CS7641_LDA_with_Vader.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "9VKkzMzhxDUD"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import glob\n",
        "import os\n",
        "import warnings\n",
        "from tqdm import tqdm\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import spacy\n",
        "import matplotlib.pyplot as plt\n",
        "import re\n",
        "from gensim.models.coherencemodel import CoherenceModel"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "eQoKiGbxVzqX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f199df43-351e-4ff6-b604-a57dfe82538b"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dirs=[\"2020-11\",\"2020-12\",\"2021-01\",\"2021-02\"]\n",
        "li = []\n",
        "for dir in dirs:\n",
        "  path=\"/content/drive/My Drive/CS7641/raw_vader/\"\n",
        "  path+=dir\n",
        "  all_files = glob.glob(os.path.join(path , \"*.csv\"))\n",
        "  for filename in tqdm(all_files):\n",
        "    df = pd.read_csv(filename, index_col=None, header=0)\n",
        "    li.append(df)"
      ],
      "metadata": {
        "id": "eEX0E5qSWYZB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "775e809d-4563-4128-af7a-a3c418fd28b8"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 720/720 [00:13<00:00, 52.37it/s] \n",
            "100%|██████████| 744/744 [00:13<00:00, 56.52it/s] \n",
            "100%|██████████| 744/744 [00:13<00:00, 55.70it/s] \n",
            "100%|██████████| 672/672 [00:13<00:00, 48.76it/s] \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_first_wave = pd.concat(li, axis=0, ignore_index=True)\n",
        "data_first_wave.head()"
      ],
      "metadata": {
        "id": "cAfJNohXY1-3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "6335c66d-da0b-4c00-9078-a11bb2ddc9a7"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Unnamed: 0                 created_at  \\\n",
              "0          0  2020-10-31 23:59:54+00:00   \n",
              "1          1  2020-10-31 23:59:54+00:00   \n",
              "2          2  2020-10-31 23:59:54+00:00   \n",
              "3          3  2020-10-31 23:59:54+00:00   \n",
              "4          4  2020-10-31 23:59:55+00:00   \n",
              "\n",
              "                                           full_text  \\\n",
              "0  Halloween is my favorite holiday, but today th...   \n",
              "1  RT The graphics in this article are excellent-...   \n",
              "2  Trick or Treats with my son who I don't  see o...   \n",
              "3  Like Bill Gates and Steve Jobs: Competition in...   \n",
              "4  RT \"Since when have children's clothes been no...   \n",
              "\n",
              "                                     sentiment_score  \n",
              "0  {'neg': 0.0, 'neu': 0.82, 'pos': 0.18, 'compou...  \n",
              "1  {'neg': 0.075, 'neu': 0.678, 'pos': 0.247, 'co...  \n",
              "2  {'neg': 0.297, 'neu': 0.703, 'pos': 0.0, 'comp...  \n",
              "3  {'neg': 0.0, 'neu': 0.815, 'pos': 0.185, 'comp...  \n",
              "4  {'neg': 0.163, 'neu': 0.837, 'pos': 0.0, 'comp...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8bff8f88-c750-4577-81b8-a954292d704f\">\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>Unnamed: 0</th>\n",
              "      <th>created_at</th>\n",
              "      <th>full_text</th>\n",
              "      <th>sentiment_score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>2020-10-31 23:59:54+00:00</td>\n",
              "      <td>Halloween is my favorite holiday, but today th...</td>\n",
              "      <td>{'neg': 0.0, 'neu': 0.82, 'pos': 0.18, 'compou...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>2020-10-31 23:59:54+00:00</td>\n",
              "      <td>RT The graphics in this article are excellent-...</td>\n",
              "      <td>{'neg': 0.075, 'neu': 0.678, 'pos': 0.247, 'co...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2020-10-31 23:59:54+00:00</td>\n",
              "      <td>Trick or Treats with my son who I don't  see o...</td>\n",
              "      <td>{'neg': 0.297, 'neu': 0.703, 'pos': 0.0, 'comp...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>2020-10-31 23:59:54+00:00</td>\n",
              "      <td>Like Bill Gates and Steve Jobs: Competition in...</td>\n",
              "      <td>{'neg': 0.0, 'neu': 0.815, 'pos': 0.185, 'comp...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>2020-10-31 23:59:55+00:00</td>\n",
              "      <td>RT \"Since when have children's clothes been no...</td>\n",
              "      <td>{'neg': 0.163, 'neu': 0.837, 'pos': 0.0, 'comp...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8bff8f88-c750-4577-81b8-a954292d704f')\"\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-8bff8f88-c750-4577-81b8-a954292d704f 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-8bff8f88-c750-4577-81b8-a954292d704f');\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": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dirs=[\"2021-12\",\"2022-01\"]\n",
        "li = []\n",
        "for dir in dirs:\n",
        "  path=\"/content/drive/My Drive/CS7641/raw_vader/\"\n",
        "  path+=dir\n",
        "  all_files = glob.glob(os.path.join(path , \"*.csv\"))\n",
        "  for filename in tqdm(all_files):\n",
        "    df = pd.read_csv(filename, index_col=None, header=0)\n",
        "    li.append(df)"
      ],
      "metadata": {
        "id": "2hbbDT_GajXp",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c39739a8-2625-4d7e-9494-c6445c3595a5"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 744/744 [00:13<00:00, 55.11it/s] \n",
            "100%|██████████| 744/744 [00:13<00:00, 54.31it/s] \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_second_wave = pd.concat(li, axis=0, ignore_index=True)\n",
        "data_second_wave.tail()"
      ],
      "metadata": {
        "id": "iKSU7VsyaxeF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "fe228a31-820a-430b-aee6-3cce8ad0bb3d"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Unnamed: 0                 created_at  \\\n",
              "227628         167  2022-01-31 22:00:00+00:00   \n",
              "227629         168  2022-01-31 22:00:00+00:00   \n",
              "227630         169  2022-01-31 22:00:00+00:00   \n",
              "227631         170  2022-01-31 22:00:00+00:00   \n",
              "227632         171  2022-01-31 22:00:00+00:00   \n",
              "\n",
              "                                                full_text  \\\n",
              "227628  I'm sure you will be covering this and the oth...   \n",
              "227629  More like they made her leave because she woul...   \n",
              "227630  RT My wise and funny Dad, Ranjith Chandrapala,...   \n",
              "227631  Thank you for attending the webinar for #journ...   \n",
              "227632  RT Thanks to everyone who's bought a copy of T...   \n",
              "\n",
              "                                          sentiment_score  \n",
              "227628  {'neg': 0.0, 'neu': 0.839, 'pos': 0.161, 'comp...  \n",
              "227629  {'neg': 0.086, 'neu': 0.715, 'pos': 0.2, 'comp...  \n",
              "227630  {'neg': 0.0, 'neu': 0.476, 'pos': 0.524, 'comp...  \n",
              "227631  {'neg': 0.0, 'neu': 0.782, 'pos': 0.218, 'comp...  \n",
              "227632  {'neg': 0.0, 'neu': 0.721, 'pos': 0.279, 'comp...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-12100107-d1e4-4ebc-b426-2581d3d1e504\">\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>Unnamed: 0</th>\n",
              "      <th>created_at</th>\n",
              "      <th>full_text</th>\n",
              "      <th>sentiment_score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>227628</th>\n",
              "      <td>167</td>\n",
              "      <td>2022-01-31 22:00:00+00:00</td>\n",
              "      <td>I'm sure you will be covering this and the oth...</td>\n",
              "      <td>{'neg': 0.0, 'neu': 0.839, 'pos': 0.161, 'comp...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227629</th>\n",
              "      <td>168</td>\n",
              "      <td>2022-01-31 22:00:00+00:00</td>\n",
              "      <td>More like they made her leave because she woul...</td>\n",
              "      <td>{'neg': 0.086, 'neu': 0.715, 'pos': 0.2, 'comp...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227630</th>\n",
              "      <td>169</td>\n",
              "      <td>2022-01-31 22:00:00+00:00</td>\n",
              "      <td>RT My wise and funny Dad, Ranjith Chandrapala,...</td>\n",
              "      <td>{'neg': 0.0, 'neu': 0.476, 'pos': 0.524, 'comp...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227631</th>\n",
              "      <td>170</td>\n",
              "      <td>2022-01-31 22:00:00+00:00</td>\n",
              "      <td>Thank you for attending the webinar for #journ...</td>\n",
              "      <td>{'neg': 0.0, 'neu': 0.782, 'pos': 0.218, 'comp...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227632</th>\n",
              "      <td>171</td>\n",
              "      <td>2022-01-31 22:00:00+00:00</td>\n",
              "      <td>RT Thanks to everyone who's bought a copy of T...</td>\n",
              "      <td>{'neg': 0.0, 'neu': 0.721, 'pos': 0.279, 'comp...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-12100107-d1e4-4ebc-b426-2581d3d1e504')\"\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-12100107-d1e4-4ebc-b426-2581d3d1e504 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-12100107-d1e4-4ebc-b426-2581d3d1e504');\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": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# import numpy as np\n",
        "# # data['created_at']=pd.to_datetime(data['created_at'])\n",
        "# data['sentiment_score']\n",
        "# data['created_at']\n",
        "# # data['created_at']=pd.to_datetime(data['created_at'])\n",
        "# # data.index[data['sentiment_score'] == \"{'neg': 0.0, 'neu': 0.757, 'pos': 0.243, 'compound': 0.5423}\"].tolist()\n",
        "# data['created_at'][228504]\n",
        "# # data.index[data['sentiment_score']=='nan'].tolist()"
      ],
      "metadata": {
        "id": "p_YncTaMWEJZ"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# data['created_at'][228504]"
      ],
      "metadata": {
        "id": "-LxqLo-0ZziK"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_first_wave=data_first_wave.drop('Unnamed: 0',axis=1)\n",
        "data_second_wave=data_second_wave.drop('Unnamed: 0',axis=1)"
      ],
      "metadata": {
        "id": "k1FrF6LfbelL"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(data_first_wave.shape)\n",
        "data_first_wave = data_first_wave[data_first_wave['full_text'].notna()]\n",
        "data_first_wave.shape"
      ],
      "metadata": {
        "id": "F_w-tVeHewSw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1510f238-83c9-4222-e946-0ab378ba1360"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(433347, 3)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(433339, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(data_second_wave.shape)\n",
        "data_second_wave = data_second_wave[data_second_wave['full_text'].notna()]\n",
        "data_second_wave.shape"
      ],
      "metadata": {
        "id": "bHNVSu3sbNYu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "280049a1-31dd-4463-d1c8-9012d067914b"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(227633, 3)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(227631, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def punctRemover(sentence):\n",
        "    # list the different punctuations\n",
        "    punctuations = '''\\n!()-[]{};:'\"\\,<>./?@#$%^&*_~'''\n",
        "    no_punct = \"\"\n",
        "    for char in sentence:\n",
        "        if char not in punctuations:\n",
        "            no_punct = no_punct + char\n",
        "    return no_punct"
      ],
      "metadata": {
        "id": "SdsTGPUpcA8P"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tweets_first_wave=data_first_wave['full_text']\n",
        "tweets_second_wave=data_second_wave['full_text']\n",
        "def urlRemover(sentence):\n",
        "    pattern = r\"http\\S+\"\n",
        "    return re.sub(pattern,\"\",sentence)\n",
        "\n",
        "new_tweets = []\n",
        "for tweet in tweets_first_wave:\n",
        "    new_tweets.append(urlRemover(punctRemover(tweet)))\n",
        "data_first_wave['full_text']=new_tweets\n",
        "\n",
        "new_tweets = []\n",
        "for tweet in tweets_second_wave:\n",
        "    new_tweets.append(urlRemover(punctRemover(tweet)))\n",
        "data_second_wave['full_text']=new_tweets"
      ],
      "metadata": {
        "id": "7BwlO4VgcCyD"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import gensim\n",
        "from gensim.utils import simple_preprocess\n",
        "from gensim.parsing.preprocessing import STOPWORDS\n",
        "from nltk.stem import WordNetLemmatizer, SnowballStemmer\n",
