Tik-Tok_Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4a68d1c8",
   "metadata": {},
   "source": [
    "# **TikTok Project**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45bece6c",
   "metadata": {},
   "source": [
    "### Issue:\n",
    "The TikTok data team seeks to develop a machine learning model to assist in the classification of claims for user submissions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "def7ff90",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import libraries\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "d00f4150",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>claim_status</th>\n",
       "      <th>video_id</th>\n",
       "      <th>video_duration_sec</th>\n",
       "      <th>video_transcription_text</th>\n",
       "      <th>verified_status</th>\n",
       "      <th>author_ban_status</th>\n",
       "      <th>video_view_count</th>\n",
       "      <th>video_like_count</th>\n",
       "      <th>video_share_count</th>\n",
       "      <th>video_download_count</th>\n",
       "      <th>video_comment_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>claim</td>\n",
       "      <td>7017666017</td>\n",
       "      <td>59</td>\n",
       "      <td>someone shared with me that drone deliveries a...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>under review</td>\n",
       "      <td>343296.0</td>\n",
       "      <td>19425.0</td>\n",
       "      <td>241.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>claim</td>\n",
       "      <td>4014381136</td>\n",
       "      <td>32</td>\n",
       "      <td>someone shared with me that there are more mic...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>140877.0</td>\n",
       "      <td>77355.0</td>\n",
       "      <td>19034.0</td>\n",
       "      <td>1161.0</td>\n",
       "      <td>684.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>claim</td>\n",
       "      <td>9859838091</td>\n",
       "      <td>31</td>\n",
       "      <td>someone shared with me that american industria...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>902185.0</td>\n",
       "      <td>97690.0</td>\n",
       "      <td>2858.0</td>\n",
       "      <td>833.0</td>\n",
       "      <td>329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>claim</td>\n",
       "      <td>1866847991</td>\n",
       "      <td>25</td>\n",
       "      <td>someone shared with me that the metro of st. p...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>437506.0</td>\n",
       "      <td>239954.0</td>\n",
       "      <td>34812.0</td>\n",
       "      <td>1234.0</td>\n",
       "      <td>584.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>claim</td>\n",
       "      <td>7105231098</td>\n",
       "      <td>19</td>\n",
       "      <td>someone shared with me that the number of busi...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>56167.0</td>\n",
       "      <td>34987.0</td>\n",
       "      <td>4110.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>152.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   # claim_status    video_id  video_duration_sec  \\\n",
       "0  1        claim  7017666017                  59   \n",
       "1  2        claim  4014381136                  32   \n",
       "2  3        claim  9859838091                  31   \n",
       "3  4        claim  1866847991                  25   \n",
       "4  5        claim  7105231098                  19   \n",
       "\n",
       "                            video_transcription_text verified_status  \\\n",
       "0  someone shared with me that drone deliveries a...    not verified   \n",
       "1  someone shared with me that there are more mic...    not verified   \n",
       "2  someone shared with me that american industria...    not verified   \n",
       "3  someone shared with me that the metro of st. p...    not verified   \n",
       "4  someone shared with me that the number of busi...    not verified   \n",
       "\n",
       "  author_ban_status  video_view_count  video_like_count  video_share_count  \\\n",
       "0      under review          343296.0           19425.0              241.0   \n",
       "1            active          140877.0           77355.0            19034.0   \n",
       "2            active          902185.0           97690.0             2858.0   \n",
       "3            active          437506.0          239954.0            34812.0   \n",
       "4            active           56167.0           34987.0             4110.0   \n",
       "\n",
       "   video_download_count  video_comment_count  \n",
       "0                   1.0                  0.0  \n",
       "1                1161.0                684.0  \n",
       "2                 833.0                329.0  \n",
       "3                1234.0                584.0  \n",
       "4                 547.0                152.0  "
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load and display dataset\n",
    "\n",
    "ttdata = pd.read_csv(\"tiktok_dataset.csv\")\n",
    "ttdata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "72fbe997",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 19382 entries, 0 to 19381\n",
      "Data columns (total 12 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   #                         19382 non-null  int64  \n",
      " 1   claim_status              19084 non-null  object \n",
