Fake_News_Detection/Fake_News_Detection.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "811ece47",
   "metadata": {},
   "source": [
    "# Fake News Detection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98eb1687",
   "metadata": {},
   "source": [
    "### Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6351fdc2",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to C:\\Users\\Jatin\n",
      "[nltk_data]     Dhall\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "#re = regular expression(Useful for searching the text in a document)\n",
    "import re\n",
    "#nltk => Natural Language toolkit\n",
    "#corpus => body of the text\n",
    "#Stop words are those words, that don't add much value to the text(a,an,the,what,where)\n",
    "from nltk.corpus import stopwords\n",
    "#PorterStemmer is used for stemming(Removes the prefix and suffix of the word and returns the root word for it)\n",
    "from nltk.stem.porter import PorterStemmer\n",
    "#TfidfVectorizer is used to convert the words into feature vectors(Numbers)\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "import nltk\n",
    "nltk.download(\"stopwords\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2c542e20",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n"
     ]
    }
   ],
   "source": [
    "#Printing the stopwords in english\n",
    "print(stopwords.words('english'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f454785c",
   "metadata": {},
   "source": [
    "### Loading the dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f22588d",
   "metadata": {},
   "source": [
    "### Loading the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6ba2da83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>author</th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>House Dem Aide: We Didn’t Even See Comey’s Let...</td>\n",
       "      <td>Darrell Lucus</td>\n",
       "      <td>House Dem Aide: We Didn’t Even See Comey’s Let...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>FLYNN: Hillary Clinton, Big Woman on Campus - ...</td>\n",
       "      <td>Daniel J. Flynn</td>\n",
       "      <td>Ever get the feeling your life circles the rou...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Why the Truth Might Get You Fired</td>\n",
       "      <td>Consortiumnews.com</td>\n",
       "      <td>Why the Truth Might Get You Fired October 29, ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>15 Civilians Killed In Single US Airstrike Hav...</td>\n",
       "      <td>Jessica Purkiss</td>\n",
       "      <td>Videos 15 Civilians Killed In Single US Airstr...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Iranian woman jailed for fictional unpublished...</td>\n",
       "      <td>Howard Portnoy</td>\n",
       "      <td>Print \\nAn Iranian woman has been sentenced to...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                                              title              author  \\\n",
       "0   0  House Dem Aide: We Didn’t Even See Comey’s Let...       Darrell Lucus   \n",
       "1   1  FLYNN: Hillary Clinton, Big Woman on Campus - ...     Daniel J. Flynn   \n",
       "2   2                  Why the Truth Might Get You Fired  Consortiumnews.com   \n",
       "3   3  15 Civilians Killed In Single US Airstrike Hav...     Jessica Purkiss   \n",
       "4   4  Iranian woman jailed for fictional unpublished...      Howard Portnoy   \n",
       "\n",
       "                                                text  label  \n",
       "0  House Dem Aide: We Didn’t Even See Comey’s Let...      1  \n",
       "1  Ever get the feeling your life circles the rou...      0  \n",
       "2  Why the Truth Might Get You Fired October 29, ...      1  \n",
       "3  Videos 15 Civilians Killed In Single US Airstr...      1  \n",
       "4  Print \\nAn Iranian woman has been sentenced to...      1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"dataset.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "da1c7a7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20800, 5)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Shape of the dataset\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be831667",
   "metadata": {},
   "source": [
    "### Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0af554de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id           0\n",
       "title      558\n",
       "author    1957\n",
       "text        39\n",
       "label        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking for missing values\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a4e26bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Handling missing values\n",
    "#Replacing the missing values with empty strings\n",
    "data = data.fillna('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f89d7645",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id        0\n",
       "title     0\n",
       "author    0\n",
       "text      0\n",
       "label     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ff93c179",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merging the author name and news title to form the input\n",