        "from nltk.stem.porter import *\n",
        "import numpy as np\n",
        "np.random.seed(2022)\n",
        "import nltk\n",
        "nltk.download('wordnet')\n",
        "nltk.download('omw-1.4')"
      ],
      "metadata": {
        "id": "SHEArDfqdKfk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "274ef8fd-1157-4431-a32f-a177ae218888"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def lemmatize(text):\n",
        "    return WordNetLemmatizer().lemmatize(text, pos='v')\n",
        "def preprocess(text):\n",
        "    result = []\n",
        "    for token in gensim.utils.simple_preprocess(text):\n",
        "        if token not in gensim.parsing.preprocessing.STOPWORDS and len(token) > 3:\n",
        "            result.append(lemmatize(token))\n",
        "    return result"
      ],
      "metadata": {
        "id": "GkmF3g0CdTbF"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "processed_tweets_first_wave = data_first_wave['full_text'].map(preprocess)\n",
        "processed_tweets_second_wave = data_second_wave['full_text'].map(preprocess)"
      ],
      "metadata": {
        "id": "iIWVdk91daIw"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lexicon_first_wave = gensim.corpora.Dictionary(processed_tweets_first_wave)\n",
        "bow_corpus_first_wave = [lexicon_first_wave.doc2bow(doc) for doc in processed_tweets_first_wave]\n",
        "\n",
        "lexicon_second_wave = gensim.corpora.Dictionary(processed_tweets_second_wave)\n",
        "bow_corpus_second_wave = [lexicon_second_wave.doc2bow(doc) for doc in processed_tweets_second_wave]"
      ],
      "metadata": {
        "id": "xsLyiDESdTXu"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lda_model_first_wave = gensim.models.LdaMulticore(bow_corpus_first_wave, num_topics=3,id2word=lexicon_first_wave, passes=2, workers=2)\n",
        "\n",
        "lda_model_second_wave = gensim.models.LdaMulticore(bow_corpus_second_wave, num_topics=3,id2word=lexicon_second_wave, passes=2, workers=2)"
      ],
      "metadata": {
        "id": "Z-6wsHiPnvhW"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "text = \"\"\n",
        "text1 = \"\"\n",
        "for idx, topic in lda_model_first_wave.print_topics(-1):\n",
        "    t_list=topic.split(\"+\")\n",
        "    t_list=[t[t.index('\"')+1:t.rfind('\"')] for t in t_list]\n",
        "    text+=\" \".join(t_list)\n",
        "    text+=\" \"\n",
        "    print('Topic: {} \\nWords: {}'.format(idx, topic))\n",
        "print(\"\\n\\n\")\n",
        "\n",
        "\n",
        "for idx, topic in lda_model_second_wave.print_topics(-1):\n",
        "    t_list=topic.split(\"+\")\n",
        "    t_list=[t[t.index('\"')+1:t.rfind('\"')] for t in t_list]\n",
        "    text1+=\" \".join(t_list)\n",
        "    text1+=\" \"\n",
        "    print('Topic: {} \\nWords: {}'.format(idx, topic))"
      ],
      "metadata": {
        "id": "mCpp0G2Rb3Kh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ae999604-489c-4614-b349-82bb2cb7033a"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Topic: 0 \n",
            "Words: 0.023*\"covid\" + 0.022*\"pandemic\" + 0.015*\"people\" + 0.015*\"lockdown\" + 0.011*\"like\" + 0.009*\"dont\" + 0.009*\"mask\" + 0.008*\"home\" + 0.008*\"go\" + 0.007*\"school\"\n",
            "Topic: 1 \n",
            "Words: 0.058*\"covid\" + 0.014*\"coronavirus\" + 0.014*\"case\" + 0.011*\"health\" + 0.009*\"state\" + 0.008*\"say\" + 0.008*\"report\" + 0.007*\"deaths\" + 0.007*\"pandemic\" + 0.005*\"break\"\n",
            "Topic: 2 \n",
            "Words: 0.049*\"covid\" + 0.021*\"vaccine\" + 0.012*\"pandemic\" + 0.009*\"help\" + 0.007*\"vaccines\" + 0.007*\"test\" + 0.006*\"relief\" + 0.006*\"need\" + 0.005*\"work\" + 0.005*\"support\"\n",
            "\n",
            "\n",
            "\n",
            "Topic: 0 \n",
            "Words: 0.033*\"covid\" + 0.022*\"pandemic\" + 0.009*\"like\" + 0.008*\"people\" + 0.008*\"dont\" + 0.008*\"work\" + 0.007*\"home\" + 0.006*\"go\" + 0.006*\"time\" + 0.006*\"think\"\n",
            "Topic: 1 \n",
            "Words: 0.053*\"covid\" + 0.023*\"test\" + 0.019*\"omicron\" + 0.015*\"case\" + 0.015*\"mask\" + 0.009*\"positive\" + 0.008*\"wear\" + 0.007*\"report\" + 0.007*\"health\" + 0.007*\"variant\"\n",
            "Topic: 2 \n",
            "Words: 0.049*\"covid\" + 0.030*\"vaccine\" + 0.013*\"people\" + 0.008*\"say\" + 0.008*\"mandate\" + 0.007*\"die\" + 0.006*\"vaccines\" + 0.005*\"vaccinate\" + 0.004*\"booster\" + 0.004*\"lockdown\"\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from wordcloud import WordCloud\n",
        "wordcloud = WordCloud(width = 800, height = 800,background_color ='white',min_font_size = 10).generate(text)\n",
        "plt.figure(figsize = (8, 8), facecolor = None)\n",
        "plt.imshow(wordcloud)\n",
        "plt.axis(\"off\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "lxk2RJ6e09U6",
        "outputId": "5399098b-7406-4145-e48f-37d631d0788e"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from wordcloud import WordCloud\n",
        "wordcloud = WordCloud(width = 800, height = 800,background_color ='white',min_font_size = 10).generate(text1)\n",
        "plt.figure(figsize = (8, 8), facecolor = None)\n",
        "plt.imshow(wordcloud)\n",
        "plt.axis(\"off\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "TGnKRuiW8P0U",
        "outputId": "90776d68-26c0-4633-84b9-78a0044771d1"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pyLDAvis"
      ],
      "metadata": {
        "id": "2z9_zJrLIvBm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7abd8f8e-0703-4f9b-a9b6-2e41cf8f8536"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting pyLDAvis\n",
            "  Downloading pyLDAvis-3.3.1.tar.gz (1.7 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.7 MB 33.4 MB/s \n",
            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "    Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: numpy>=1.20.0 in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (1.21.6)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (57.4.0)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (1.7.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (2.11.3)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (1.2.0)\n",
            "Requirement already satisfied: pandas>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (1.3.5)\n",
            "Collecting sklearn\n",
            "  Downloading sklearn-0.0.post1.tar.gz (3.6 kB)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (0.16.0)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (1.0.2)\n",
            "Requirement already satisfied: gensim in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (3.6.0)\n",
            "Requirement already satisfied: numexpr in /usr/local/lib/python3.8/dist-packages (from pyLDAvis) (2.8.4)\n",
            "Collecting funcy\n",
            "  Downloading funcy-1.17-py2.py3-none-any.whl (33 kB)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas>=1.2.0->pyLDAvis) (2022.6)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas>=1.2.0->pyLDAvis) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.7.3->pandas>=1.2.0->pyLDAvis) (1.15.0)\n",
            "Requirement already satisfied: smart-open>=1.2.1 in /usr/local/lib/python3.8/dist-packages (from gensim->pyLDAvis) (5.2.1)\n",
            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.8/dist-packages (from jinja2->pyLDAvis) (2.0.1)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn->pyLDAvis) (3.1.0)\n",
            "Building wheels for collected packages: pyLDAvis, sklearn\n",
            "  Building wheel for pyLDAvis (PEP 517) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyLDAvis: filename=pyLDAvis-3.3.1-py2.py3-none-any.whl size=136898 sha256=b51662f9241874e5180fdbe055e8772846d42d83ee07982411359bb867ec2904\n",
            "  Stored in directory: /root/.cache/pip/wheels/90/61/ec/9dbe9efc3acf9c4e37ba70fbbcc3f3a0ebd121060aa593181a\n",
            "  Building wheel for sklearn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sklearn: filename=sklearn-0.0.post1-py3-none-any.whl size=2344 sha256=c5424c50b4b6961147add5b7d2a32f51feffbc8fc2ef524abee2e83482e2ab8a\n",
            "  Stored in directory: /root/.cache/pip/wheels/14/25/f7/1cc0956978ae479e75140219088deb7a36f60459df242b1a72\n",
            "Successfully built pyLDAvis sklearn\n",
            "Installing collected packages: sklearn, funcy, pyLDAvis\n",
            "Successfully installed funcy-1.17 pyLDAvis-3.3.1 sklearn-0.0.post1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pyLDAvis\n",
        "import pyLDAvis.gensim_models as gensimvis\n",
        "pyLDAvis.enable_notebook()\n",
        "\n",
        "# feed the LDA model into the pyLDAvis instance\n",
        "lda_viz = gensimvis.prepare(lda_model_first_wave, bow_corpus_first_wave, lexicon_first_wave)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2AovvAgFIIb2",
        "outputId": "d74bf013-61d7-4f4f-a2f6-8943dc4dbb6a"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/past/types/oldstr.py:5: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working\n",
            "  from collections import Iterable\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lda_viz"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 862
        },
        "id": "CiDmvtBPM2e7",
        "outputId": "2d51c1f5-7bf8-4d82-904a-42e2f5ef5e23"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PreparedData(topic_coordinates=              x         y  topics  cluster       Freq\n",
              "topic                                                \n",
              "0      0.211367  0.105936       1        1  35.760043\n",
              "2      0.002045 -0.208857       2        1  34.650763\n",
              "1     -0.213412  0.102920       3        1  29.589194, topic_info=            Term           Freq          Total Category  logprob  loglift\n",
              "941      vaccine   31714.000000   31714.000000  Default  30.0000  30.0000\n",
              "84          case   18495.000000   18495.000000  Default  29.0000  29.0000\n",
              "58         covid  183049.000000  183049.000000  Default  28.0000  28.0000\n",
              "86   coronavirus   23184.000000   23184.000000  Default  27.0000  27.0000\n",
              "40          like   16530.000000   16530.000000  Default  26.0000  26.0000\n",
              "..           ...            ...            ...      ...      ...      ...\n",
              "21         today    4358.573976   11285.063369   Topic3  -5.6829   0.2664\n",
              "104       people    5530.238565   33572.881912   Topic3  -5.4448  -0.5857\n",
              "77         biden    3827.795394    8765.956749   Topic3  -5.8127   0.3892\n",
              "209        world    3524.919102    7438.859619   Topic3  -5.8952   0.4709\n",
              "446        virus    3506.015049    8790.433456   Topic3  -5.9006   0.2986\n",
              "\n",
              "[258 rows x 6 columns], token_table=      Topic      Freq      Term\n",
              "term                           \n",
              "1013      2  0.995015    access\n",
              "1013      3  0.005105    access\n",
              "1396      2  0.000786    accord\n",
              "1396      3  0.998997    accord\n",
              "76        1  0.998812  actually\n",
              "...     ...       ...       ...\n",
              "3524      3  0.993430     wuhan\n",
              "198       1  0.999756      yall\n",
              "22        1  0.467952      year\n",
              "22        2  0.344140      year\n",
              "22        3  0.187865      year\n",
              "\n",
              "[451 rows x 3 columns], R=30, lambda_step=0.01, plot_opts={'xlab': 'PC1', 'ylab': 'PC2'}, topic_order=[1, 3, 2])"
            ],
            "text/html": [
              "\n",
              "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.jsdelivr.net/gh/bmabey/pyLDAvis@3.3.1/pyLDAvis/js/ldavis.v1.0.0.css\">\n",
              "\n",
              "\n",
              "<div id=\"ldavis_el761406533827594721218944773\"></div>\n",
              "<script type=\"text/javascript\">\n",
              "\n",
