mAgOu91WQNPQ","executionInfo":{"status":"aborted","timestamp":1666461665589,"user_tz":-330,"elapsed":56,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["data_mod['Sentiment'].value_counts().plot.pie(autopct ='%1.1f%%').set_title('Sentiment value Counts')"],"metadata":{"id":"0l3qSpdMQOKj","executionInfo":{"status":"aborted","timestamp":1666461665590,"user_tz":-330,"elapsed":56,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["# **TRIAL CONV ID**"],"metadata":{"id":"oTJ5KAGoVdON"}},{"cell_type":"markdown","metadata":{"id":"UJBLyfNs9_SB"},"source":["*   1st-predator\n","*   2nd - if not exists in previous, then complement, else take existing role \n","*   Ensure the 1st in EVERY CONVERSATION IS PREDATOR: Verify this\n","*   Give Conversation ID based on conv and not just zip\n","\n","\n","\n","\n","\n","\n","\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"-XUEHgJ_wOEW","executionInfo":{"status":"aborted","timestamp":1666461665591,"user_tz":-330,"elapsed":57,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"outputs":[],"source":["category = ['Predator', 'Victim']\n","data['Role'] = ''\n","data[:2]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"pce2EZ1A1T5G","executionInfo":{"status":"aborted","timestamp":1666461665592,"user_tz":-330,"elapsed":58,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"outputs":[],"source":["def compliment(i):\n","  if data['Role'][i-1] == 'Predator': return 'Victim'\n","  else: return 'Predator'"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":59,"status":"aborted","timestamp":1666461665593,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"},"user_tz":-330},"id":"TteytHuUvEAw"},"outputs":[],"source":["data['Role'][0] = category[0]\n","for i in range(1, len(data)):\n","  if data['Author ID'][i] in list(data['Author ID'][:i]):\n","    a = [j for j in data.index[data['Author ID']==data['Author ID'][i]] if j<i][-1]\n","    data['Role'][i] = data['Role'][a]\n","  else: \n","    data['Role'][i] = compliment(i)"]},{"cell_type":"code","source":["col = ['conversation id', 'message', 'author', 'time', 'text']"],"metadata":{"id":"y0DHVolySkFw","executionInfo":{"status":"aborted","timestamp":1666461665596,"user_tz":-330,"elapsed":62,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!pip install untangle"],"metadata":{"id":"9FB-yGc3TE67","executionInfo":{"status":"aborted","timestamp":1666461665598,"user_tz":-330,"elapsed":64,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"execution_count":null,"outputs":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"selOAwuF1rdo","executionInfo":{"status":"aborted","timestamp":1666461665599,"user_tz":-330,"elapsed":65,"user":{"displayName":"PANIGRAHI BHARATI","userId":"17428908446995148453"}}},"outputs":[],"source":["import untangle, csv\n","\n","# PARSE XML FILE\n","xml = untangle.parse(train_path)\n","\n","# CREATE CSV FILE\n","csvfile = open(\"/content/drive/MyDrive/Capstone Project/data.csv\",'w',encoding='utf-8')\n","csvfile_writer = csv.writer(csvfile)\n","\n","# ADD HEADER\n","csvfile_writer.writerow(col)\n","\n","# FOR EACH EMPLOYEE\n","for employee in xml.conversations:\n","\n","    # EXTRACT EMPLOYEE DETAILS\n","    csv_line = [employee.id.cdata, employee.message.cdata, employee.author.cdata, employee.time.cdata, employee.text.cdata]\n","\n","    # ADD NEW ROW TO CSV FILE\n","    csvfile_writer.writerow(csv_line)"]}],"metadata":{"colab":{"collapsed_sections":["Ygy5lo9_sFHx","oTJ5KAGoVdON"],"provenance":[],"authorship_tag":"ABX9TyN1LNlQClLgHt+NVmZP4M05"},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}