      " 2   video_id                  19382 non-null  int64  \n",
      " 3   video_duration_sec        19382 non-null  int64  \n",
      " 4   video_transcription_text  19084 non-null  object \n",
      " 5   verified_status           19382 non-null  object \n",
      " 6   author_ban_status         19382 non-null  object \n",
      " 7   video_view_count          19084 non-null  float64\n",
      " 8   video_like_count          19084 non-null  float64\n",
      " 9   video_share_count         19084 non-null  float64\n",
      " 10  video_download_count      19084 non-null  float64\n",
      " 11  video_comment_count       19084 non-null  float64\n",
      "dtypes: float64(5), int64(3), object(4)\n",
      "memory usage: 1.8+ MB\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>video_id</th>\n",
       "      <th>video_duration_sec</th>\n",
       "      <th>video_view_count</th>\n",
       "      <th>video_like_count</th>\n",
       "      <th>video_share_count</th>\n",
       "      <th>video_download_count</th>\n",
       "      <th>video_comment_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>19382.000000</td>\n",
       "      <td>1.938200e+04</td>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9691.500000</td>\n",
       "      <td>5.627454e+09</td>\n",
       "      <td>32.421732</td>\n",
       "      <td>254708.558688</td>\n",
       "      <td>84304.636030</td>\n",
       "      <td>16735.248323</td>\n",
       "      <td>1049.429627</td>\n",
       "      <td>349.312146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5595.245794</td>\n",
       "      <td>2.536440e+09</td>\n",
       "      <td>16.229967</td>\n",
       "      <td>322893.280814</td>\n",
       "      <td>133420.546814</td>\n",
       "      <td>32036.174350</td>\n",
       "      <td>2004.299894</td>\n",
       "      <td>799.638865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.234959e+09</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4846.250000</td>\n",
       "      <td>3.430417e+09</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>4942.500000</td>\n",
       "      <td>810.750000</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>9691.500000</td>\n",
       "      <td>5.618664e+09</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>9954.500000</td>\n",
       "      <td>3403.500000</td>\n",
       "      <td>717.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>14536.750000</td>\n",
       "      <td>7.843960e+09</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>504327.000000</td>\n",
       "      <td>125020.000000</td>\n",
       "      <td>18222.000000</td>\n",
       "      <td>1156.250000</td>\n",
       "      <td>292.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>19382.000000</td>\n",
       "      <td>9.999873e+09</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>999817.000000</td>\n",
       "      <td>657830.000000</td>\n",
       "      <td>256130.000000</td>\n",
       "      <td>14994.000000</td>\n",
       "      <td>9599.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  #      video_id  video_duration_sec  video_view_count  \\\n",
       "count  19382.000000  1.938200e+04        19382.000000      19084.000000   \n",
       "mean    9691.500000  5.627454e+09           32.421732     254708.558688   \n",
       "std     5595.245794  2.536440e+09           16.229967     322893.280814   \n",
       "min        1.000000  1.234959e+09            5.000000         20.000000   \n",
       "25%     4846.250000  3.430417e+09           18.000000       4942.500000   \n",
       "50%     9691.500000  5.618664e+09           32.000000       9954.500000   \n",
       "75%    14536.750000  7.843960e+09           47.000000     504327.000000   \n",
       "max    19382.000000  9.999873e+09           60.000000     999817.000000   \n",
       "\n",
       "       video_like_count  video_share_count  video_download_count  \\\n",
       "count      19084.000000       19084.000000          19084.000000   \n",
       "mean       84304.636030       16735.248323           1049.429627   \n",
       "std       133420.546814       32036.174350           2004.299894   \n",
       "min            0.000000           0.000000              0.000000   \n",
       "25%          810.750000         115.000000              7.000000   \n",
       "50%         3403.500000         717.000000             46.000000   \n",
       "75%       125020.000000       18222.000000           1156.250000   \n",
       "max       657830.000000      256130.000000          14994.000000   \n",
       "\n",
       "       video_comment_count  \n",
       "count         19084.000000  \n",
       "mean            349.312146  \n",
       "std             799.638865  \n",
       "min               0.000000  \n",
       "25%               1.000000  \n",
       "50%               9.000000  \n",
       "75%             292.000000  \n",
       "max            9599.000000  "
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Summary information and statistic\n",
    "\n",
    "ttdata.info(),\n",
    "ttdata.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b69bcccb",
   "metadata": {},
   "source": [
    "#### Obeservation: The insights from the summary statistics\n",
    "\n",
    "1. Video Duration: Videos vary significantly in length, with an average duration around 32 seconds.\n",
    "\n",