              "var ldavis_el761406533827594721218944773_data = {\"mdsDat\": {\"x\": [0.2113668934594679, 0.0020447632092032214, -0.21341165666867104], \"y\": [0.10593640542202021, -0.20885668074527208, 0.10292027532325182], \"topics\": [1, 2, 3], \"cluster\": [1, 1, 1], \"Freq\": [35.76004316339267, 34.65076325932857, 29.58919357727875]}, \"tinfo\": {\"Term\": [\"vaccine\", \"case\", \"covid\", \"coronavirus\", \"like\", \"dont\", \"state\", \"health\", \"lockdown\", \"go\", \"report\", \"mask\", \"school\", \"help\", \"think\", \"vaccines\", \"deaths\", \"home\", \"wear\", \"people\", \"want\", \"stay\", \"number\", \"lose\", \"test\", \"vaccination\", \"know\", \"relief\", \"break\", \"vote\", \"republicans\", \"fuck\", \"yall\", \"thing\", \"kid\", \"vote\", \"republican\", \"shit\", \"survival\", \"hate\", \"middle\", \"chill\", \"true\", \"literally\", \"maybe\", \"nepa\", \"barometer\", \"sayre\", \"bradfordcounty\", \"patemp\", \"statscases\", \"inhgwind\", \"fhumidity\", \"fwind\", \"weewx\", \"gonna\", \"sorry\", \"imagine\", \"dems\", \"tire\", \"think\", \"dont\", \"like\", \"lose\", \"school\", \"thats\", \"didnt\", \"point\", \"go\", \"trillion\", \"democrats\", \"actually\", \"things\", \"lock\", \"lie\", \"isnt\", \"arent\", \"doesnt\", \"believe\", \"try\", \"life\", \"right\", \"theres\", \"wear\", \"mask\", \"stay\", \"want\", \"feel\", \"lockdown\", \"home\", \"tell\", \"trump\", \"people\", \"know\", \"stop\", \"pandemic\", \"happen\", \"live\", \"time\", \"love\", \"covid\", \"good\", \"work\", \"need\", \"year\", \"say\", \"come\", \"get\", \"dose\", \"vaccine\", \"effective\", \"approve\", \"employees\", \"rollout\", \"info\", \"pfizer\", \"administer\", \"stayathome\", \"provide\", \"practice\", \"train\", \"available\", \"ensure\", \"appointment\", \"safely\", \"minimum\", \"volunteer\", \"eligible\", \"resources\", \"site\", \"ready\", \"programme\", \"welcome\", \"wind\", \"negative\", \"rain\", \"index\", \"sunset\", \"travel\", \"free\", \"vaccines\", \"online\", \"offer\", \"distance\", \"happy\", \"information\", \"book\", \"package\", \"symptoms\", \"program\", \"visit\", \"deliver\", \"billion\", \"social\", \"wage\", \"vaccination\", \"join\", \"prevent\", \"safety\", \"access\", \"share\", \"fund\", \"receive\", \"business\", \"help\", \"service\", \"support\", \"relief\", \"company\", \"check\", \"workers\", \"covid\", \"test\", \"learn\", \"read\", \"need\", \"work\", \"pandemic\", \"thank\", \"time\", \"safe\", \"today\", \"year\", \"lockdown\", \"coronavirus\", \"people\", \"case\", \"report\", \"total\", \"record\", \"confirm\", \"unite\", \"rate\", \"toll\", \"infections\", \"rat\", \"prime\", \"surge\", \"publish\", \"highest\", \"minister\", \"rise\", \"radio\", \"price\", \"average\", \"department\", \"decline\", \"officer\", \"wave\", \"nations\", \"hospitals\", \"accord\", \"infectious\", \"higher\", \"investigation\", \"tenanttips\", \"state\", \"number\", \"data\", \"death\", \"county\", \"increase\", \"office\", \"white\", \"outbreak\", \"police\", \"officials\", \"south\", \"disease\", \"population\", \"daily\", \"texas\", \"wuhan\", \"contract\", \"break\", \"variant\", \"health\", \"coronavirus\", \"deaths\", \"million\", \"response\", \"india\", \"covid\", \"news\", \"say\", \"hospital\", \"china\", \"die\", \"public\", \"patients\", \"test\", \"pandemic\", \"president\", \"today\", \"people\", \"biden\", \"world\", \"virus\"], \"Freq\": [31714.0, 18495.0, 183049.0, 23184.0, 16530.0, 14561.0, 11035.0, 16617.0, 28977.0, 12866.0, 9773.0, 15759.0, 10917.0, 14427.0, 10396.0, 10354.0, 11055.0, 15234.0, 10948.0, 33572.0, 11378.0, 10977.0, 6240.0, 7454.0, 15489.0, 7098.0, 12419.0, 10993.0, 6732.0, 6236.0, 3415.6536758673333, 3149.1384659055293, 3101.081346829027, 3141.397209213748, 2998.6815714515096, 6234.00115210554, 2379.357795043248, 1545.2076595592393, 1373.4949187601944, 1648.6365277086672, 2246.324853697951, 1242.8415742866398, 1353.6018276194286, 1154.4979594433828, 1393.390622268816, 969.3940408518707, 971.220176064771, 968.1467703231702, 967.9475997945731, 967.9475997945731, 967.9475997945731, 963.1557064120639, 963.1557064120639, 963.1557064120639, 960.4822631973612, 1291.0829103378055, 1014.9700410368521, 1308.9179960980505, 1000.3468165145688, 896.1395528257432, 10384.345272978668, 14469.535858546704, 16386.552646702963, 7431.7303764607905, 10836.249600036523, 5480.568679285267, 3687.4458688979853, 3786.5782026593665, 12674.43773773379, 2646.7903965307123, 3029.4876941876787, 2282.9223257256226, 3946.3019766329926, 1937.938972068935, 2284.7794490261927, 2931.756310250243, 1749.2398948178509, 3458.892147311216, 3016.493596309303, 3437.2167006395484, 5327.69507431962, 6736.204910676734, 3703.005492174121, 10057.727225675315, 14123.211549445106, 9862.273105638864, 10116.51523125051, 4902.860283147544, 22710.28304959517, 12723.583403471335, 6643.661509137747, 6234.515698491496, 23923.766473590993, 10174.278467973007, 5314.926901219952, 34188.324050743504, 3892.9934576762994, 8080.453020065761, 9380.973334487006, 4795.156500206117, 35238.93264464162, 4898.053886619352, 7466.880957022913, 7340.271557990239, 6977.286467520432, 7645.353605016437, 5585.9238534426195, 5338.843579348652, 5879.946862930515, 31702.694741681422, 2414.526875520031, 1840.3780164047218, 1689.5731293529188, 1673.3301831822523, 1619.439173219777, 1519.0461985708778, 1528.4360435423603, 1344.0375009115173, 3987.8987748518853, 1420.365626348685, 1538.6404536808334, 2588.143427889171, 1554.554850420665, 1094.1130737608826, 1276.1095569371153, 1310.8396932785022, 1080.6395793281376, 997.4845388844666, 958.0496165914287, 1252.844172187929, 1300.101783107812, 848.5663670153154, 1041.6385622478208, 793.3633415122231, 1126.430327021351, 723.7831360669713, 702.3797205483535, 652.1055475189507, 5923.246954550547, 4815.271434108302, 10241.57358312588, 3583.5287942810355, 3170.926223880577, 4766.1241402372625, 2409.985491410708, 2598.5369023388, 3105.9355851391806, 2469.3042008174425, 2201.0016926322573, 2210.378968231253, 3150.013232107216, 1851.5380480014264, 2039.5035865119394, 6010.669733390027, 1507.981659290149, 6980.524609365816, 4036.9175818041704, 2205.37984947387, 2355.163125861886, 2143.7726414014514, 5005.799728009176, 3134.0358139303326, 5449.752408287092, 3713.8148790466325, 12991.28163006478, 3726.320357223277, 7602.23859259039, 9198.650849988993, 2447.0941196332924, 3949.06255621084, 4658.990141293853, 73210.62847338551, 10046.002526813156, 4886.945836669546, 4509.447428729265, 8607.595661155105, 8206.5970656046, 17794.259519582534, 4137.537154307068, 5906.662365852706, 3765.0130755284317, 4743.925231828656, 5130.896058534673, 5694.434796099575, 4575.978513898764, 4118.876873402727, 18494.640203472132, 9772.271685492082, 3919.581943370205, 3166.4385682905627, 2709.5523086719663, 2604.5971733458036, 2492.799847144587, 1476.9712314488772, 1453.0885595782115, 1842.872213885287, 1510.0183663949458, 1269.4436079000423, 1331.4538510107732, 1197.4624122670036, 3483.3367450819887, 2967.6259502048533, 1568.3248700771455, 1314.9279728932977, 1198.9741700269044, 1568.8345535187293, 1103.6791682772462, 1109.6854276229992, 1495.2514104556647, 1003.195651703276, 1514.6238534508943, 2541.228271303633, 717.3457533424242, 1393.7264640709593, 700.8332918700913, 620.036801351486, 10973.961831717354, 6232.552234567507, 4632.594343942324, 4550.9078453608, 3323.57431620065, 4148.308909761186, 3460.287545022348, 2486.382516699048, 2691.581756020303, 2108.354377792081, 2408.0808886131676, 3016.7311695744256, 2014.457092318611, 1658.9107784555874, 2479.297633620748, 2394.584936190395, 1875.1622028238082, 2345.793219095655, 6317.1212248209995, 2975.87748511522, 13799.661142945766, 18501.458244385933, 9314.699686232865, 5746.018170660472, 3373.791328231039, 3945.5729664881123, 74599.75267658143, 5951.709055489286, 10513.59082213372, 3037.2052682096974, 3481.762525385257, 5035.669421370664, 4486.834122227138, 3029.9170484205692, 5442.935560593882, 9264.0396267651, 3865.613935505616, 4358.573976140616, 5530.238564979765, 3827.7953943253356, 3524.919102446272, 3506.015049440354], \"Total\": [31714.0, 18495.0, 183049.0, 23184.0, 16530.0, 14561.0, 11035.0, 16617.0, 28977.0, 12866.0, 9773.0, 15759.0, 10917.0, 14427.0, 10396.0, 10354.0, 11055.0, 15234.0, 10948.0, 33572.0, 11378.0, 10977.0, 6240.0, 7454.0, 15489.0, 7098.0, 12419.0, 10993.0, 6732.0, 6236.0, 3416.349187184881, 3149.7810396819004, 3101.7575921545977, 3142.1478334507224, 2999.544536276891, 6236.48759240582, 2380.3316197213244, 1545.8447853894434, 1374.1480245041214, 1649.4512584525824, 2247.4642678508135, 1243.4896122402713, 1354.3116994164614, 1155.142653736386, 1394.2556117083464, 970.0155213438039, 971.842849505802, 968.7682417387773, 968.5690601422191, 968.569060251404, 968.5690602877991, 963.7771665652834, 963.7771666593839, 963.7771666957788, 961.1037243253462, 1291.9238251259, 1015.6328384481129, 1309.801741381166, 1001.048460379265, 896.7823694428387, 10396.374674694438, 14561.526696388624, 16530.832111853586, 7454.96347855166, 10917.370466580456, 5484.847206969701, 3691.3033166566765, 3794.252118090067, 12866.012206848422, 2649.7311691877917, 3040.7539213565633, 2285.7151131779824, 3975.1015432210224, 1940.3696934235902, 2291.914967059187, 2948.519338727381, 1751.3317149008756, 3490.9087687074925, 3040.9301506059937, 3473.6770134750846, 5449.356353278034, 7022.774724983149, 3820.1615445763296, 10948.727503441554, 15759.427485222148, 10977.686082751905, 11378.078196759643, 5211.635803744494, 28977.139644267412, 15234.457098283332, 7469.941164152404, 7017.396222152887, 33572.88191197348, 12419.150651383998, 5837.932821480512, 61246.62319709114, 4101.110417687908, 11353.38426027226, 17262.839415816958, 5896.090477067882, 183049.31379460858, 6438.572018283076, 15740.785427436866, 15970.181881176215, 14909.64958726997, 19747.076086699235, 9551.513030187976, 8032.914800814025, 5880.7862958699325, 31714.253298827614, 2415.45814569413, 1841.1494473539244, 1690.3224076536032, 1674.0747621103897, 1620.182259553996, 1519.7600344636871, 1529.1893665430423, 1344.7347015570442, 3989.9953742388825, 1421.1300639834167, 1539.4886943081672, 2589.677026870971, 1555.5286011744006, 1094.8014214010534, 1276.9336251673571, 1311.7043959540872, 1081.3694721087413, 998.1956326752938, 958.7885273502318, 1253.8651595703639, 1301.1741686416783, 849.2698065061415, 1042.5286675325865, 794.0623566879461, 1127.439683895662, 724.460667026432, 703.0589353332097, 652.7665621783785, 5936.573551583803, 4827.400942054565, 10354.41911055719, 3587.6109905394737, 3178.7211711608106, 4800.010358217783, 2413.268108780451, 2604.3406172873238, 3118.792406434225, 2474.330818541546, 2203.3239540777276, 2213.7351671163046, 3170.3537483338464, 1855.2513963867618, 2045.9518791671803, 6097.566594217465, 1509.6002867000225, 7098.717204211904, 4099.170855774617, 2216.3295215086337, 2370.0922707578534, 2154.742256793784, 5146.582101835915, 3188.3656463498933, 5643.696755192778, 3847.6342602578056, 14427.033354739817, 3902.047475876412, 8431.53842305925, 10993.086179149732, 2499.3346597227783, 4463.886042676329, 5475.227848678435, 183049.31379460858, 15489.669197425605, 6519.061253025958, 5958.182231591861, 15970.181881176215, 15740.785427436866, 61246.62319709114, 5640.192152515375, 17262.839415816958, 5339.303850892558, 11285.06336883756, 14909.64958726997, 28977.139644267412, 23184.463037134952, 33572.88191197348, 18495.426219357738, 9773.319489843501, 3920.3114951254365, 3167.1954401004427, 2710.2354547236205, 2605.4401101779235, 2493.734881737104, 1477.6335625541642, 1453.745441354499, 1843.7128478238658, 1510.7821693296748, 1270.1237666878174, 1332.1748063199566, 1198.112426746958, 3485.309596249688, 2969.3533197063884, 1569.2399434760514, 1315.7092810010163, 1199.6950384741274, 1569.819428575037, 1104.3860603659618, 1110.4132739909753, 1496.2716310898547, 1004.0114705660558, 1515.8673008843323, 2543.5509873557494, 718.0354823075713, 1395.135973613928, 701.553043021861, 620.6786876313834, 11035.805283390417, 6240.8336256207995, 4642.303533356145, 4567.571056302371, 3328.8472878252846, 4165.952629218579, 3471.2315805314106, 2490.488231588036, 2700.1669397031806, 2113.3101713819674, 2417.1207088926726, 3036.098606475023, 2020.6040991165728, 1661.9673139749968, 2511.157439796789, 2423.07366460747, 1887.4002178593996, 2386.4864722597213, 6732.094070538163, 3096.283573694845, 16617.74062848939, 23184.463037134952, 11055.324559189354, 6700.5302691142615, 3702.8820004479717, 4511.01156065734, 183049.31379460858, 8465.988721387854, 19747.076086699235, 3335.003587049445, 4324.701866947431, 8352.151065076256, 6805.42422010271, 3554.817798327615, 15489.669197425605, 61246.62319709114, 7266.194614565126, 11285.06336883756, 33572.88191197348, 8765.95674945108, 7438.859619365705, 8790.433456389745], \"Category\": [\"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\"], \"logprob\": [30.0, 29.0, 28.0, 27.0, 26.0, 25.0, 24.0, 23.0, 22.0, 21.0, 20.0, 19.0, 18.0, 17.