PostCovid.ipynb

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      "name": "PostCovid.ipynb",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/smriti-nayak/Analysing-Mental-Health-during-COVID/blob/main/PostCovid.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ykXT5O-Mjsuv"
      },
      "source": [
        "## 1. Loading and Exploring the Dataset"
      ]
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    {
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      "source": [
        "import pandas as pd\n",
        "file = '/content/drive/My Drive/Datasets/Post Covid Mini.csv'\n",
        "\n",
        "import chardet\n",
        "with open(file, 'rb') as rawdata:\n",
        "    result = chardet.detect(rawdata.read(100000))\n",
        "result\n",
        "\n",
        "data = pd.read_csv(file, encoding='Windows-1252')\n",
        "data.head(15)"
      ],
      "execution_count": null,
      "outputs": [
        {
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          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tweets</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>@janie_crawford ha...yes ma'am...been branding...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>I really miss XYZ since 2016 i have Post anime...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>boys before flowers is AWESOME. specially so y...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>RT: #BipolarHotline: National #Suicide Hotline...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Only 2 days of sophmore year left! thank godd ...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>There's #noshame in talking about other illnes...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ok so like... how am i supposed to tell my mom...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Searching for Susan Boyle on Microsoft's Bing ...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>@PressSec @FoxNews @EricFolmer When Obama came...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Good morning my twitter friends... Time for wo...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>this movie just worsened my depression tbh :) ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>I need a job!! I hate being unemployed #unempl...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>@BananaAnna2008 @mikequad I TOTALLY AGREE WITH...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>It's hard for someone who has depression to ad...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>I understand  You just gotta work on it! haha....</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               tweets  label\n",
              "0   @janie_crawford ha...yes ma'am...been branding...      0\n",
              "1   I really miss XYZ since 2016 i have Post anime...      1\n",
              "2   boys before flowers is AWESOME. specially so y...      0\n",
              "3   RT: #BipolarHotline: National #Suicide Hotline...      1\n",
              "4   Only 2 days of sophmore year left! thank godd ...      0\n",
              "5   There's #noshame in talking about other illnes...      1\n",
              "6   ok so like... how am i supposed to tell my mom...      1\n",
              "7   Searching for Susan Boyle on Microsoft's Bing ...      0\n",
              "8   @PressSec @FoxNews @EricFolmer When Obama came...      1\n",
              "9   Good morning my twitter friends... Time for wo...      0\n",
              "10  this movie just worsened my depression tbh :) ...      1\n",
              "11  I need a job!! I hate being unemployed #unempl...      1\n",
              "12  @BananaAnna2008 @mikequad I TOTALLY AGREE WITH...      0\n",
              "13  It's hard for someone who has depression to ad...      1\n",
              "14  I understand  You just gotta work on it! haha....      0"
            ]
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          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
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      },
      "source": [
        "data.tweets[:15]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     @janie_crawford ha...yes ma'am...been branding...\n",
              "1     I really miss XYZ since 2016 i have Post anime...\n",
              "2     boys before flowers is AWESOME. specially so y...\n",
              "3     RT: #BipolarHotline: National #Suicide Hotline...\n",
              "4     Only 2 days of sophmore year left! thank godd ...\n",
              "5     There's #noshame in talking about other illnes...\n",
              "6     ok so like... how am i supposed to tell my mom...\n",
              "7     Searching for Susan Boyle on Microsoft's Bing ...\n",
              "8     @PressSec @FoxNews @EricFolmer When Obama came...\n",
              "9     Good morning my twitter friends... Time for wo...\n",
              "10    this movie just worsened my depression tbh :) ...\n",
              "11    I need a job!! I hate being unemployed #unempl...\n",
              "12    @BananaAnna2008 @mikequad I TOTALLY AGREE WITH...\n",
              "13    It's hard for someone who has depression to ad...\n",
              "14    I understand  You just gotta work on it! haha....\n",
              "Name: tweets, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
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          "height": 34
        }
      },
      "source": [
        "print(data.tweets[11])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "I need a job!! I hate being unemployed #unemployed #corona #jobs #lockdown #crisis\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
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      "source": [
        "data.shape"
      ],