    "2. Views: There is a wide range of viewership, with videos averaging about 254,709 views.\n",
    "\n",
    "3. Likes: On average, videos receive around 84,305 likes, indicating a high level of engagement.\n",
    "\n",
    "4. Shares: Videos are shared an average of 16,735 times, suggesting they are widely circulated.\n",
    "\n",
    "5. Downloads: The average video is downloaded approximately 1,049 times.\n",
    "\n",
    "6. Comments: There is an average of 349 comments per video, showing active audience interaction."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2dae286a",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "84f1e3e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Handle Missing Values\n",
    "\n",
    "# We will fill missing 'claim_status' and 'video_transcription_text' with 'unknown'\n",
    "ttdata['claim_status'].fillna('unknown', inplace=True)\n",
    "ttdata['video_transcription_text'].fillna('unknown', inplace=True)\n",
    "\n",
    "# For numerical columns with missing values (engagement metrics), we'll use median to fill missing values\n",
    "numeric_cols = ['video_view_count', 'video_like_count', 'video_share_count', 'video_download_count', 'video_comment_count']\n",
    "ttdata[numeric_cols] = ttdata[numeric_cols].fillna(ttdata[numeric_cols].median())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "d0ff1c94",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>claim_status</th>\n",
       "      <th>video_id</th>\n",
       "      <th>video_duration_sec</th>\n",
       "      <th>video_transcription_text</th>\n",
       "      <th>verified_status</th>\n",
       "      <th>author_ban_status</th>\n",
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       "      <th>video_comment_count</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>claim</td>\n",
       "      <td>7017666017</td>\n",
       "      <td>59</td>\n",
       "      <td>someone shared with me that drone deliveries a...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>under review</td>\n",
       "      <td>343296.0</td>\n",
       "      <td>19425.0</td>\n",
       "      <td>241.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>claim</td>\n",
       "      <td>4014381136</td>\n",
       "      <td>32</td>\n",
       "      <td>someone shared with me that there are more mic...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>140877.0</td>\n",
       "      <td>77355.0</td>\n",
       "      <td>19034.0</td>\n",
       "      <td>1161.0</td>\n",
       "      <td>684.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>claim</td>\n",
       "      <td>9859838091</td>\n",
       "      <td>31</td>\n",
       "      <td>someone shared with me that american industria...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>902185.0</td>\n",
       "      <td>97690.0</td>\n",
       "      <td>2858.0</td>\n",
       "      <td>833.0</td>\n",
       "      <td>329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>claim</td>\n",
       "      <td>1866847991</td>\n",
       "      <td>25</td>\n",
       "      <td>someone shared with me that the metro of st. p...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>437506.0</td>\n",
       "      <td>239954.0</td>\n",
       "      <td>34812.0</td>\n",
       "      <td>1234.0</td>\n",
       "      <td>584.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>claim</td>\n",
       "      <td>7105231098</td>\n",
       "      <td>19</td>\n",
       "      <td>someone shared with me that the number of busi...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>56167.0</td>\n",
       "      <td>34987.0</td>\n",
       "      <td>4110.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>152.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19377</th>\n",
       "      <td>19378</td>\n",
       "      <td>unknown</td>\n",
       "      <td>7578226840</td>\n",
       "      <td>21</td>\n",
       "      <td>unknown</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>9954.5</td>\n",
       "      <td>3403.5</td>\n",
       "      <td>717.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19378</th>\n",
       "      <td>19379</td>\n",
       "      <td>unknown</td>\n",
       "      <td>6079236179</td>\n",
       "      <td>53</td>\n",
       "      <td>unknown</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>9954.5</td>\n",
       "      <td>3403.5</td>\n",
       "      <td>717.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19379</th>\n",
       "      <td>19380</td>\n",
       "      <td>unknown</td>\n",
       "      <td>2565539685</td>\n",
       "      <td>10</td>\n",
       "      <td>unknown</td>\n",
       "      <td>verified</td>\n",
       "      <td>under review</td>\n",
       "      <td>9954.5</td>\n",
       "      <td>3403.5</td>\n",
       "      <td>717.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19380</th>\n",
       "      <td>19381</td>\n",
       "      <td>unknown</td>\n",
       "      <td>2969178540</td>\n",
       "      <td>24</td>\n",
       "      <td>unknown</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>9954.5</td>\n",
       "      <td>3403.5</td>\n",
       "      <td>717.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19381</th>\n",
       "      <td>19382</td>\n",
       "      <td>unknown</td>\n",
       "      <td>8132759688</td>\n",
       "      <td>13</td>\n",