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0, 10.0, 9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, -6.1161, -6.1973, -6.2127, -6.1998, -6.2463, -5.5144, -6.4776, -6.9093, -7.0271, -6.8445, -6.5352, -7.1271, -7.0417, -7.2008, -7.0127, -7.3755, -7.3737, -7.3768, -7.377, -7.377, -7.377, -7.382, -7.382, -7.382, -7.3848, -7.089, -7.3296, -7.0753, -7.3441, -7.4541, -5.0042, -4.6724, -4.548, -5.3387, -4.9616, -5.6432, -6.0395, -6.013, -4.8049, -6.3711, -6.2361, -6.519, -5.9717, -6.6828, -6.5182, -6.2689, -6.7853, -6.1035, -6.2404, -6.1098, -5.6715, -5.437, -6.0353, -5.0361, -4.6966, -5.0557, -5.0303, -5.7546, -4.2216, -4.801, -5.4508, -5.5144, -4.1696, -5.0246, -5.6739, -3.8126, -5.9853, -5.255, -5.1058, -5.7768, -3.7823, -5.7556, -5.334, -5.3511, -5.4018, -5.3104, -5.6242, -5.6694, -5.5414, -3.8565, -6.4314, -6.703, -6.7885, -6.7981, -6.8309, -6.8949, -6.8887, -7.0173, -5.9297, -6.962, -6.882, -6.362, -6.8718, -7.223, -7.0691, -7.0423, -7.2354, -7.3155, -7.3558, -7.0875, -7.0505, -7.4772, -7.2721, -7.5444, -7.1939, -7.6362, -7.6662, -7.7405, -5.5341, -5.7412, -4.9865, -6.0366, -6.1589, -5.7514, -6.4333, -6.358, -6.1796, -6.409, -6.524, -6.5198, -6.1655, -6.6969, -6.6002, -5.5194, -6.9022, -5.3698, -5.9175, -6.522, -6.4563, -6.5504, -5.7023, -6.1706, -5.6174, -6.0009, -4.7487, -5.9975, -5.2845, -5.0939, -6.418, -5.9395, -5.7741, -3.0196, -5.0058, -5.7264, -5.8068, -5.1603, -5.208, -4.4341, -5.8928, -5.5369, -5.9872, -5.7561, -5.6777, -5.5735, -5.7921, -5.8974, -4.2376, -4.8755, -5.789, -6.0024, -6.1582, -6.1978, -6.2416, -6.765, -6.7813, -6.5437, -6.7429, -6.9165, -6.8688, -6.9748, -5.907, -6.0673, -6.705, -6.8813, -6.9736, -6.7047, -7.0564, -7.051, -6.7527, -7.1518, -6.7399, -6.2224, -7.4872, -6.8231, -7.5105, -7.633, -4.7595, -5.3252, -5.6219, -5.6397, -5.954, -5.7323, -5.9137, -6.2442, -6.1649, -6.4091, -6.2762, -6.0509, -6.4547, -6.6489, -6.2471, -6.2818, -6.5263, -6.3024, -5.3118, -6.0645, -4.5304, -4.2372, -4.9234, -5.4065, -5.939, -5.7824, -2.8429, -5.3714, -4.8024, -6.0441, -5.9075, -5.5385, -5.6539, -6.0465, -5.4607, -4.9289, -5.8029, -5.6829, -5.4448, -5.8127, -5.8952, -5.9006], \"loglift\": [30.0, 29.0, 28.0, 27.0, 26.0, 25.0, 24.0, 23.0, 22.0, 21.0, 20.0, 19.0, 18.0, 17.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0, 10.0, 9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 1.0281, 1.0281, 1.0281, 1.0281, 1.0281, 1.0279, 1.0279, 1.0279, 1.0279, 1.0278, 1.0278, 1.0278, 1.0278, 1.0278, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0277, 1.0276, 1.0276, 1.0272, 1.022, 1.0196, 1.0252, 1.0209, 1.0276, 1.0273, 1.0263, 1.0133, 1.0272, 1.0246, 1.0271, 1.0211, 1.0271, 1.0252, 1.0226, 1.0271, 1.0191, 1.0203, 1.0178, 1.0058, 0.9867, 0.9972, 0.9435, 0.9187, 0.9212, 0.9108, 0.9673, 0.7846, 0.8482, 0.9111, 0.91, 0.6895, 0.829, 0.9345, 0.4453, 0.9763, 0.6883, 0.4185, 0.8217, -0.6193, 0.7549, 0.2826, 0.251, 0.269, 0.0794, 0.4919, 0.6198, 1.0597, 1.0595, 1.0595, 1.0594, 1.0594, 1.0594, 1.0594, 1.0594, 1.0594, 1.0593, 1.0593, 1.0593, 1.0593, 1.0593, 1.0592, 1.0592, 1.0592, 1.0592, 1.0592, 1.0591, 1.0591, 1.059, 1.059, 1.059, 1.059, 1.059, 1.059, 1.0589, 1.0589, 1.0588, 1.0576, 1.0573, 1.0489, 1.0587, 1.0574, 1.0528, 1.0585, 1.0576, 1.0557, 1.0578, 1.0588, 1.0583, 1.0534, 1.0578, 1.0567, 1.0455, 1.0588, 1.0431, 1.0445, 1.0549, 1.0535, 1.0547, 1.0321, 1.0427, 1.0249, 1.0245, 0.955, 1.0138, 0.9563, 0.8816, 1.0387, 0.9373, 0.8984, 0.1434, 0.6269, 0.7717, 0.7813, 0.4418, 0.4085, -0.1762, 0.75, -0.0126, 0.7105, 0.1932, -0.0069, -0.5672, -0.5628, -1.0383, 1.2177, 1.2177, 1.2176, 1.2175, 1.2175, 1.2174, 1.2174, 1.2173, 1.2173, 1.2173, 1.2173, 1.2172, 1.2172, 1.2172, 1.2172, 1.2172, 1.2172, 1.2172, 1.2172, 1.2171, 1.2171, 1.2171, 1.2171, 1.2169, 1.2169, 1.2168, 1.2168, 1.2168, 1.2167, 1.2167, 1.2121, 1.2164, 1.2157, 1.2141, 1.2162, 1.2135, 1.2146, 1.2161, 1.2146, 1.2154, 1.214, 1.2114, 1.2147, 1.2159, 1.205, 1.2059, 1.2113, 1.2006, 1.1541, 1.1781, 1.0319, 0.9921, 1.0464, 1.0641, 1.1247, 1.0838, 0.3201, 0.8654, 0.5874, 1.1242, 1.001, 0.7118, 0.8012, 1.058, 0.1719, -0.671, 0.5866, 0.2664, -0.5857, 0.3892, 0.4709, 0.2986]}, \"token.table\": {\"Topic\": [2, 3, 2, 3, 1, 2, 3, 2, 2, 2, 1, 2, 2, 3, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 1, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 2, 3, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 2, 2, 2, 3, 2, 2, 2, 3, 1, 2, 1, 1, 2, 3, 1, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 1, 1, 2, 3, 1, 2, 3, 2, 3, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 2, 2, 3, 3, 3, 2, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 3, 2, 2, 3, 3, 1, 2, 3, 2, 3, 1, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 2, 3, 2, 3, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 3, 1, 3, 1, 2, 3, 2, 1, 2, 3, 1, 2, 3, 3, 3, 2, 3, 2, 1, 2, 3, 1, 2, 3, 3, 3, 2, 1, 3, 1, 3, 1, 2, 3, 1, 2, 1, 2, 3, 3, 1, 2, 2, 3, 1, 2, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 2, 1, 2, 3, 2, 1, 2, 3, 3, 1, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 3, 3, 2, 1, 2, 3, 1, 3, 1, 1, 2, 3, 1, 2, 3, 3, 2, 3, 1, 2, 3, 2, 3, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 1, 2, 1, 2, 3, 2, 3, 1, 2, 1, 2, 1, 3, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 1, 2, 3], \"Freq\": [0.9950145977970618, 0.005105018925264776, 0.000786302303331918, 0.9989970763832018, 0.9988121384146569, 0.0008749996832366683, 0.00043749984161833415, 0.99922222416068, 0.9992679755566742, 0.9993756903571427, 0.9986686046503717, 0.0011419881128077434, 0.999352418524175, 0.0003861485388424169, 0.9994206540397038, 0.9991327306608979, 0.9918018009716449, 0.004603854513794108, 0.003288467509852934, 0.5579539278820047, 0.0053616509119718304, 0.43668935512825885, 0.00097754009777303, 0.9970908997284906, 0.002443850244432575, 0.004168279996187098, 0.9958982821659327, 0.9994124733427521, 0.06119938249274416, 0.000445626571549108, 0.938341017491905, 0.034566695014065216, 0.9652684607687084, 0.00025989996251176854, 0.9999769554184541, 0.11492228858343125, 0.8846552000311305, 0.0004480401114363791, 0.9996062594850397, 0.1937705825237609, 0.0011561490604043013, 0.8051422056655554, 0.584828810089585, 0.2703236640979786, 0.14489850933834328, 0.008002129655665385, 0.9790605633706599, 0.013203513931847887, 0.9999131238862623, 0.007961494951198798, 0.009218573101388081, 0.98303511344802, 0.004615159722639091, 0.1973735597270699, 0.7979913086779983, 0.0015020214409614653, 0.9985438539511822, 0.1925109647749901, 0.39995233241981326, 0.40754045155124324, 0.011150236761843913, 0.001592890965977702, 0.9871941761646809, 0.00021541030068687728, 0.0019386927061818956, 0.9979959230823024, 0.0035029559043034636, 0.9963720200303164, 0.1573902232073038, 0.8425804190666868, 0.9996504298815272, 0.0010780210185504491, 0.9982474631777158, 0.0005390105092752246, 0.9961345371376453, 0.0036175239050888403, 0.9989526377385689, 0.0006370159406854356, 0.9994780109354483, 0.9988342012867764, 0.0008127210750909491, 0.00027090702503031633, 0.39702347026091833, 0.00011972963518121782, 0.602958442772613, 0.000494901500218281, 0.002474507501091405, 0.9967316214396179, 0.007083318047801883, 0.9929145239948168, 0.990859466453686, 0.008307292433407602, 0.0008593750793180277, 0.9937144848684497, 0.00631801883952297, 0.9998662940922569, 0.9998103276204778, 0.0004140001356606533, 0.9988022060644671, 0.999809262628157, 0.9996601790709592, 0.0006428682823607455, 0.9407794758945467, 0.059098527141652125, 0.9991936241215615, 0.0012429048409321416, 0.9974311348480436, 0.0012429048409321416, 0.9997520336581938, 0.014427454408393136, 0.9829487416500889, 0.002509122505807502, 0.9991936240838293, 0.664640436552242, 0.33250694999644853, 0.0028632197116878755, 0.985076012383525, 0.012902210671900359, 0.002020828177526562, 0.999284922912688, 0.000774039444548945, 0.7607276871473299, 0.2331262267064398, 0.006212557673722579, 0.9492551049612473, 0.04023300598988076, 0.010484965197362866, 0.0012431275203466949, 0.9986457746785117, 0.9997264190437457, 0.00012035330462260361, 0.16945745290862588, 0.8304378018959648, 0.09918879126524396, 0.9004623251759499, 0.00034657159771224303, 0.0007167760124553473, 0.9991857613627543, 0.9990715172281633, 0.8352119092864676, 0.16180425623947992, 0.003019470907511593, 0.06086949974755464, 0.028485726482845766, 0.9106436981937115, 0.0006596883509635813, 0.0006596883509635813, 0.9994278517098256, 0.9993878910404252, 0.00024004113560637707, 0.00408069930530841, 0.995690630495252, 0.998493817118322, 0.1252490693944639, 0.8747483678416894, 0.9994872270390032, 0.9985578953504588, 0.9992702922482799, 0.0003839743516505142, 0.9979493399396864, 0.0019198717582525708, 0.99919362421912, 0.9992116875162015, 0.9943974121144781, 0.0030523795051262967, 0.0027132262267789307, 0.00024395177346444878, 0.9848333094759797, 0.015125009954795824, 0.9998184603461274, 0.8192186636262604, 0.17988347695508805, 0.0008857288480331103, 0.21536843197297836, 0.7496478112905592, 0.03497436074774862, 0.9969828867307151, 0.0030542145326542696, 0.9777301491386167, 0.011928014206833724, 0.010459950919838805, 0.9912991608117265, 0.008529516182001186, 0.0001814790677021529, 0.9990108115801196, 0.7116820689557316, 0.20663442249630523, 0.08164966310915386, 0.9987787412720258, 0.0005153657075707048, 0.0010307314151414095, 0.7837212464306411, 0.1964997259874976, 0.019739698501027157, 0.9969197060967867, 0.0002682776388850341, 0.0028169152082928584, 0.8132507495686443, 0.1867339051668566, 0.8961619965727403, 0.10381087774502606, 0.9990994393726643, 0.0007172285996932264, 0.9993484800306909, 0.00044494589493797456, 0.007760579821524162, 0.13461621151951528, 0.8575440702784198, 0.9994629918476603, 0.0005738371139688905, 0.9993373339768228, 0.9989925707069008, 0.4596065376469841, 0.5390045062759182, 0.0013775672790509062, 0.9987230501850995, 0.0008869654086901417, 0.9989530875316335, 0.07784087856568372, 0.21911203298838136, 0.7030484206721541, 0.0012818800307633918, 0.9987447789685275, 0.00031459192113878246, 0.9975709819310792, 0.0018875515268326948, 0.001728493147403741, 0.001440410956169784, 0.9967643816694906, 0.9996278196589906, 0.0004137153747932259, 0.0033097229983458073, 0.996226622502088, 0.0005574740419945188, 0.9989934832541778, 0.0005574740419945188, 0.0029627797757124643, 0.9969753945272442, 0.0020207483827676563, 0.9978455514106687, 0.5582022030828262, 0.2905303030787355, 0.1512573186310782, 0.9994124732300902, 0.1474055858071035, 0.8523643606784802, 0.7125989381170077, 0.12268830572245255, 0.16471627352395304, 0.9994998983744461, 0.9980886567723081, 0.0002635565505076071, 0.0018448958535532496, 0.002365956530048935, 0.997487273068631, 0.0006016965505827297, 0.0012033931011654593, 0.9982145774167485, 0.9992048131187591, 0.46103912401202507, 0.007018804574511426, 0.5320529114717878, 0.0004511964445247789, 0.9948881601771374, 0.004511964445247789, 0.9994609135838302, 0.9994822752442055, 0.9983127308217404, 0.0013551756526991952, 0.9996823076670398, 0.0002506268569774361, 0.9994999056260151, 0.0005012537139548722, 0.18294230598033315, 0.1578152904601428, 0.6593270095853452, 0.9991181290065063, 0.9992098445612436, 0.9993641241720923, 0.0005423838105702306, 0.9996133628809349, 0.0004010049373425826, 0.9997053087950585, 0.09734512598904517, 0.7567744363527666, 0.14568201613532966, 0.0007685366218451139, 0.9990976083986481, 0.00017718882558314243, 0.9656790994281261, 0.034197443337546485, 0.999622555625931, 0.16319348095374964, 0.8367986796508042, 0.00010231938094720086, 0.9998649906160468, 0.9994405738636197, 0.00042010953083800745, 0.9998977893752223, 0.9991775794893886, 0.07237605734332814, 0.016473654843070958, 0.911182154762646, 0.9591650400000782, 0.03830394830166583, 0.0025630894774348882, 0.0003367736649469793, 0.0003367736649469793, 0.9995442375626346, 0.9993579963483621, 0.2947949852557798, 0.7051481064091556, 0.9992688538002633, 0.0016876980062556688, 0.993632201183025, 0.004641169517203089, 0.3871459230943733, 0.08041696872123803, 0.5324332551228569, 0.9992069912021492, 0.9925466973178622, 0.00018319429629344079, 0.007236174703590911, 0.9548833075546137, 0.04484824981805083, 0.014572778305284514, 0.9726843759500571, 0.012629741197913246, 0.999453512152431, 0.9993100058935681, 0.000797533923298937, 0.014103987003857704, 0.9858030916301006, 0.00016399984888206632, 0.9993769023369903, 0.006258031264030458, 0.993709490714731, 0.005346234233472634, 0.00018122827910076723, 0.9943995674259097, 0.9994124731925362, 0.8983678277606365, 0.10156967430066008, 0.9994536457219454, 0.9104250018848461, 0.08924391834092282, 0.00034258701858319704, 0.9988256718055221, 0.09796551454251679, 0.901614820281129, 0.0003558069535442498, 0.999115230564697, 0.9991645554309655, 0.0004538597232373767, 0.9989452508454661, 0.0004538597232373767, 0.8894313695379525, 0.03440455478194669, 0.0761719520269559, 0.9989065394947371, 6.455915792999638e-05, 0.6485613005647437, 0.3513954966129703, 0.011555571095085095, 0.9884140275974573, 0.2565515430807932, 0.7336629476629732, 0.009928739746043138, 0.9992985753614408, 0.00018232048446660114, 0.0007292819378664046, 0.969330735569895, 0.029579900923412946, 0.0010470761388818742, 0.9996346978208654, 0.9926790440685342, 0.007043845218935367, 0.0002515659006762631, 0.9988097125121357, 0.001058061136135737, 9.618737601233972e-05, 0.5434216106653187, 0.34218009318836345, 0.1144075984504855, 0.9991275815967203, 0.19344153671552347, 0.4203786762155032, 0.3862627844905941, 0.9995712316164036, 0.9999205432716701, 0.9996825606384938, 0.0001684473360450849, 0.9977135713950378, 0.002021368032541019, 0.998969265554351, 0.0011321903274133182, 0.9997698466190644, 0.8885061926982294, 0.00014250299802698145, 0.11143734445709949, 0.9894414439417346, 0.002878793843298617, 0.0074848639925764035, 0.9998310802938036, 0.9834171159625773, 0.01662272162778744, 3.153156376022787e-05, 0.9996451658905042, 0.0003153156376022787, 0.9891428858193919, 0.010816637689100947, 0.038756140109221994, 0.9611522747087055, 0.5601544024453944, 0.041067371909583136, 0.39884267566481574, 0.002523377715879288, 0.9935799756274696, 0.0041004887883038426, 0.9996583294440329, 0.9996011228485648, 0.0003206933342472136, 0.0006624270072086394, 0.9989399268706283, 