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              "(449, 2)"
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          "metadata": {
            "tags": []
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xDWaZRspoPE5"
      },
      "source": [
        "### 2. Preprocessing the Data\n",
        "\n",
        "*   Lowercasing\n",
        "*   Removal of non-alphabetical characters\n",
        "*   Tokenization\n",
        "*   Stop-word removal\n",
        "*   Stemming"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RqfsAd6foThp",
        "outputId": "8d459b29-b1c8-4d4a-e2c0-222448803878",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 154
        }
      },
      "source": [
        "import nltk\n",
        "nltk.download('stopwords')\n",
        "nltk.download('punkt')\n",
        "nltk.download('wordnet')\n",
        "import re\n",
        "import string\n",
        "\n",
        "from nltk.tokenize import word_tokenize\n",
        "from nltk.corpus import stopwords\n",
        "from nltk.stem import PorterStemmer\n",
        "\n",
        "stop = stopwords.words('english')\n",
        "punc = string.punctuation\n",
        "print(stop)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n",
            "['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n"
          ],
          "name": "stdout"
        }
      ]
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        "id": "HXJGL0_VoaKv",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Lowercasing\n",
        "data['tweets'] = data['tweets'].str.lower()\n",
        "\n",
        "print(data.tweets[11])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "i need a job!! i hate being unemployed #unemployed #corona #jobs #lockdown #crisis\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
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        "id": "BlbXR6Yrorz8",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Removing non-alphabetic characters\n",
        "data['tweets'] = data['tweets'].str.replace('[^a-z\\s]', '')\n",
        "\n",
        "print(data.tweets[11])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "i need a job i hate being unemployed unemployed corona jobs lockdown crisis\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sl9tFmLUo6e_",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Tokennization\n",
        "data['tweets'] = data['tweets'].apply(word_tokenize)\n",
        "\n",
        "print(data.tweets[11])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['i', 'need', 'a', 'job', 'i', 'hate', 'being', 'unemployed', 'unemployed', 'corona', 'jobs', 'lockdown', 'crisis']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ix9KTgN-pHW-"
      },
      "source": [
        "# Removing stopwords and Stemming\n",
        "\n",
        "stemmer = PorterStemmer()\n",
        "\n",
        "def clean(df):\n",
        "  clean_tokens = []\n",
        "  for word in df:\n",
        "    if(word not in stop and word not in punc):\n",
        "      clean_tokens.append(stemmer.stem(word))\n",
        "  return clean_tokens\n",
        "\n",
        "data['tweets'] = data['tweets'].apply(clean)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nGtzXg1DpPCX",
        "outputId": "f595dbb2-3b37-4b7e-cd76-9e7d54abb2f8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "print(data.tweets[11])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['need', 'job', 'hate', 'unemploy', 'unemploy', 'corona', 'job', 'lockdown', 'crisi']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
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        "id": "kLO0KOtFpUn1",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 491
        }
      },
      "source": [
        "data.head(15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tweets</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[janiecrawford, hay, maambeen, brand, whiletha...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[realli, miss, xyz, sinc, post, anim, depress,...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[boy, flower, awesom, special, yijung, cha, ga...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[rt, bipolarhotlin, nation, suicid, hotlin, lo...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[day, sophmor, year, left, thank, godd, lt, tx...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>[there, nosham, talk, ill, depress, notalon, k...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>[ok, like, suppos, tell, mom, depress, without...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>[search, susan, boyl, microsoft, bing, twiligh...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>[presssec, foxnew, ericfolm, obama, came, offi...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>[good, morn, twitter, friend, time, work, unem...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>[movi, worsen, depress, tbh, wan, na, die, pic...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>[need, job, hate, unemploy, unemploy, corona, ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>[bananaanna, mikequad, total, agre, anna]</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>[hard, someon, depress, admit, depress, stayho...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>[understand, got, ta, work, haha, chew, gum, f...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               tweets  label\n",
              "0   [janiecrawford, hay, maambeen, brand, whiletha...      0\n",
              "1   [realli, miss, xyz, sinc, post, anim, depress,...      1\n",
              "2   [boy, flower, awesom, special, yijung, cha, ga...      0\n",
              "3   [rt, bipolarhotlin, nation, suicid, hotlin, lo...      1\n",