       "      <td>unknown</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>9954.5</td>\n",
       "      <td>3403.5</td>\n",
       "      <td>717.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>19382 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           # claim_status    video_id  video_duration_sec  \\\n",
       "0          1        claim  7017666017                  59   \n",
       "1          2        claim  4014381136                  32   \n",
       "2          3        claim  9859838091                  31   \n",
       "3          4        claim  1866847991                  25   \n",
       "4          5        claim  7105231098                  19   \n",
       "...      ...          ...         ...                 ...   \n",
       "19377  19378      unknown  7578226840                  21   \n",
       "19378  19379      unknown  6079236179                  53   \n",
       "19379  19380      unknown  2565539685                  10   \n",
       "19380  19381      unknown  2969178540                  24   \n",
       "19381  19382      unknown  8132759688                  13   \n",
       "\n",
       "                                video_transcription_text verified_status  \\\n",
       "0      someone shared with me that drone deliveries a...    not verified   \n",
       "1      someone shared with me that there are more mic...    not verified   \n",
       "2      someone shared with me that american industria...    not verified   \n",
       "3      someone shared with me that the metro of st. p...    not verified   \n",
       "4      someone shared with me that the number of busi...    not verified   \n",
       "...                                                  ...             ...   \n",
       "19377                                            unknown    not verified   \n",
       "19378                                            unknown    not verified   \n",
       "19379                                            unknown        verified   \n",
       "19380                                            unknown    not verified   \n",
       "19381                                            unknown    not verified   \n",
       "\n",
       "      author_ban_status  video_view_count  video_like_count  \\\n",
       "0          under review          343296.0           19425.0   \n",
       "1                active          140877.0           77355.0   \n",
       "2                active          902185.0           97690.0   \n",
       "3                active          437506.0          239954.0   \n",
       "4                active           56167.0           34987.0   \n",
       "...                 ...               ...               ...   \n",
       "19377            active            9954.5            3403.5   \n",
       "19378            active            9954.5            3403.5   \n",
       "19379      under review            9954.5            3403.5   \n",
       "19380            active            9954.5            3403.5   \n",
       "19381            active            9954.5            3403.5   \n",
       "\n",
       "       video_share_count  video_download_count  video_comment_count  \n",
       "0                  241.0                   1.0                  0.0  \n",
       "1                19034.0                1161.0                684.0  \n",
       "2                 2858.0                 833.0                329.0  \n",
       "3                34812.0                1234.0                584.0  \n",
       "4                 4110.0                 547.0                152.0  \n",
       "...                  ...                   ...                  ...  \n",
       "19377              717.0                  46.0                  9.0  \n",
       "19378              717.0                  46.0                  9.0  \n",
       "19379              717.0                  46.0                  9.0  \n",
       "19380              717.0                  46.0                  9.0  \n",
       "19381              717.0                  46.0                  9.0  \n",
       "\n",
       "[19382 rows x 12 columns]"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Type Corrections\n",
    "\n",
    "# From the initial inspection, it seems the data types are appropriate for analysis. \n",
    "categorical_cols = ['claim_status', 'verified_status', 'author_ban_status']\n",
    "ttdata[categorical_cols] = ttdata[categorical_cols].astype('category')\n",
    "\n",
    "ttdata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "dadf0b33",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 19382 entries, 0 to 19381\n",
      "Data columns (total 12 columns):\n",
      " #   Column                    Non-Null Count  Dtype   \n",
      "---  ------                    --------------  -----   \n",
      " 0   #                         19382 non-null  int64   \n",
      " 1   claim_status              19382 non-null  category\n",
      " 2   video_id                  19382 non-null  int64   \n",
      " 3   video_duration_sec        19382 non-null  int64   \n",
      " 4   video_transcription_text  19382 non-null  object  \n",
      " 5   verified_status           19382 non-null  category\n",
      " 6   author_ban_status         19382 non-null  category\n",
      " 7   video_view_count          19382 non-null  float64 \n",