0.8891659755758415, 0.11082715184354415, 8.78883043961492e-05, 0.0006683278485147912, 0.9991501335296129, 0.9186455683401045, 0.0813793200826241, 0.998851607482719, 0.999492898805519, 0.0016061107815191075, 0.9981978507141253, 0.9986621243545944, 0.4743727709409403, 0.5213844021845851, 0.004256458504492166, 0.0007305632040437343, 0.8509234919099395, 0.14830433042087807, 0.25823850674625304, 0.2679174096539731, 0.47386295485712754, 0.006357952005330292, 0.9934300008328582, 0.9997557539130351, 0.4679519769503532, 0.3441395433183692, 0.1878649114860168], \"Term\": [\"access\", \"access\", \"accord\", \"accord\", \"actually\", \"actually\", \"actually\", \"administer\", \"appointment\", \"approve\", \"arent\", \"arent\", \"available\", \"available\", \"average\", \"barometer\", \"believe\", \"believe\", \"believe\", \"biden\", \"biden\", \"biden\", \"billion\", \"billion\", \"billion\", \"book\", \"book\", \"bradfordcounty\", \"break\", \"break\", \"break\", \"business\", \"business\", \"business\", \"case\", \"check\", \"check\", \"check\", \"chill\", \"china\", \"china\", \"china\", \"come\", \"come\", \"come\", \"company\", \"company\", \"company\", \"confirm\", \"contract\", \"contract\", \"contract\", \"coronavirus\", \"coronavirus\", \"coronavirus\", \"county\", \"county\", \"covid\", \"covid\", \"covid\", \"daily\", \"daily\", \"daily\", \"data\", \"data\", \"data\", \"death\", \"death\", \"deaths\", \"deaths\", \"decline\", \"deliver\", \"deliver\", \"deliver\", \"democrats\", \"democrats\", \"dems\", \"department\", \"department\", \"didnt\", \"didnt\", \"didnt\", \"die\", \"die\", \"die\", \"disease\", \"disease\", \"disease\", \"distance\", \"distance\", \"doesnt\", \"doesnt\", \"doesnt\", \"dont\", \"dont\", \"dose\", \"effective\", \"effective\", \"eligible\", \"employees\", \"ensure\", \"ensure\", \"feel\", \"feel\", \"fhumidity\", \"free\", \"free\", \"free\", \"fuck\", \"fund\", \"fund\", \"fund\", \"fwind\", \"get\", \"get\", \"get\", \"go\", \"go\", \"go\", \"gonna\", \"gonna\", \"good\", \"good\", \"good\", \"happen\", \"happen\", \"happen\", \"happy\", \"happy\", \"hate\", \"health\", \"health\", \"health\", \"help\", \"help\", \"help\", \"higher\", \"higher\", \"highest\", \"home\", \"home\", \"home\", \"hospital\", \"hospital\", \"hospital\", \"hospitals\", \"hospitals\", \"hospitals\", \"imagine\", \"increase\", \"increase\", \"increase\", \"index\", \"india\", \"india\", \"infections\", \"infectious\", \"info\", \"information\", \"information\", \"information\", \"inhgwind\", \"investigation\", \"isnt\", \"isnt\", \"isnt\", \"join\", \"join\", \"join\", \"kid\", \"know\", \"know\", \"know\", \"learn\", \"learn\", \"learn\", \"lie\", \"lie\", \"life\", \"life\", \"life\", \"like\", \"like\", \"like\", \"literally\", \"live\", \"live\", \"live\", \"lock\", \"lock\", \"lock\", \"lockdown\", \"lockdown\", \"lockdown\", \"lose\", \"lose\", \"lose\", \"love\", \"love\", \"mask\", \"mask\", \"maybe\", \"maybe\", \"middle\", \"middle\", \"million\", \"million\", \"million\", \"minimum\", \"minister\", \"minister\", \"nations\", \"need\", \"need\", \"need\", \"negative\", \"negative\", \"nepa\", \"news\", \"news\", \"news\", \"number\", \"number\", \"offer\", \"offer\", \"offer\", \"office\", \"office\", \"office\", \"officer\", \"officials\", \"officials\", \"officials\", \"online\", \"online\", \"online\", \"outbreak\", \"outbreak\", \"package\", \"package\", \"pandemic\", \"pandemic\", \"pandemic\", \"patemp\", \"patients\", \"patients\", \"people\", \"people\", \"people\", \"pfizer\", \"point\", \"point\", \"point\", \"police\", \"police\", \"population\", \"population\", \"population\", \"practice\", \"president\", \"president\", \"president\", \"prevent\", \"prevent\", \"prevent\", \"price\", \"prime\", \"program\", \"program\", \"programme\", \"provide\", \"provide\", \"provide\", \"public\", \"public\", \"public\", \"publish\", \"radio\", \"rain\", \"rat\", \"rat\", \"rate\", \"rate\", \"read\", \"read\", \"read\", \"ready\", \"ready\", \"receive\", \"receive\", \"receive\", \"record\", \"relief\", \"relief\", \"report\", \"report\", \"republican\", \"republican\", \"republicans\", \"resources\", \"response\", \"response\", \"response\", \"right\", \"right\", \"right\", \"rise\", \"rise\", \"rise\", \"rollout\", \"safe\", \"safe\", \"safely\", \"safety\", \"safety\", \"safety\", \"say\", \"say\", \"say\", \"sayre\", \"school\", \"school\", \"school\", \"service\", \"service\", \"share\", \"share\", \"share\", \"shit\", \"site\", \"site\", \"social\", \"social\", \"social\", \"sorry\", \"south\", \"south\", \"state\", \"state\", \"state\", \"statscases\", \"stay\", \"stay\", \"stayathome\", \"stop\", \"stop\", \"stop\", \"sunset\", \"support\", \"support\", \"support\", \"surge\", \"survival\", \"symptoms\", \"symptoms\", \"symptoms\", \"tell\", \"tell\", \"tell\", \"tenanttips\", \"test\", \"test\", \"test\", \"texas\", \"texas\", \"thank\", \"thank\", \"thank\", \"thats\", \"thats\", \"thats\", \"theres\", \"theres\", \"theres\", \"thing\", \"things\", \"things\", \"things\", \"think\", \"think\", \"think\", \"time\", \"time\", \"time\", \"tire\", \"today\", \"today\", \"today\", \"toll\", \"total\", \"train\", \"travel\", \"travel\", \"travel\", \"trillion\", \"trillion\", \"true\", \"trump\", \"trump\", \"trump\", \"try\", \"try\", \"try\", \"unite\", \"vaccination\", \"vaccination\", \"vaccine\", \"vaccine\", \"vaccine\", \"vaccines\", \"vaccines\", \"variant\", \"variant\", \"virus\", \"virus\", \"virus\", \"visit\", \"visit\", \"visit\", \"volunteer\", \"vote\", \"vote\", \"wage\", \"wage\", \"want\", \"want\", \"want\", \"wave\", \"wave\", \"wear\", \"wear\", \"weewx\", \"welcome\", \"white\", \"white\", \"wind\", \"work\", \"work\", \"work\", \"workers\", \"workers\", \"workers\", \"world\", \"world\", \"world\", \"wuhan\", \"wuhan\", \"yall\", \"year\", \"year\", \"year\"]}, \"R\": 30, \"lambda.step\": 0.01, \"plot.opts\": {\"xlab\": \"PC1\", \"ylab\": \"PC2\"}, \"topic.order\": [1, 3, 2]};\n",
              "\n",
              "function LDAvis_load_lib(url, callback){\n",
              "  var s = document.createElement('script');\n",
              "  s.src = url;\n",
              "  s.async = true;\n",
              "  s.onreadystatechange = s.onload = callback;\n",
              "  s.onerror = function(){console.warn(\"failed to load library \" + url);};\n",
              "  document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
              "}\n",
              "\n",
              "if(typeof(LDAvis) !== \"undefined\"){\n",
              "   // already loaded: just create the visualization\n",
              "   !function(LDAvis){\n",
              "       new LDAvis(\"#\" + \"ldavis_el761406533827594721218944773\", ldavis_el761406533827594721218944773_data);\n",
              "   }(LDAvis);\n",
              "}else if(typeof define === \"function\" && define.amd){\n",
              "   // require.js is available: use it to load d3/LDAvis\n",
              "   require.config({paths: {d3: \"https://d3js.org/d3.v5\"}});\n",
              "   require([\"d3\"], function(d3){\n",
              "      window.d3 = d3;\n",
              "      LDAvis_load_lib(\"https://cdn.jsdelivr.net/gh/bmabey/pyLDAvis@3.3.1/pyLDAvis/js/ldavis.v3.0.0.js\", function(){\n",
              "        new LDAvis(\"#\" + \"ldavis_el761406533827594721218944773\", ldavis_el761406533827594721218944773_data);\n",
              "      });\n",
              "    });\n",
              "}else{\n",
              "    // require.js not available: dynamically load d3 & LDAvis\n",
              "    LDAvis_load_lib(\"https://d3js.org/d3.v5.js\", function(){\n",
              "         LDAvis_load_lib(\"https://cdn.jsdelivr.net/gh/bmabey/pyLDAvis@3.3.1/pyLDAvis/js/ldavis.v3.0.0.js\", function(){\n",
              "                 new LDAvis(\"#\" + \"ldavis_el761406533827594721218944773\", ldavis_el761406533827594721218944773_data);\n",
              "            })\n",
              "         });\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lda_viz1 = gensimvis.prepare(lda_model_second_wave, bow_corpus_second_wave, lexicon_second_wave)"
      ],
      "metadata": {
        "id": "HekPwqHeNHaE"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lda_viz1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 862
        },
        "id": "jRqVeBekNWe_",
        "outputId": "64825832-f36e-4c93-a57f-47536c2bd3f6"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PreparedData(topic_coordinates=              x         y  topics  cluster       Freq\n",
              "topic                                                \n",
              "0      0.191591 -0.086928       1        1  37.643018\n",
              "1     -0.180695 -0.103664       2        1  31.673205\n",
              "2     -0.010897  0.190592       3        1  30.683778, topic_info=        Term          Freq         Total Category  logprob  loglift\n",
              "19   vaccine  20861.000000  20861.000000  Default  30.0000  30.0000\n",
              "82      test  16235.000000  16235.000000  Default  29.0000  29.0000\n",
              "0    omicron  13524.000000  13524.000000  Default  28.0000  28.0000\n",
              "236     mask  10576.000000  10576.000000  Default  27.0000  27.0000\n",
              "319     case  10679.000000  10679.000000  Default  26.0000  26.0000\n",
              "..       ...           ...           ...      ...      ...      ...\n",
              "533   deaths   2079.504593   5441.080813   Topic3  -5.7768   0.2196\n",
              "806     time   2169.155167   9460.594249   Topic3  -5.7346  -0.2914\n",
              "460    today   1936.102175   5212.651344   Topic3  -5.8482   0.1910\n",
              "662    years   1917.499836   5115.313610   Topic3  -5.8579   0.2002\n",
              "576      get   1868.709126   4952.729268   Topic3  -5.8837   0.2067\n",
              "\n",
              "[270 rows x 6 columns], token_table=      Topic      Freq    Term\n",
              "term                         \n",
              "436       2  0.997955  africa\n",
              "436       3  0.001641  africa\n",
              "2952      2  0.003243     age\n",
              "2952      3  0.996486     age\n",
              "726       1  0.006310    amid\n",
              "...     ...       ...     ...\n",
              "614       2  0.039928    year\n",
              "614       3  0.299832    year\n",
              "662       1  0.575527   years\n",
              "662       2  0.049655   years\n",
              "662       3  0.374757   years\n",
              "\n",
              "[519 rows x 3 columns], R=30, lambda_step=0.01, plot_opts={'xlab': 'PC1', 'ylab': 'PC2'}, topic_order=[1, 2, 3])"
            ],
            "text/html": [
              "\n",
              "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.jsdelivr.net/gh/bmabey/pyLDAvis@3.3.1/pyLDAvis/js/ldavis.v1.0.0.css\">\n",
              "\n",
              "\n",
              "<div id=\"ldavis_el761406533149701128729283870\"></div>\n",
              "<script type=\"text/javascript\">\n",
              "\n",