              "4   [day, sophmor, year, left, thank, godd, lt, tx...      0\n",
              "5   [there, nosham, talk, ill, depress, notalon, k...      1\n",
              "6   [ok, like, suppos, tell, mom, depress, without...      1\n",
              "7   [search, susan, boyl, microsoft, bing, twiligh...      0\n",
              "8   [presssec, foxnew, ericfolm, obama, came, offi...      1\n",
              "9   [good, morn, twitter, friend, time, work, unem...      0\n",
              "10  [movi, worsen, depress, tbh, wan, na, die, pic...      1\n",
              "11  [need, job, hate, unemploy, unemploy, corona, ...      1\n",
              "12          [bananaanna, mikequad, total, agre, anna]      0\n",
              "13  [hard, someon, depress, admit, depress, stayho...      1\n",
              "14  [understand, got, ta, work, haha, chew, gum, f...      0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FzjJtGrIpdcY"
      },
      "source": [
        "### 3. Analysis of Data (Word Frequency Distribution Analysis)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rh9AczW4pie1"
      },
      "source": [
        "from nltk.probability import FreqDist\n",
        "\n",
        "fdist = FreqDist()\n",
        "for doc in data.tweets:\n",
        "  for word in doc:\n",
        "    fdist[word] +=1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iB7ltJSgpq8P",
        "outputId": "79a026b1-f6ea-498a-fbd7-f3114839cf27",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "source": [
        "vocab = fdist.most_common(50)\n",
        "print(vocab)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[('depress', 114), ('im', 50), ('get', 33), ('like', 32), ('day', 31), ('go', 31), ('good', 25), ('time', 24), ('thing', 24), ('think', 23), ('got', 22), ('anxieti', 22), ('love', 20), ('u', 19), ('lockdown', 18), ('make', 18), ('quarantin', 18), ('dont', 18), ('see', 18), ('one', 18), ('tri', 17), ('lol', 17), ('great', 16), ('ill', 16), ('thank', 15), ('new', 15), ('that', 15), ('life', 14), ('stayhom', 14), ('feel', 14), ('covid', 14), ('viru', 14), ('us', 13), ('unemploy', 13), ('job', 13), ('cant', 13), ('everyon', 13), ('know', 13), ('realli', 12), ('could', 12), ('face', 12), ('last', 12), ('mental', 11), ('live', 11), ('friend', 11), ('corona', 11), ('peopl', 11), ('hope', 11), ('home', 11), ('night', 11)]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5hws40_wp0Hv",
        "outputId": "2edf8787-697f-4283-f172-f7a3a1795871",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "source": [
        "# Storing the most common 50 words in a list\n",
        "\n",
        "lst = [tup[0] for tup in vocab]\n",
        "print(lst)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['depress', 'im', 'get', 'like', 'day', 'go', 'good', 'time', 'thing', 'think', 'got', 'anxieti', 'love', 'u', 'lockdown', 'make', 'quarantin', 'dont', 'see', 'one', 'tri', 'lol', 'great', 'ill', 'thank', 'new', 'that', 'life', 'stayhom', 'feel', 'covid', 'viru', 'us', 'unemploy', 'job', 'cant', 'everyon', 'know', 'realli', 'could', 'face', 'last', 'mental', 'live', 'friend', 'corona', 'peopl', 'hope', 'home', 'night']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XdmRroIccAK8",
        "outputId": "7a05d0f1-d033-4dce-914c-429e06e27544",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        }
      },
      "source": [
        "#Generate WordCloud of the 50 most frequent \n",
        "from wordcloud import WordCloud\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "words=\"\"\n",
        "for word in lst:\n",
        "  words = words+\" \"+word\n",
        "#print(words)\n",
        "wcloud = WordCloud(width = 800, height = 800, background_color ='white', min_font_size = 10).generate(words)\n",
        "\n",
        "# plot the WordCloud image                        \n",
        "plt.figure(figsize = (8, 8), facecolor = None) \n",
        "plt.imshow(wcloud) \n",
        "plt.axis(\"off\") \n",
        "plt.tight_layout(pad = 0) \n",
        "  \n",
        "plt.show() "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zM5Ecw3Qp_-7"
      },
      "source": [
        "with open('nlargest.txt', 'w') as f:\n",
        "  for item in lst:\n",
        "    f.write(\"%s\\n\" % item)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kUnIm-5mqIHk"
      },
      "source": [
        "### 4. Feature Preparation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rnz6AilPqJOM"
      },
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer, TfidfTransformer, CountVectorizer\n",
        "from sklearn.naive_bayes import MultinomialNB\n",
        "from sklearn.pipeline import Pipeline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6A_tOiyFqMwD",
        "outputId": "dc7a7aa7-2973-4cac-e220-739161d51337",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 491
        }
      },
      "source": [
        "#Preparing data to create TF-IDF features\n",
        "\n",
        "d = data.tweets\n",
        "merged = []\n",
        "for doc in d:\n",
        "  merged.append((' '.join(doc)))\n",
        "\n",
        "data.tweets = merged\n",