      " 8   video_like_count          19382 non-null  float64 \n",
      " 9   video_share_count         19382 non-null  float64 \n",
      " 10  video_download_count      19382 non-null  float64 \n",
      " 11  video_comment_count       19382 non-null  float64 \n",
      "dtypes: category(3), float64(5), int64(3), object(1)\n",
      "memory usage: 1.4+ MB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>video_id</th>\n",
       "      <th>video_duration_sec</th>\n",
       "      <th>video_view_count</th>\n",
       "      <th>video_like_count</th>\n",
       "      <th>video_share_count</th>\n",
       "      <th>video_download_count</th>\n",
       "      <th>video_comment_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>19382.000000</td>\n",
       "      <td>1.938200e+04</td>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19382.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9691.500000</td>\n",
       "      <td>5.627454e+09</td>\n",
       "      <td>32.421732</td>\n",
       "      <td>250945.442937</td>\n",
       "      <td>83060.773759</td>\n",
       "      <td>16488.966309</td>\n",
       "      <td>1034.001806</td>\n",
       "      <td>344.079816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5595.245794</td>\n",
       "      <td>2.536440e+09</td>\n",
       "      <td>16.229967</td>\n",
       "      <td>321813.461011</td>\n",
       "      <td>132764.541002</td>\n",
       "      <td>31849.968548</td>\n",
       "      <td>1992.659853</td>\n",
       "      <td>794.571564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.234959e+09</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4846.250000</td>\n",
       "      <td>3.430417e+09</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>5026.250000</td>\n",
       "      <td>833.000000</td>\n",
       "      <td>119.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>9691.500000</td>\n",
       "      <td>5.618664e+09</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>9954.500000</td>\n",
       "      <td>3403.500000</td>\n",
       "      <td>717.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>14536.750000</td>\n",
       "      <td>7.843960e+09</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>496858.000000</td>\n",
       "      <td>122187.500000</td>\n",
       "      <td>17713.750000</td>\n",
       "      <td>1121.750000</td>\n",
       "      <td>281.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>19382.000000</td>\n",
       "      <td>9.999873e+09</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>999817.000000</td>\n",
       "      <td>657830.000000</td>\n",
       "      <td>256130.000000</td>\n",
       "      <td>14994.000000</td>\n",
       "      <td>9599.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  #      video_id  video_duration_sec  video_view_count  \\\n",
       "count  19382.000000  1.938200e+04        19382.000000      19382.000000   \n",
       "mean    9691.500000  5.627454e+09           32.421732     250945.442937   \n",
       "std     5595.245794  2.536440e+09           16.229967     321813.461011   \n",
       "min        1.000000  1.234959e+09            5.000000         20.000000   \n",
       "25%     4846.250000  3.430417e+09           18.000000       5026.250000   \n",
       "50%     9691.500000  5.618664e+09           32.000000       9954.500000   \n",
       "75%    14536.750000  7.843960e+09           47.000000     496858.000000   \n",
       "max    19382.000000  9.999873e+09           60.000000     999817.000000   \n",
       "\n",
       "       video_like_count  video_share_count  video_download_count  \\\n",
       "count      19382.000000       19382.000000          19382.000000   \n",
       "mean       83060.773759       16488.966309           1034.001806   \n",
       "std       132764.541002       31849.968548           1992.659853   \n",
       "min            0.000000           0.000000              0.000000   \n",
       "25%          833.000000         119.000000              7.000000   \n",
       "50%         3403.500000         717.000000             46.000000   \n",
       "75%       122187.500000       17713.750000           1121.750000   \n",
       "max       657830.000000      256130.000000          14994.000000   \n",
       "\n",
       "       video_comment_count  \n",
       "count         19382.000000  \n",
       "mean            344.079816  \n",
       "std             794.571564  \n",
       "min               0.000000  \n",
       "25%               1.000000  \n",
       "50%               9.000000  \n",
       "75%             281.000000  \n",
       "max            9599.000000  "
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Recheck the dataset information to confirm changes\n",
    "ttdata.info(), \n",
    "ttdata.describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "5eb654b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean view count for claims: 501029\n",
      "Median view count for claims 501555\n"
     ]
    }
   ],
   "source": [
    "# The average view count of videos with \"claim\" status\n",
    "\n",
    "claims = ttdata[ttdata['claim_status'] == 'claim']\n",
    "mean_view_count = round(claims['video_view_count'].mean())\n",
    "median_view_count = round(claims['video_view_count'].median())\n",
    "\n",
    "\n",
    "print('Mean view count for claims:', mean_view_count)\n",