              "var ldavis_el761406533149701128729283870_data = {\"mdsDat\": {\"x\": [0.19159147141219765, -0.18069486132270526, -0.010896610089492272], \"y\": [-0.08692808613696038, -0.10366361998811806, 0.19059170612507847], \"topics\": [1, 2, 3], \"cluster\": [1, 1, 1], \"Freq\": [37.64301770415, 31.673204717093718, 30.68377757875628]}, \"tinfo\": {\"Term\": [\"vaccine\", \"test\", \"omicron\", \"mask\", \"case\", \"pandemic\", \"positive\", \"wear\", \"die\", \"variant\", \"like\", \"home\", \"mandate\", \"report\", \"dont\", \"covid\", \"want\", \"stay\", \"coronavirus\", \"think\", \"dose\", \"work\", \"vaccines\", \"booster\", \"virus\", \"deaths\", \"school\", \"party\", \"patients\", \"people\", \"yall\", \"gonna\", \"hate\", \"brexit\", \"sleep\", \"relief\", \"stayathome\", \"scar\", \"money\", \"invest\", \"stream\", \"profit\", \"prepandemic\", \"jimin\", \"cool\", \"dream\", \"sound\", \"anymore\", \"investment\", \"excite\", \"glad\", \"shit\", \"worth\", \"kiss\", \"asian\", \"theory\", \"spend\", \"exams\", \"retweet\", \"content\", \"stay\", \"sick\", \"home\", \"exam\", \"hope\", \"happy\", \"parent\", \"fuck\", \"shes\", \"truth\", \"guy\", \"feel\", \"vote\", \"common\", \"want\", \"great\", \"cold\", \"bidens\", \"hard\", \"thank\", \"pandemic\", \"support\", \"like\", \"miss\", \"thing\", \"life\", \"fund\", \"thats\", \"game\", \"love\", \"think\", \"learn\", \"dont\", \"work\", \"hear\", \"go\", \"live\", \"look\", \"help\", \"good\", \"year\", \"know\", \"covid\", \"time\", \"need\", \"people\", \"tell\", \"come\", \"years\", \"get\", \"care\", \"start\", \"kid\", \"take\", \"wear\", \"mask\", \"positive\", \"rapid\", \"weekly\", \"survival\", \"february\", \"south\", \"surge\", \"chill\", \"barometer\", \"sayre\", \"bradfordcounty\", \"nepa\", \"patemp\", \"statscases\", \"fhumidity\", \"fwind\", \"inhgwind\", \"weewx\", \"cloth\", \"delta\", \"ship\", \"contagious\", \"flatten\", \"detect\", \"france\", \"positivity\", \"africa\", \"athome\", \"test\", \"case\", \"variant\", \"omicron\", \"infections\", \"rate\", \"travel\", \"negative\", \"quarantine\", \"countries\", \"distance\", \"florida\", \"kit\", \"chain\", \"measure\", \"supply\", \"amid\", \"rise\", \"require\", \"mild\", \"record\", \"coronavirus\", \"hours\", \"current\", \"daily\", \"virus\", \"report\", \"city\", \"spread\", \"wave\", \"covid\", \"free\", \"update\", \"state\", \"health\", \"school\", \"close\", \"public\", \"deaths\", \"restrictions\", \"days\", \"high\", \"face\", \"number\", \"say\", \"vaccinate\", \"week\", \"time\", \"people\", \"protest\", \"pfizer\", \"boris\", \"convoy\", \"police\", \"die\", \"johnson\", \"rogan\", \"ottawa\", \"drug\", \"hospitalize\", \"street\", \"down\", \"moderna\", \"dose\", \"djokovic\", \"investigate\", \"monoclonal\", \"walkin\", \"novak\", \"antivaccine\", \"treatments\", \"treatment\", \"robert\", \"mrna\", \"cure\", \"antivax\", \"johnsons\", \"facts\", \"morrison\", \"party\", \"age\", \"prime\", \"truckers\", \"clinic\", \"fire\", \"antibodies\", \"gate\", \"approve\", \"vaccine\", \"patients\", \"second\", \"fake\", \"claim\", \"fauci\", \"thousands\", \"natural\", \"immunity\", \"heart\", \"death\", \"unvaccinated\", \"booster\", \"study\", \"shots\", \"mandate\", \"misinformation\", \"vaccines\", \"children\", \"lie\", \"covid\", \"people\", \"say\", \"minister\", \"rule\", \"vaccinate\", \"vaccination\", \"lockdown\", \"break\", \"hospital\", \"risk\", \"data\", \"know\", \"deaths\", \"time\", \"today\", \"years\", \"get\"], \"Freq\": [20861.0, 16235.0, 13524.0, 10576.0, 10679.0, 20181.0, 6083.0, 5199.0, 4997.0, 4580.0, 8324.0, 5801.0, 6548.0, 5922.0, 8021.0, 96695.0, 5083.0, 4106.0, 4245.0, 5695.0, 2676.0, 7815.0, 4568.0, 3053.0, 3909.0, 5441.0, 5912.0, 2282.0, 2414.0, 17547.0, 760.8379512977551, 722.4417988673714, 639.2121167767739, 528.2792225835847, 478.6099325030023, 550.0021419579664, 360.78614680224337, 389.18986558363895, 1300.184580375588, 319.4614044181479, 344.45936923003904, 451.96968866738837, 476.36926958019393, 523.8927353025207, 288.1819062429887, 294.80241918501633, 484.04946810012814, 371.28993714807956, 273.13305316883964, 295.7064286249996, 391.05138989934244, 821.1264769500493, 591.8407090460219, 384.1184464259338, 281.31440089989695, 245.5932566827843, 1201.9302939797467, 463.54080822480785, 224.3904158944616, 270.5291618983662, 4082.293855205691, 2335.755476442789, 5671.525965367229, 1105.1519237592981, 1536.8763344365523, 799.5137792525103, 1736.9711372129518, 1502.2298276074223, 636.2776323594745, 639.5729250397952, 619.7990124468023, 2479.465949128069, 1157.5930973226027, 646.9031457745197, 4868.357283233081, 1654.386156086948, 956.5281521001141, 702.4902376847889, 1219.4673295249186, 2457.2839804308715, 18270.05991892263, 2467.5577908518517, 7639.538414261504, 1280.382058069084, 1872.0011256997157, 2239.1234614402006, 1093.6793807189506, 2608.196049946247, 1279.516961673273, 1992.0754703129646, 5042.7498286437985, 2288.9070466074218, 6664.045520443828, 6443.139044025726, 2115.064842821427, 5346.728178464739, 4241.624943933125, 2963.3795570308716, 3370.253771826906, 2640.0974619523745, 3571.7600829814473, 4405.939969352578, 26904.47107313886, 5207.148047468035, 4177.568322529323, 6763.527963854506, 2940.9623848597853, 3119.7478870847726, 2943.5584408067093, 2832.320807638284, 2498.439987804461, 2507.242578451932, 2373.5864312833105, 2392.5723547318144, 5197.884811331395, 10568.406419705785, 6078.838732490258, 1126.215133828624, 777.5565519446568, 671.1256856009215, 856.2796552646207, 1084.9527019240588, 1837.3277317384868, 563.0421236018315, 491.10193937955256, 480.29363156656586, 480.29363156656586, 480.29363156656586, 480.29363156656586, 480.29363156656586, 480.0388744203846, 480.0388744203846, 480.0388744203846, 477.01719176439667, 475.96078428215503, 1182.9534776883893, 458.36096869276594, 419.8916315585125, 421.2009816773473, 394.94143923955977, 630.002204808376, 368.3829865889452, 608.2075253081488, 827.5679845693592, 16122.12123868288, 10641.927445003726, 4570.98255502591, 13319.379083792594, 1479.8648267531605, 1537.351393722223, 2022.8417404269173, 1332.3001973958799, 1234.9924030044951, 1345.5549883253998, 1213.7820762365343, 712.4146899903449, 558.7925824687359, 562.1811186410197, 1862.7639303700262, 1020.388418532884, 1094.532506100973, 2072.013337369337, 1702.4878952212346, 1708.0090043512953, 2120.8681612600944, 3929.2693843680786, 1230.474999933748, 1439.4199725465965, 1470.9630846481334, 3378.584272673968, 4883.251106796379, 1317.310493365443, 3289.342658883468, 1666.2135098521564, 36604.763532987454, 3055.6951140268015, 1889.790445849522, 3197.341700200997, 4751.781580710658, 3732.3681586631596, 1866.1535955704983, 2702.8476762748546, 3361.1646580479032, 2429.2402754633285, 2823.760466221382, 2002.500362139521, 2137.4277789862294, 2321.0092139959365, 3211.015844457564, 2519.553337004434, 1984.3454275834529, 2084.2910350468364, 2127.935232559289, 2109.409680026168, 1368.1962994852145, 1562.9624170022291, 1214.3889530557271, 1176.9154447288217, 4993.348168179827, 1822.750314087248, 825.8575855482347, 899.1306041932172, 681.2424233592262, 645.7582281092236, 639.6136858776771, 536.358391792919, 515.7295909697468, 2672.7708308047772, 495.61528652437573, 467.85994328428495, 484.83297214562793, 366.0347389718516, 371.77818418667516, 380.95825895352874, 570.3680437835466, 1126.24925082947, 383.652187144149, 592.2656830657368, 383.37788803512785, 431.32476291206444, 331.5584034928338, 367.0754896357153, 356.33618341974625, 2261.3743551980724, 1228.818679953221, 1246.851873699046, 1434.9787183926949, 618.2622619816223, 721.6823620961384, 598.2091689722859, 617.197800187144, 532.3217182913482, 19985.10401810202, 2358.9849939350984, 1351.6847587574482, 913.5011899840378, 1528.4585422364182, 1090.7268521433207, 1167.849042762773, 1081.090836163067, 1645.5154331028825, 1100.6812300914642, 2281.860459546557, 2394.2544999365705, 2826.8120853893224, 2203.6151347797713, 959.7738324752371, 5399.483975941174, 1309.7015262012242, 3738.1488827455273, 2764.8875185464776, 1274.4938957036952, 33186.592787245725, 8655.72799632648, 5441.128065110254, 1698.8149296990919, 1957.592818558128, 3511.9736031675, 2531.0012386664316, 2767.1290993029675, 2586.1118437631617, 1805.7381442821227, 1918.18202882809, 1892.7561967481356, 2274.6175880572, 2079.504592715049, 2169.155166621557, 1936.1021747782008, 1917.4998357719885, 1868.7091258974622], \"Total\": [20861.0, 16235.0, 13524.0, 10576.0, 10679.0, 20181.0, 6083.0, 5199.0, 4997.0, 4580.0, 8324.0, 5801.0, 6548.0, 5922.0, 8021.0, 96695.0, 5083.0, 4106.0, 4245.0, 5695.0, 2676.0, 7815.0, 4568.0, 3053.0, 3909.0, 5441.0, 5912.0, 2282.0, 2414.0, 17547.0, 761.5754064135821, 723.1721548332021, 639.9222709423009, 528.9796207234803, 479.3227886459453, 550.8737899725943, 361.44731663636924, 389.9388409727292, 1302.856215715653, 320.1239079971489, 345.20729917590586, 452.9560014467476, 477.4514761850448, 525.0852584913229, 288.840974024003, 295.48950247331555, 485.195698549166, 372.1999111171294, 273.8085250905396, 296.45026617062507, 392.0755886558328, 823.298526237333, 593.4346828171033, 385.1567767245243, 282.1224720287799, 246.31156669308598, 1205.4583075663224, 464.92893578008386, 225.0655397466536, 271.4060076103742, 4106.4651272230785, 2347.630187239306, 5801.146963152578, 1112.1739766557353, 1553.1955849988267, 802.8525602924356, 1758.053185696516, 1518.5556404744161, 638.3626011001707, 641.8005376512602, 622.2659064185286, 2529.589608585299, 1172.2662491228668, 651.3081070304273, 5083.018005297643, 1695.9194701488493, 970.3076759288404, 708.5613001473359, 1245.2576777571066, 2546.5963538674073, 20181.93193533968, 2575.3025415373536, 8324.38257275429, 1322.8053777730966, 1973.085089935701, 2389.310620938488, 1125.1843006090485, 2810.397853855122, 1328.558612123311, 2118.4454809163217, 5695.844111325998, 2477.569255102806, 8021.1263439639115, 7815.187822339137, 2335.7831540142583, 6556.011227290884, 5144.78259337682, 3754.5293011180106, 4495.49111297829, 3324.742722879435, 5409.699014152575, 7396.609089128941, 96695.82739337203, 9460.594249136428, 7294.55717518199, 17547.191192740276, 4397.969020514673, 5288.447680281994, 5115.313610052742, 4952.729268159002, 3960.044903811863, 4139.149016525477, 3329.004415965503, 4147.552195337864, 5199.4293078731835, 10576.07231727176, 6083.309083890774, 1127.0928761708578, 778.1943649429156, 671.7753391691269, 857.1636311473271, 1086.0970566825868, 1839.3223676313091, 563.6938043322209, 491.7132403856261, 480.90126565206134, 480.90126581585884, 480.9012662413784, 480.9012662881777, 480.9012680197512, 480.64651277188784, 480.64651277188784, 480.64651277188784, 477.624827559049, 476.6134224302846, 1184.6681366572702, 459.0439995752679, 420.5343058897565, 421.8664392533847, 395.58126201604534, 631.0399093483398, 369.00960411867004, 609.2456943988251, 828.9821972216535, 16235.047249367979, 10679.258646862852, 4580.0220535758035, 13524.902389259778, 1483.1094967181461, 1542.1458171508423, 2036.4058938167987, 1336.4286807672975, 1238.1197712829426, 1354.7410970997828, 1221.1274719794635, 713.695106906596, 559.7567879338462, 563.2754671916503, 1899.3600198930467, 1032.1193529334957, 1109.2877052313518, 2131.283131021669, 1748.4645001549509, 1760.4364334462775, 2227.1327617871475, 4245.217391156474, 1264.3682241581719, 1493.305320303143, 1554.4681642428159, 3909.362194551465, 5922.740021870186, 1386.9473344593462, 4333.356307229798, 1864.4752906998194, 96695.82739337203, 4109.8113038034035, 2216.9994855987347, 4652.108606032862, 8149.2675479207155, 5912.526883352627, 2203.1233915072294, 3840.492258095281, 5441.080813365721, 3318.021999263685, 4327.533592587129, 2499.5643490095795, 2885.1039386120856, 3479.517284531059, 10549.239348201725, 6199.412417103453, 3964.3652901004134, 9460.594249136428, 17547.191192740276, 2110.2354978532258, 1369.0106501828366, 1563.9867497999044, 1215.2154353447445, 1177.7776229434926, 4997.209890351334, 1824.4296140457254, 826.638865790727, 900.0157131940682, 681.9778892963091, 646.4710384604731, 640.3248289463486, 537.0288167323612, 516.3962114926901, 2676.2693930288406, 496.3212606563738, 468.58910192963083, 485.5901388041459, 366.70136485373064, 372.45807591053165, 381.6692935166235, 571.4374369379185, 1128.4003021236297, 384.4071912935148, 593.4360034711432, 384.14228582140896, 432.27774854541144, 332.2952933707985, 367.9018738678873, 357.1471715307464, 2282.254801773223, 1233.3343504423012, 1253.6028385362488, 1449.5975400980906, 619.7043164291223, 725.0562260300185, 599.8806953584831, 619.1992244109108, 533.6723145174285, 20861.015696259798, 2414.613442697668, 1372.543706687202, 921.4746337977634, 1564.8975944191598, 1109.1024996188073, 1191.9407188576652, 1102.3829593512598, 1705.831321418924, 1126.96003667625, 2410.0964250005645, 2547.6332812417904, 3053.1463356371523, 2420.296516115534, 987.3657810279789, 6548.99234834151, 1387.749114842799, 4568.290099685374, 3274.638724713296, 1349.0729480148943, 96695.82739337203, 17547.191192740276, 10549.239348201725, 2055.232997413606, 2554.0526892811986, 6199.412417103453, 3815.7362372087728, 4668.550110361816, 4214.265681166364, 2593.047548785687, 2980.088143047375, 3063.963270711666, 7396.609089128941, 5441.080813365721, 9460.594249136428, 5212.651344344761, 5115.313610052742, 4952.729268159002], \"Category\": [\"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Default\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic1\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic2\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\", \"Topic3\"], \"logprob\": [30.0, 29.0, 28.0, 27.0, 26.0, 25.0, 24.0, 23.0, 22.0, 21.0, 20.0, 19.0, 18.0, 17.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0, 10.0, 9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, -6.9867, -7.0384, -7.1608, -7.3515, -7.4502, -7.3112, -7.7328, -7.657, -6.4508, -7.8544, -7.7791, -7.5075, -7.4549, -7.3598, -7.9575, -7.9348, -7.4389, -7.7041, -8.0111, -7.9317, -7.6522, -6.9104, -7.2378, -7.6701, -7.9816, -8.1174, -6.5294, -7.4822, -8.2077, -8.0207, -5.3067, -5.865, -4.9779, -6.6133, -6.2836, -6.9371, -6.1612, -6.3064, -7.1654, -7.1603, -7.1917, -5.8053, -6.567, -7.1489, -5.1306, -6.2099, -6.7578, -7.0664, -6.5149, -5.8143, -3.8081, -5.8101, -4.68, -6.4662, -6.0863, -5.9072, -6.6238, -5.7547, -6.4668, -6.0241, -5.0954, -5.8852, -4.8166, -4.8503, -5.9642, -5.0368, -5.2684, -5.627, -5.4983, -5.7425, -5.4403, -5.2304, -3.421, -5.0633, -5.2836, -4.8018, -5.6346, -5.5756, -5.6337, -5.6722, -5.7977, -5.7941, -5.8489, -5.841, -4.8924, -4.1828, -4.7358, -6.4218, -6.7922, -6.9394, -6.6958, -6.4591, -5.9323, -7.115, -7.2517, -7.274, -7.274, -7.274, -7.274, -7.274, -7.2745, -7.2745, -7.2745, -7.2808, -7.2831, -6.3726, -7.3207, -7.4084, -7.4053, -7.4697, -7.0027, -7.5393, -7.0379, -6.7299, -3.7605, -4.1758, -5.0209, -3.9514, -6.1487, -6.1106, -5.8361, -6.2537, -6.3296, -6.2438, -6.3469, -6.8797, -7.1226, -7.1166, -5.9186, -6.5205, -6.4503, -5.8121, -6.0086, -6.0053, -5.7888, -5.1722, -6.3332, -6.1764, -6.1547, -5.3232, -4.9548, -6.2651, -5.35, -6.0301, -2.9405, -5.4236, -5.9042, -5.3783, -4.9821, -5.2236, -5.9168, -5.5463, -5.3284, -5.6531, -5.5026, -5.8462, -5.781, -5.6986, -5.3741, -5.6166, -5.8554, -5.8062, -5.7855, -5.7625, -6.1954, -6.0623, -6.3147, -6.346, -4.9008, -5.9086, -6.7002, -6.6152, -6.8927, -6.9462, -6.9558, -7.1319, -7.1711, -5.5258, -7.2109, -7.2685, -7.2329, -7.5139, -7.4984, -7.474, -7.0704, -6.39, -7.4669, -7.0327, -7.4676, -7.3498, -7.6129, -7.5111, -7.5408, -5.6929, -6.3029, -6.2883, -6.1478, -6.9898, -6.8351, -7.0227, -6.9915, -7.1394, -3.5139, -5.6507, -6.2076, -6.5994, -6.0846, -6.4221, -6.3537, -6.4309, -6.0109, -6.413, -5.6839, -5.6358, -5.4698, -5.7188, -6.55, -4.8226, -6.2391, -5.1903, -5.4919, -6.2664, -3.0068, -4.3507, -4.8149, -5.979, -5.8372, -5.2527, -5.5803, -5.4911, -5.5588, -5.9179, -5.8575, -5.8709, -5.6871, -5.7768, -5.7346, -5.8482, -5.8579, -5.8837], \"loglift\": [30.0, 29.0, 28.0, 27.0, 26.0, 25.0, 24.0, 23.0, 22.0, 21.0, 20.0, 19.0, 18.0, 17.