        "data.head(15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>tweets</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>janiecrawford hay maambeen brand whilethank mu...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>realli miss xyz sinc post anim depress longest...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>boy flower awesom special yijung cha gaeul sto...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>rt bipolarhotlin nation suicid hotlin logic li...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>day sophmor year left thank godd lt txt mehhh ...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>there nosham talk ill depress notalon keeptalk...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ok like suppos tell mom depress without cri ge...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>search susan boyl microsoft bing twilight new ...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>presssec foxnew ericfolm obama came offic wars...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>good morn twitter friend time work unemploy lo...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>movi worsen depress tbh wan na die pictwitterc...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>need job hate unemploy unemploy corona job loc...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>bananaanna mikequad total agre anna</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>hard someon depress admit depress stayhom peop...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>understand got ta work haha chew gum feel like...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               tweets  label\n",
              "0   janiecrawford hay maambeen brand whilethank mu...      0\n",
              "1   realli miss xyz sinc post anim depress longest...      1\n",
              "2   boy flower awesom special yijung cha gaeul sto...      0\n",
              "3   rt bipolarhotlin nation suicid hotlin logic li...      1\n",
              "4   day sophmor year left thank godd lt txt mehhh ...      0\n",
              "5   there nosham talk ill depress notalon keeptalk...      1\n",
              "6   ok like suppos tell mom depress without cri ge...      1\n",
              "7   search susan boyl microsoft bing twilight new ...      0\n",
              "8   presssec foxnew ericfolm obama came offic wars...      1\n",
              "9   good morn twitter friend time work unemploy lo...      0\n",
              "10  movi worsen depress tbh wan na die pictwitterc...      1\n",
              "11  need job hate unemploy unemploy corona job loc...      1\n",
              "12                bananaanna mikequad total agre anna      0\n",
              "13  hard someon depress admit depress stayhom peop...      1\n",
              "14  understand got ta work haha chew gum feel like...      0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U-7VugrEqYWV"
      },
      "source": [
        "pipeline = Pipeline([\n",
        "   ( 'bow',CountVectorizer()),\n",
        "    ('classifier',MultinomialNB()),\n",
        "])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hLgSt9uErtgy"
      },
      "source": [
        "### 5. Training the DataSet\n",
        "The multinomial Naive Bayes classifier is suitable for classification with discrete features (e.g., word counts for text classification). The multinomial distribution normally requires integer feature counts. However, in practice, fractional counts such as tf-idf may also work."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ltIR5E_BrzjR"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "x_train, x_test, y_train, y_test = train_test_split(data.tweets, data.label, test_size=0.32, random_state=42)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7E6H-qLusHGn",
        "outputId": "88ada2d5-92d1-4b12-dc75-ab19a2c90e80",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 252
        }
      },
      "source": [
        "pipeline.fit(x_train, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pipeline(memory=None,\n",
              "         steps=[('bow',\n",
              "                 CountVectorizer(analyzer='word', binary=False,\n",
              "                                 decode_error='strict',\n",
              "                                 dtype=<class 'numpy.int64'>, encoding='utf-8',\n",
              "                                 input='content', lowercase=True, max_df=1.0,\n",
              "                                 max_features=None, min_df=1,\n",
              "                                 ngram_range=(1, 1), preprocessor=None,\n",
              "                                 stop_words=None, strip_accents=None,\n",
              "                                 token_pattern='(?u)\\\\b\\\\w\\\\w+\\\\b',\n",
              "                                 tokenizer=None, vocabulary=None)),\n",
              "                ('classifier',\n",
              "                 MultinomialNB(alpha=1.0, class_prior=None, fit_prior=True))],\n",
              "         verbose=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4SNZxlsasKTp"
      },
      "source": [
        "preds = pipeline.predict(x_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pAwmCi2TsSrt",
        "outputId": "315cea2e-e003-4cda-db7f-b537d1db8f43",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "from sklearn.metrics import accuracy_score\n",
        "accuracy_score(y_test, preds)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9236111111111112"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PSxed8W8Uy5n",
        "outputId": "debcd54a-e8ed-4ad7-dfa3-b903db78b30f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 168
        }
      },
      "source": [
        "from sklearn.metrics import accuracy_score, f1_score, recall_score\n",
        "print(\"Acccuracy: \"+ str(accuracy_score(y_test, preds)))\n",
        "print(\"F1 Score: \"+ str(f1_score(y_test, preds)))\n",
        "print(\"Recall: \"+ str(recall_score(y_test, preds)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.96      0.93      0.94        99\n",
            "           1       0.85      0.91      0.88        45\n",
            "\n",
            "    accuracy                           0.92       144\n",
            "   macro avg       0.91      0.92      0.91       144\n",
            "weighted avg       0.93      0.92      0.92       144\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}