    "print('Median view count for claims', median_view_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9698434d",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "These values are very close to each other suggests a relatively symmetric distribution of view counts for these videos, indicating that there are no extreme outliers skewing the average view count significantly away from the median. \n",
    "\n",
    "This implies that the majority of \"claim\" videos have a view count around the 500,000 mark, showing a consistent level of engagement across these videos."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d0b32ce",
   "metadata": {},
   "source": [
    "## Data Exploratory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "1dfd79b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "claim_status\n",
       "claim      9608\n",
       "opinion    9476\n",
       "unknown     298\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Investigation the different values for claim status and \n",
    "# how many of each are in the data?\n",
    "\n",
    "ttdata['claim_status'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "4442a33c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Filtering out the 'unknown' claim statuses from the DataFrame\n",
    "filtered_ttdata = ttdata[ttdata['claim_status'] != 'unknown']\n",
    "\n",
    "# The count of the claim statuses (excluding unknown).\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.figure(figsize=(10, 5))\n",
    "ax = sns.countplot(x='claim_status', data=filtered_ttdata, order=['claim', 'opinion'])\n",
    "plt.title('Distribution of Claim Status (Excluding Unknown)')\n",
    "plt.xlabel('Claim Status')\n",
    "plt.ylabel('Count')\n",
    "\n",
    "# Adding the count numbers above the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f'{int(p.get_height())}', (p.get_x() + p.get_width() / 2., p.get_height()),\n",
    "                ha='center', va='center', xytext=(0, 5), textcoords='offset points')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32e1cb26",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "The dataset has a nearly equal number of 'claim' and 'opinion' videos, indicating a balanced classification distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "dd3ed1d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "claim_status  author_ban_status\n",
       "claim         active               6566\n",
       "              banned               1439\n",
       "              under review         1603\n",
       "opinion       active               8817\n",
       "              banned                196\n",
       "              under review          463\n",
       "unknown       active                280\n",
       "              banned                  4\n",
       "              under review           14\n",
       "dtype: int64"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# counts for each group combination of claim status \n",
    "# and author ban status\n",
    "\n",
    "ttdata.groupby(['claim_status','author_ban_status']).size()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f285518c",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "The data above suggests that there are significantly more banned authors among those who posted claim videos compared to those who posted opinion videos. \n",
    "\n",
    "This could indicate stricter regulation or different standards for claim videos versus opinion videos. However, it's unclear if claim videos are inherently more likely to lead to bans or if authors of claim videos tend to violate terms of service more often. \n",
    "\n",
    "Importantly, while this data can inform about the status of authors (banned or active), it does not include the depth details and reasons for bans or the compliance of individual videos with terms of service."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "0c22f2c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The impact of Author Ban Status on Engagement using the median engagement metrics by author ban status\n",
    "\n",
    "for metric in engagement_metrics:\n",
    "    plt.figure(figsize=(10, 5))\n",
    "    ax = sns.barplot(x='author_ban_status', y=metric, data=ttdata, estimator=np.median)\n",
    "    plt.title(f'Median {metric.replace(\"_\", \" \").title()} by Author Ban Status')\n",
    "    plt.xlabel('Author Ban Status')\n",
    "    plt.ylabel(f'Median {metric.replace(\"_\", \" \").title()}')\n",
    "\n",
    "    # Adding the count numbers above the bars\n",
    "    for p in ax.patches:\n",
    "        ax.annotate(f'{p.get_height():.2f}', (p.get_x() + p.get_width() / 2., p.get_height()),\n",
    "                    ha='center', va='center', xytext=(0, 23), textcoords='offset points')\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65c690a4",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "The data above suggests that there are significantly more banned authors among those who posted claim videos compared to those who posted opinion videos. \n",
    "\n",
    "This could indicate stricter regulation or different standards for claim videos versus opinion videos. However, it's unclear if claim videos are inherently more likely to lead to bans or if authors of claim videos tend to violate terms of service more often. \n",
    "\n",