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0, 10.0, 9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 0.9761, 0.976, 0.9759, 0.9757, 0.9755, 0.9754, 0.9752, 0.9751, 0.975, 0.975, 0.9749, 0.9748, 0.9748, 0.9747, 0.9747, 0.9747, 0.9747, 0.9746, 0.9746, 0.9745, 0.9744, 0.9744, 0.9743, 0.9743, 0.9742, 0.9741, 0.9741, 0.974, 0.974, 0.9738, 0.9711, 0.972, 0.9544, 0.9707, 0.9665, 0.9729, 0.965, 0.9662, 0.9738, 0.9735, 0.9731, 0.957, 0.9644, 0.9702, 0.9339, 0.9522, 0.9627, 0.9684, 0.9561, 0.9413, 0.8775, 0.9343, 0.8912, 0.9444, 0.9244, 0.9121, 0.9486, 0.9024, 0.9394, 0.9155, 0.8552, 0.8978, 0.7917, 0.784, 0.8778, 0.7731, 0.784, 0.7404, 0.6889, 0.7464, 0.5619, 0.459, -0.3023, 0.3799, 0.4196, 0.0237, 0.5746, 0.4493, 0.4244, 0.4182, 0.5164, 0.4757, 0.6388, 0.4269, 1.1494, 1.149, 1.149, 1.1489, 1.1489, 1.1487, 1.1487, 1.1486, 1.1486, 1.1485, 1.1485, 1.1484, 1.1484, 1.1484, 1.1484, 1.1484, 1.1484, 1.1484, 1.1484, 1.1484, 1.1483, 1.1483, 1.1482, 1.1482, 1.1481, 1.1481, 1.1481, 1.148, 1.148, 1.148, 1.1427, 1.1462, 1.1477, 1.1344, 1.1475, 1.1466, 1.143, 1.1466, 1.1472, 1.1429, 1.1437, 1.1479, 1.148, 1.1478, 1.1302, 1.1383, 1.1363, 1.1215, 1.1231, 1.1195, 1.1008, 1.0724, 1.1225, 1.1129, 1.0945, 1.0038, 0.9567, 1.0982, 0.874, 1.0373, 0.1783, 0.8533, 0.99, 0.7747, 0.6103, 0.6897, 0.9837, 0.7984, 0.668, 0.8379, 0.7228, 0.928, 0.8497, 0.7448, -0.0398, 0.2493, 0.4576, -0.363, -0.96, 1.181, 1.1808, 1.1808, 1.1808, 1.1807, 1.1807, 1.1805, 1.1805, 1.1805, 1.1804, 1.1803, 1.1803, 1.1802, 1.1801, 1.1801, 1.18, 1.1799, 1.1799, 1.1796, 1.1796, 1.1796, 1.1796, 1.1795, 1.1795, 1.1795, 1.1794, 1.1792, 1.1792, 1.1792, 1.1792, 1.1722, 1.1778, 1.176, 1.1713, 1.1791, 1.1768, 1.1786, 1.1782, 1.1789, 1.1385, 1.1581, 1.1661, 1.1727, 1.1579, 1.1647, 1.161, 1.1619, 1.1454, 1.1578, 1.1268, 1.1193, 1.1044, 1.0876, 1.1531, 0.9884, 1.1236, 0.9809, 1.0122, 1.1246, 0.112, 0.4748, 0.5194, 0.991, 0.9155, 0.6132, 0.7709, 0.6584, 0.6931, 0.8196, 0.7409, 0.6998, 0.0022, 0.2196, -0.2914, 0.191, 0.2002, 0.2067]}, \"token.table\": {\"Topic\": [2, 3, 2, 3, 1, 2, 3, 2, 3, 3, 1, 3, 1, 2, 3, 1, 1, 2, 2, 1, 2, 3, 1, 2, 3, 1, 3, 2, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 3, 2, 1, 2, 3, 1, 2, 3, 2, 3, 1, 2, 3, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 2, 3, 1, 2, 3, 1, 2, 3, 2, 3, 2, 3, 2, 3, 2, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 2, 3, 3, 1, 3, 1, 2, 1, 2, 1, 1, 2, 3, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 3, 2, 1, 2, 3, 2, 1, 2, 3, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 2, 3, 2, 3, 2, 1, 3, 1, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 2, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 2, 3, 3, 1, 3, 3, 3, 2, 3, 1, 3, 1, 2, 3, 1, 2, 2, 3, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 3, 1, 2, 3, 3, 3, 1, 2, 2, 1, 2, 3, 2, 3, 1, 3, 3, 1, 2, 3, 1, 2, 1, 2, 2, 3, 2, 3, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 3, 3, 1, 2, 3, 1, 2, 3, 2, 1, 1, 2, 3, 1, 2, 3, 1, 3, 2, 1, 3, 1, 2, 3, 1, 2, 3, 1, 1, 3, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 1, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 3, 1, 3, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 2, 1, 2, 3, 1, 3, 1, 1, 2, 3, 1, 2, 3], \"Freq\": [0.9979553496885123, 0.0016413739304087373, 0.0032432405685980533, 0.9964856647017519, 0.006310355705727477, 0.9871199282530839, 0.007211835092259974, 0.0016669981343580482, 0.9968648843461129, 0.9982464046021183, 0.002313327492254551, 0.9970441491617115, 0.9967761649552039, 0.001873809026245341, 0.9968664019625213, 0.996021330662857, 0.0012062985228772287, 0.9988151769423453, 0.9985494789909121, 0.9907399682342635, 0.005645241984240817, 0.0028226209921204085, 0.00032753097626790064, 0.07369446966027765, 0.9259300699093551, 0.0006393916061807681, 0.9993690804605406, 0.9981258817975248, 0.013762777287441354, 0.3725441438152229, 0.6136300356090232, 0.9981480936408468, 0.6308009279378305, 0.11313003031070779, 0.25605770253361093, 9.363945879274689e-05, 0.9965111204724124, 0.0033710205165388882, 0.0017753302926288418, 0.997735624457409, 0.133755212962721, 0.021681781096696783, 0.8443679539769944, 0.9987691822636887, 0.020188221502235225, 0.9495674185158496, 0.030282332253352834, 0.004473136149588227, 0.018531564048294084, 0.9764217195101159, 0.0016136728008644965, 0.9972497909342589, 0.14933344236108367, 0.8469793417804927, 0.0036312083248895726, 0.9987129560322563, 0.9862850967183152, 0.012367211244116806, 0.0010306009370097337, 0.5899651823413017, 0.27040070857309656, 0.13954945659226942, 0.993385454619827, 0.006141486581884557, 0.0015353716454711392, 0.9987294594465342, 0.998504058130662, 0.9989998190366964, 0.9970884531640822, 0.0007066775911757833, 0.9255120852432175, 0.07373002867934006, 0.0036907420987699817, 0.9935477729888791, 0.0029525936790159853, 0.27823330877092345, 0.37855821690304986, 0.34321025937335103, 0.9970263991662193, 0.03080414927515422, 0.963634147977107, 0.005357243352200734, 0.9463043591610167, 0.05339446758012535, 0.003263746695526576, 0.37892099135063545, 0.6178272494631808, 0.17007378088542977, 0.6525657027451816, 0.17746829309783976, 0.05310990824774574, 0.946850082979342, 0.6177081567588346, 0.38227699079392324, 0.9985918953961427, 0.0008441182547727326, 0.998530612868054, 0.0006003350000952395, 0.00020011166669841316, 0.999157551825177, 0.0049134919471379365, 0.9941632039709092, 0.0008189153245229893, 0.9993527163113083, 0.8308060132994687, 0.003989464649697329, 0.16518877065153, 0.0011209633857542198, 0.9987783767070099, 0.998084242967405, 0.9983434183982229, 0.9985660982391701, 0.9935495913352449, 0.006293979311625986, 0.9980019832955218, 0.002150866343309314, 0.9984811409467047, 0.19444706739746642, 0.7407012175194041, 0.06446908116921346, 0.9975486021356577, 0.00542608533822902, 0.003255651202937412, 0.9918883998282649, 0.00270488976540138, 0.01442607874880736, 0.9836782446843019, 0.9986424632298391, 0.9800008632176537, 0.008301741882844183, 0.011464310219165776, 0.9986549100956555, 0.0041376101498034655, 0.0013792033832678218, 0.9957848427193673, 0.9979461763895745, 0.0014011585484092072, 0.9976248864673555, 0.0014011585484092072, 0.9983520703953357, 0.0015846858260243422, 0.2552428621307281, 0.7435864505924739, 0.0012166008681159584, 0.9890977715711201, 0.009877807305969908, 0.0006585204870646605, 0.9722851620021993, 0.002666229877519742, 0.02488481219018426, 0.9986549100956555, 0.9634501544153147, 0.00827964976450661, 0.028602426459204654, 0.0032299782059687578, 0.9964482765413618, 0.5718059370228193, 0.05088103676897968, 0.37736768936993265, 0.9972566803775764, 0.0025505285943160524, 0.8155873769315556, 0.08694310919225484, 0.09746780135763307, 0.9983791482769792, 0.7940464029991454, 0.16813331033201603, 0.03789766923405012, 0.975282157622042, 0.002948253197164577, 0.021817073659017867, 0.9963586203339179, 0.0032140600655932833, 0.9964469686795338, 0.0012455587108494172, 0.0024911174216988344, 0.9789138599776388, 0.002409139934317405, 0.01847007282976677, 0.9985587766136927, 0.2087304153407026, 0.5831198904756136, 0.2081168632673907, 0.9054778892317884, 0.038959095943306266, 0.05565585134758037, 0.02307091569695937, 0.0008873429114215142, 0.976964545475087, 0.7496400093575881, 0.2086535100229726, 0.041597234940613945, 0.01440250978706131, 0.801339641763439, 0.18443213921764623, 0.9777376846384195, 0.0220646021921223, 0.00034475940925191093, 0.9895727330445386, 0.007726007024420601, 0.003219169593508584, 0.05938957813254043, 0.24411430492141617, 0.6964777799179741, 0.9992713695858753, 0.025309082740754496, 0.9728178678477509, 0.001581817671297156, 0.008207142068627682, 0.027552548373250073, 0.9649254174972259, 0.9979033936974803, 0.002022777149386784, 0.9986549100956555, 0.9964891469550632, 0.9987428176899443, 0.9970471149856556, 0.9979331766150872, 0.001904452627128029, 0.001904452627128029, 0.0005481165139511582, 0.0005481165139511582, 0.9992164049329614, 0.999111352532854, 0.7131261192128742, 0.07059167565923564, 0.21658126872471875, 0.9969966081491234, 0.0025963453337216756, 0.001786490171367396, 0.9986480057943743, 0.5956783638161511, 0.09680111404729103, 0.307573372147468, 0.9238894110772369, 0.04803094797649244, 0.028253498809701436, 0.04892248421192961, 0.00667124784708131, 0.9443521952423988, 0.9370903809570612, 0.00962620757570898, 0.05357193781264129, 0.9177857856996776, 0.02522709620378695, 0.056941160002833405, 0.8245246369518073, 0.029738865972094887, 0.14577875476517102, 0.3981964327369994, 0.009210568374228604, 0.5926893649183848, 0.7891801507895246, 0.1262475165285976, 0.08443135599064439, 0.9403121382847066, 0.0028322654767611644, 0.05664530953522329, 0.06168887952698714, 0.11391065378003071, 0.8244016350648603, 0.0004727652998206632, 0.9992367377009537, 0.0002836591798923979, 0.014741807612427625, 0.9808566993554523, 0.004211945032122178, 0.0022721638361968533, 0.9702139580560563, 0.027834006993411452, 0.00048656283801322924, 0.17321637033270962, 0.8266702617844766, 0.05620612484327592, 0.9439746608293775, 0.9676404567955733, 0.0015119382137430831, 0.030994733381733208, 0.9992327374138845, 0.9978077276055485, 0.001535088811700844, 0.9987846977172987, 0.9967879585162902, 0.0016851016691787671, 0.9975801881538301, 0.019049641344563478, 0.9806029663558629, 0.5727558095253074, 0.19727037096862549, 0.23003452570212202, 0.002993051599059846, 0.9966861824869286, 0.9981258809143455, 0.9987701275924497, 0.001149584747799029, 0.6670465499103866, 0.3316551997400199, 0.0004436261221940236, 0.9847760535837, 0.014713599719435116, 0.99887144948785, 0.9052651678013154, 0.06570233237572765, 0.02903587237720694, 0.9880247162783218, 0.0011376220106831569, 0.01080740910148999, 0.008763263411456416, 0.00043816317057282083, 0.9906869286651478, 0.9981258808172121, 0.0008282899302364311, 0.02236382811638364, 0.9769679727138705, 0.38547479911191945, 0.12127297050712073, 0.4932983236417467, 0.9992617660186196, 0.9993397540177839, 0.0006575368676552059, 0.9992916546189993, 0.9972640166884509, 0.996959950366805, 0.0020944536772411868, 0.0020944536772411868, 0.004786204861346528, 0.9947329103498533, 0.9978894165356146, 0.002207719948087643, 0.9994145213392142, 0.12993126049093573, 0.7038160262665317, 0.1663849207489137, 0.0024230289101121395, 0.9974802346628309, 0.0008872383289275696, 0.9990303583724434, 0.9966632097343756, 0.0025937884443314914, 0.9523455612489028, 0.0475948276720338, 0.9984138109518012, 0.001815297838094184, 0.0027014523583541966, 0.8244494916152214, 0.17272411016227146, 0.022877215978051115, 0.9734255398660749, 0.0034315823967076674, 0.008438762614055479, 0.7320626567693128, 0.25949195038220596, 0.995265646851788, 0.0197064385246021, 0.972184300547037, 0.007976415593291326, 0.18321605730818147, 0.17281368042804662, 0.6436051243902785, 0.9989407292508118, 0.9992271524880265, 0.03288890646325726, 0.20085725018632114, 0.7666247482744967, 0.1798233917522567, 0.3043821354330502, 0.5157717841455081, 0.9981258821374918, 0.9975923378897388, 0.3665099614348356, 0.631202204003141, 0.002198721503762281, 0.010200039482743081, 0.004371445492604178, 0.9850323843334747, 0.9962989669255391, 0.0031330156192627013, 0.997725709134127, 0.9972081497001606, 0.0024292524962245083, 0.0010127958849848607, 0.02734548889459124, 0.9722840495854662, 0.9950459883747779, 0.0021298073381309456, 0.002981730273383324, 0.9993265735458622, 0.997535636542654, 0.0020610240424435, 0.9989899091652659, 0.0009207280268804294, 0.9971311263569916, 0.0008295600052886786, 0.002488680015866036, 0.007615344241354582, 0.7589959760550066, 0.23330645539422673, 0.6056800540378827, 0.2587488384023025, 0.13553510582977749, 0.017626415663138707, 0.6872152545738346, 0.294920027924711, 0.9981258772232761, 0.9940422902751831, 0.005844442666978048, 0.9987624292233458, 0.9965026835215015, 0.999492712242811, 0.0037185526401717884, 0.08593988323952578, 0.9106322243265135, 0.004844400975322253, 0.9882577989657397, 0.006782161365451155, 0.9583340054977392, 0.005824558380253682, 0.03611226195757283, 0.0005436784859457814, 0.9987373786824003, 0.0005436784859457814, 0.9988458356180715, 0.576966819776228, 0.1186241852611384, 0.304516963383776, 0.6687177618308529, 0.16848686212739272, 0.16280242008530793, 0.006898655623214161, 