    "Importantly, while this data can inform about the status of authors (banned or active), it does not include the depth details and reasons for bans or the compliance of individual videos with terms of service."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "6e98c134",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation between Video Duration and Engagement Metrics\n",
    "plt.figure(figsize=(10, 5))\n",
    "sns.heatmap(ttdata[['video_duration_sec'] + engagement_metrics].corr(), annot=True, fmt=\".2f\", cmap='coolwarm')\n",
    "plt.title('Correlation between Video Duration and Engagement Metrics')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f403f30a",
   "metadata": {},
   "source": [
    "#### Observation:\n",
    "#### - Video Duration: \n",
    "There is virtually no correlation between video duration and any of the engagement metrics, as indicated by the correlation coefficients close to 0. This suggests that the length of a video does not significantly influence how much engagement (views, likes, shares, downloads, comments) it will receive.\n",
    "\n",
    "\n",
    "#### - Engagement Metrics: \n",
    "There are strong positive correlations between the various engagement metrics themselves (like count with view count, share count with like count, etc.). This indicates that when a video receives a high number of views, it is also likely to receive a high number of likes, shares, downloads, and comments, and vice versa.\n",
    "\n",
    "#### - Implication: \n",
    "The engagement metrics are interrelated, videos that perform well on one metric tend to perform well on others. However, these metrics do not appear to be influenced by the duration of the video within this dataset.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea61a297",
   "metadata": {},
   "source": [
    "## My Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6efb888e",
   "metadata": {},
   "source": [
    "#### 1. Claim Status\n",
    "The graph shows a close count between videos labeled as 'claim' and those labeled as 'opinion', indicating a nearly balanced dataset with respect to these two categories. This also suggests that for the videos classified, there is no significant skew towards one type of content over the other. This balance is beneficial for machine learning classification tasks as it provides a more equal representation of classes.\n",
    "\n",
    "#### 2. The impact of Author Ban Status \n",
    "#### - Video View Count: \n",
    "Banned authors tend to have higher median view counts compared to active authors. This suggests that videos from banned authors may receive more attention, which could be due to various factors including the nature of the content or a heightened audience curiosity following a ban.\n",
    "\n",
    "#### - Video Like Count: \n",
    "Similar to view counts, banned authors have a higher median like count. This indicates that despite the ban, or perhaps because of it, their content is well-received by viewers who interact with it through likes.\n",
    "\n",
    "#### - Video Share Count:\n",
    "The trend continues with share counts, where banned authors have a notably higher median share count. This could imply that their videos are shared more widely, possibly due to being controversial or highly engaging.\n",
    "\n",
    "#### - Video Download Count: \n",
    "Banned authors also see higher median download counts. This could suggest that viewers are keen to save content from these authors, potentially due to the perceived risk of the content being taken down or as a means to view it offline.\n",
    "\n",
    "#### - Video Comment Count: \n",
    "Once again, banned authors lead with higher median comment counts, indicating a higher level of viewer engagement in terms of discussions or reactions to the content.\n",
    "\n",
    "Across all these engagement metrics, the consistent pattern is that banned authors receive higher median engagement on their videos. This could be due to a variety of reasons, such as the content being more provocative or contentious, thus drawing more views, or perhaps the audience's reaction to the author's ban status. It's also possible that the content from these authors goes viral, leading to increased engagement.\n",
    "\n",
    "It's important to note that while these charts provide quantitative insights, they do not reveal the qualitative aspects behind why these differences exist. Further investigation, possibly including content analysis and understanding the context of the bans, would be necessary to draw more nuanced conclusions.\n",
    "\n",
    "\n",
    "#### 3. The Correlation \n",
    "The longer videos tend to get more views, likes, shares, downloads, and comments: A positive correlation would suggest that as videos get longer, they tend to engage users more, potentially because they provide more content or are more in-depth.\n",
    "\n",
    "A diminishing return on engagement with increasing video length: If the correlation starts strong and gets weaker as the video duration increases, it might indicate that there's an optimal video length for maximizing engagement.\n",
    "\n",
    "Which engagement metric is most closely related to video duration: By comparing the correlation coefficients, you can determine which type of engagement (e.g., likes, shares) is most strongly affected by the length of the video."
   ]
  }
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