0.9930368389058812, 6.159513949298358e-05, 0.9648172142666658, 0.03494860890099034, 0.00039268099888753184, 0.9279824906009355, 0.021349290427935635, 0.050526654012780996, 0.9987350707996827, 0.9487680027327178, 0.006588666685643874, 0.04460020525666622, 0.8853823772971878, 0.01544986103552499, 0.0991951305121775, 0.00503380739081579, 0.015101422172447369, 0.9799145054121403, 0.5503882592232829, 0.2202821456157714, 0.22926678207322848, 0.2802796318969325, 0.34819132915327344, 0.3714040844301583, 0.006383796098544154, 0.9934168851811402, 0.0004910612383495503, 0.0017724206527027996, 0.9978728274716762, 0.0017499728497988502, 0.9974845243853446, 0.009657853033506567, 0.000689846645250469, 0.989929935934423, 0.9971945525975259, 0.003116232976867268, 0.004317732886044839, 0.05613052751858291, 0.9396956844719405, 0.0022553004781819663, 0.8525035807527833, 0.14524135079491865, 0.02709934243711673, 0.4064901365567509, 0.5665053014235355, 0.0002620726218569825, 0.33623917384250857, 0.6633058059200228, 0.034082712479214336, 0.007909490237792357, 0.9580070448623046, 0.020795526975518216, 0.16111060898927798, 0.8182492614156536, 0.0004366791200139574, 0.9980301287918997, 0.001528376920048851, 0.026347008763616887, 0.864335365167587, 0.10948077427988377, 0.9878301971642182, 0.006824388236022232, 0.005118291177016674, 0.9980873677576564, 0.9576987519868028, 0.002557535697581848, 0.03954343655491934, 0.06597030307322158, 0.8935489830893265, 0.04022579455684243, 0.00019232880010230355, 0.9997251029317739, 0.00019232880010230355, 0.20835617798961162, 0.500458422677227, 0.2910932559322177, 0.999750235992868, 0.9986918025969416, 0.824420365379212, 0.123093650705386, 0.052461950924332916, 0.9975824082099606, 0.0016851054192735821, 0.9992444524747828, 0.6602955156386924, 0.039928284260346454, 0.29983183828834237, 0.5755267857310601, 0.04965482458413358, 0.3747570816054491], \"Term\": [\"africa\", \"africa\", \"age\", \"age\", \"amid\", \"amid\", \"amid\", \"antibodies\", \"antibodies\", \"antivaccine\", \"antivax\", \"antivax\", \"anymore\", \"approve\", \"approve\", \"asian\", \"athome\", \"athome\", \"barometer\", \"bidens\", \"bidens\", \"bidens\", \"booster\", \"booster\", \"booster\", \"boris\", \"boris\", \"bradfordcounty\", \"break\", \"break\", \"break\", \"brexit\", \"care\", \"care\", \"care\", \"case\", \"case\", \"case\", \"chain\", \"chain\", \"children\", \"children\", \"children\", \"chill\", \"city\", \"city\", \"city\", \"claim\", \"claim\", \"claim\", \"clinic\", \"clinic\", \"close\", \"close\", \"close\", \"cloth\", \"cold\", \"cold\", \"cold\", \"come\", \"come\", \"come\", \"common\", \"common\", \"common\", \"contagious\", \"content\", \"convoy\", \"cool\", \"coronavirus\", \"coronavirus\", \"coronavirus\", \"countries\", \"countries\", \"countries\", \"covid\", \"covid\", \"covid\", \"cure\", \"current\", \"current\", \"current\", \"daily\", \"daily\", \"data\", \"data\", \"data\", \"days\", \"days\", \"days\", \"death\", \"death\", \"deaths\", \"deaths\", \"delta\", \"delta\", \"detect\", \"die\", \"die\", \"die\", \"distance\", \"distance\", \"distance\", \"djokovic\", \"dont\", \"dont\", \"dont\", \"dose\", \"dose\", \"down\", \"dream\", \"drug\", \"exam\", \"exam\", \"exams\", \"exams\", \"excite\", \"face\", \"face\", \"face\", \"facts\", \"fake\", \"fake\", \"fake\", \"fauci\", \"fauci\", \"fauci\", \"february\", \"feel\", \"feel\", \"feel\", \"fhumidity\", \"fire\", \"fire\", \"fire\", \"flatten\", \"florida\", \"florida\", \"florida\", \"france\", \"france\", \"free\", \"free\", \"free\", \"fuck\", \"fuck\", \"fuck\", \"fund\", \"fund\", \"fund\", \"fwind\", \"game\", \"game\", \"game\", \"gate\", \"gate\", \"get\", \"get\", \"get\", \"glad\", \"glad\", \"go\", \"go\", \"go\", \"gonna\", \"good\", \"good\", \"good\", \"great\", \"great\", \"great\", \"guy\", \"guy\", \"happy\", \"happy\", \"happy\", \"hard\", \"hard\", \"hard\", \"hate\", \"health\", \"health\", \"health\", \"hear\", \"hear\", \"hear\", \"heart\", \"heart\", \"heart\", \"help\", \"help\", \"help\", \"high\", \"high\", \"high\", \"home\", \"home\", \"home\", \"hope\", \"hope\", \"hope\", \"hospital\", \"hospital\", \"hospital\", \"hospitalize\", \"hours\", \"hours\", \"hours\", \"immunity\", \"immunity\", \"immunity\", \"infections\", \"infections\", \"inhgwind\", \"invest\", \"investigate\", \"investment\", \"jimin\", \"jimin\", \"jimin\", \"johnson\", \"johnson\", \"johnson\", \"johnsons\", \"kid\", \"kid\", \"kid\", \"kiss\", \"kiss\", \"kit\", \"kit\", \"know\", \"know\", \"know\", \"learn\", \"learn\", \"learn\", \"lie\", \"lie\", \"lie\", \"life\", \"life\", \"life\", \"like\", \"like\", \"like\", \"live\", \"live\", \"live\", \"lockdown\", \"lockdown\", \"lockdown\", \"look\", \"look\", \"look\", \"love\", \"love\", \"love\", \"mandate\", \"mandate\", \"mandate\", \"mask\", \"mask\", \"mask\", \"measure\", \"measure\", \"measure\", \"mild\", \"mild\", \"mild\", \"minister\", \"minister\", \"minister\", \"misinformation\", \"misinformation\", \"miss\", \"miss\", \"miss\", \"moderna\", \"money\", \"money\", \"monoclonal\", \"morrison\", \"mrna\", \"mrna\", \"natural\", \"natural\", \"need\", \"need\", \"need\", \"negative\", \"negative\", \"nepa\", \"novak\", \"number\", \"number\", \"number\", \"omicron\", \"omicron\", \"omicron\", \"ottawa\", \"pandemic\", \"pandemic\", \"pandemic\", \"parent\", \"parent\", \"parent\", \"party\", \"party\", \"party\", \"patemp\", \"patients\", \"patients\", \"patients\", \"people\", \"people\", \"people\", \"pfizer\", \"police\", \"positive\", \"positive\", \"positivity\", \"prepandemic\", \"prepandemic\", \"prepandemic\", \"prime\", \"prime\", \"profit\", \"profit\", \"protest\", \"public\", \"public\", \"public\", \"quarantine\", \"quarantine\", \"rapid\", \"rapid\", \"rate\", \"rate\", \"record\", \"record\", \"relief\", \"relief\", \"report\", \"report\", \"report\", \"require\", \"require\", \"require\", \"restrictions\", \"restrictions\", \"restrictions\", \"retweet\", \"rise\", \"rise\", \"rise\", \"risk\", \"risk\", \"risk\", \"robert\", \"rogan\", \"rule\", \"rule\", \"rule\", \"say\", \"say\", \"say\", \"sayre\", \"scar\", \"school\", \"school\", \"school\", \"second\", \"second\", \"second\", \"shes\", \"shes\", \"ship\", \"shit\", \"shit\", \"shots\", \"shots\", \"shots\", \"sick\", \"sick\", \"sick\", \"sleep\", \"sound\", \"sound\", \"south\", \"south\", \"spend\", \"spend\", \"spend\", \"spread\", \"spread\", \"spread\", \"start\", \"start\", \"start\", \"state\", \"state\", \"state\", \"statscases\", \"stay\", \"stay\", \"stayathome\", \"stream\", \"street\", \"study\", \"study\", \"study\", \"supply\", \"supply\", \"supply\", \"support\", \"support\", \"support\", \"surge\", \"surge\", \"surge\", \"survival\", \"take\", \"take\", \"take\", \"tell\", \"tell\", \"tell\", \"test\", \"test\", \"test\", \"thank\", \"thank\", \"thank\", \"thats\", \"thats\", \"thats\", \"theory\", \"thing\", \"thing\", \"thing\", \"think\", \"think\", \"think\", \"thousands\", \"thousands\", \"thousands\", \"time\", \"time\", \"time\", \"today\", \"today\", \"today\", \"travel\", \"travel\", \"travel\", \"treatment\", \"treatment\", \"treatments\", \"treatments\", \"truckers\", \"truckers\", \"truckers\", \"truth\", \"truth\", \"unvaccinated\", \"unvaccinated\", \"unvaccinated\", \"update\", \"update\", \"update\", \"vaccinate\", \"vaccinate\", \"vaccinate\", \"vaccination\", \"vaccination\", \"vaccination\", \"vaccine\", \"vaccine\", \"vaccine\", \"vaccines\", \"vaccines\", \"vaccines\", \"variant\", \"variant\", \"variant\", \"virus\", \"virus\", \"virus\", \"vote\", \"vote\", \"vote\", \"walkin\", \"want\", \"want\", \"want\", \"wave\", \"wave\", \"wave\", \"wear\", \"wear\", \"wear\", \"week\", \"week\", \"week\", \"weekly\", \"weewx\", \"work\", \"work\", \"work\", \"worth\", \"worth\", \"yall\", \"year\", \"year\", \"year\", \"years\", \"years\", \"years\"]}, \"R\": 30, \"lambda.step\": 0.01, \"plot.opts\": {\"xlab\": \"PC1\", \"ylab\": \"PC2\"}, \"topic.order\": [1, 2, 3]};\n",
              "\n",
              "function LDAvis_load_lib(url, callback){\n",
              "  var s = document.createElement('script');\n",
              "  s.src = url;\n",
              "  s.async = true;\n",
              "  s.onreadystatechange = s.onload = callback;\n",
              "  s.onerror = function(){console.warn(\"failed to load library \" + url);};\n",
              "  document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
              "}\n",
              "\n",
              "if(typeof(LDAvis) !== \"undefined\"){\n",
              "   // already loaded: just create the visualization\n",
              "   !function(LDAvis){\n",
              "       new LDAvis(\"#\" + \"ldavis_el761406533149701128729283870\", ldavis_el761406533149701128729283870_data);\n",
              "   }(LDAvis);\n",
              "}else if(typeof define === \"function\" && define.amd){\n",
              "   // require.js is available: use it to load d3/LDAvis\n",
              "   require.config({paths: {d3: \"https://d3js.org/d3.v5\"}});\n",
              "   require([\"d3\"], function(d3){\n",
              "      window.d3 = d3;\n",
              "      LDAvis_load_lib(\"https://cdn.jsdelivr.net/gh/bmabey/pyLDAvis@3.3.1/pyLDAvis/js/ldavis.v3.0.0.js\", function(){\n",
              "        new LDAvis(\"#\" + \"ldavis_el761406533149701128729283870\", ldavis_el761406533149701128729283870_data);\n",
              "      });\n",
              "    });\n",
              "}else{\n",
              "    // require.js not available: dynamically load d3 & LDAvis\n",
              "    LDAvis_load_lib(\"https://d3js.org/d3.v5.js\", function(){\n",
              "         LDAvis_load_lib(\"https://cdn.jsdelivr.net/gh/bmabey/pyLDAvis@3.3.1/pyLDAvis/js/ldavis.v3.0.0.js\", function(){\n",
              "                 new LDAvis(\"#\" + \"ldavis_el761406533149701128729283870\", ldavis_el761406533149701128729283870_data);\n",
              "            })\n",
              "         });\n",
              "}\n",
              "</script>"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "coherence_model_lda_first_wave = CoherenceModel(model=lda_model_first_wave,texts=processed_tweets_first_wave,dictionary=lexicon_first_wave, coherence='u_mass')\n",
        "coherence_lda_first_wave = coherence_model_lda_first_wave.get_coherence()\n",
        "print('UMass Coherence Score for First Wave ', coherence_lda_first_wave)\n",
        "\n",
        "coherence_model_lda_first_wave = CoherenceModel(model=lda_model_first_wave,texts=processed_tweets_first_wave,dictionary=lexicon_first_wave, coherence='c_v')\n",
        "coherence_lda_first_wave = coherence_model_lda_first_wave.get_coherence()\n",
        "print('CV Coherence Score for First Wave ', coherence_lda_first_wave)\n",
        "\n",
        "coherence_model_lda_first_wave = CoherenceModel(model=lda_model_first_wave,texts=processed_tweets_first_wave,dictionary=lexicon_first_wave, coherence='c_uci')\n",
        "coherence_lda_first_wave = coherence_model_lda_first_wave.get_coherence()\n",
        "print('UCI Coherence Score for First Wave ', coherence_lda_first_wave)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7FRG1PC-ElAR",
        "outputId": "fc7c6102-4f63-4222-fab1-0749351666d0"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "UMass Coherence Score for First Wave  -3.6102245249450853\n",
            "CV Coherence Score for First Wave  0.27068894280097017\n",
            "UCI Coherence Score for First Wave  -0.07458269286331265\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "coherence_model_lda_second_wave = CoherenceModel(model=lda_model_second_wave,texts=processed_tweets_second_wave,dictionary=lexicon_second_wave, coherence='u_mass')\n",
        "coherence_lda_second_wave = coherence_model_lda_second_wave.get_coherence()\n",
        "print('UMass Coherence Score for Second Wave ', coherence_lda_second_wave)\n",
        "\n",
        "coherence_model_lda_second_wave = CoherenceModel(model=lda_model_second_wave,texts=processed_tweets_second_wave,dictionary=lexicon_second_wave, coherence='c_v')\n",
        "coherence_lda_second_wave = coherence_model_lda_second_wave.get_coherence()\n",
        "print('CV Coherence Score for Second Wave ', coherence_lda_second_wave)\n",
        "\n",
        "coherence_model_lda_second_wave = CoherenceModel(model=lda_model_second_wave,texts=processed_tweets_second_wave,dictionary=lexicon_second_wave, coherence='c_uci')\n",
        "coherence_lda_second_wave = coherence_model_lda_second_wave.get_coherence()\n",
        "print('UCI Coherence Score for Second Wave ', coherence_lda_second_wave)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "deHmOHcoFJCY",
        "outputId": "73120984-54ed-4c05-d45a-7a01ab0d6cf2"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "UMass Coherence Score for Second Wave  -3.703634839267553\n",
            "CV Coherence Score for Second Wave  0.2687365221581337\n",
            "UCI Coherence Score for Second Wave  -0.06418014696882211\n"
          ]
        }
      ]
    }
  ]
}