    "data['content'] = data[\"author\"] + ' ' + data[\"title\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "06603a96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        Darrell Lucus House Dem Aide: We Didn’t Even S...\n",
       "1        Daniel J. Flynn FLYNN: Hillary Clinton, Big Wo...\n",
       "2        Consortiumnews.com Why the Truth Might Get You...\n",
       "3        Jessica Purkiss 15 Civilians Killed In Single ...\n",
       "4        Howard Portnoy Iranian woman jailed for fictio...\n",
       "                               ...                        \n",
       "20795    Jerome Hudson Rapper T.I.: Trump a ’Poster Chi...\n",
       "20796    Benjamin Hoffman N.F.L. Playoffs: Schedule, Ma...\n",
       "20797    Michael J. de la Merced and Rachel Abrams Macy...\n",
       "20798    Alex Ansary NATO, Russia To Hold Parallel Exer...\n",
       "20799              David Swanson What Keeps the F-35 Alive\n",
       "Name: content, Length: 20800, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['content']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "24be8bf8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#To make predictions we will be using the content column as features and labels as targets\n",
    "#Seperating the data and label\n",
    "x = data.drop(columns = 'label',axis = 1)\n",
    "y = data['label']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c7f0f3c8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>author</th>\n",
       "      <th>text</th>\n",
       "      <th>content</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>House Dem Aide: We Didn’t Even See Comey’s Let...</td>\n",
       "      <td>Darrell Lucus</td>\n",
       "      <td>House Dem Aide: We Didn’t Even See Comey’s Let...</td>\n",
       "      <td>Darrell Lucus House Dem Aide: We Didn’t Even S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>FLYNN: Hillary Clinton, Big Woman on Campus - ...</td>\n",
       "      <td>Daniel J. Flynn</td>\n",
       "      <td>Ever get the feeling your life circles the rou...</td>\n",
       "      <td>Daniel J. Flynn FLYNN: Hillary Clinton, Big Wo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Why the Truth Might Get You Fired</td>\n",
       "      <td>Consortiumnews.com</td>\n",
       "      <td>Why the Truth Might Get You Fired October 29, ...</td>\n",
       "      <td>Consortiumnews.com Why the Truth Might Get You...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>15 Civilians Killed In Single US Airstrike Hav...</td>\n",
       "      <td>Jessica Purkiss</td>\n",
       "      <td>Videos 15 Civilians Killed In Single US Airstr...</td>\n",
       "      <td>Jessica Purkiss 15 Civilians Killed In Single ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Iranian woman jailed for fictional unpublished...</td>\n",
       "      <td>Howard Portnoy</td>\n",
       "      <td>Print \\nAn Iranian woman has been sentenced to...</td>\n",
       "      <td>Howard Portnoy Iranian woman jailed for fictio...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                                              title              author  \\\n",
       "0   0  House Dem Aide: We Didn’t Even See Comey’s Let...       Darrell Lucus   \n",
       "1   1  FLYNN: Hillary Clinton, Big Woman on Campus - ...     Daniel J. Flynn   \n",
       "2   2                  Why the Truth Might Get You Fired  Consortiumnews.com   \n",
       "3   3  15 Civilians Killed In Single US Airstrike Hav...     Jessica Purkiss   \n",
       "4   4  Iranian woman jailed for fictional unpublished...      Howard Portnoy   \n",
       "\n",
       "                                                text  \\\n",
       "0  House Dem Aide: We Didn’t Even See Comey’s Let...   \n",
       "1  Ever get the feeling your life circles the rou...   \n",
       "2  Why the Truth Might Get You Fired October 29, ...   \n",
       "3  Videos 15 Civilians Killed In Single US Airstr...   \n",
       "4  Print \\nAn Iranian woman has been sentenced to...   \n",
       "\n",
       "                                             content  \n",
       "0  Darrell Lucus House Dem Aide: We Didn’t Even S...  \n",
       "1  Daniel J. Flynn FLYNN: Hillary Clinton, Big Wo...  \n",
       "2  Consortiumnews.com Why the Truth Might Get You...  \n",
       "3  Jessica Purkiss 15 Civilians Killed In Single ...  \n",
       "4  Howard Portnoy Iranian woman jailed for fictio...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "05cf9585",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    0\n",
       "2    1\n",
       "3    1\n",
       "4    1\n",
       "Name: label, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d990b346",
   "metadata": {},
   "source": [
    "### Stemming Procedure\n",
    "#### Stemming is the process of reducing a word to its Root Word\n",
    "##### Eg : actor, actress, acting ==> act"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b0244e60",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Using Porter Stemmer\n",
    "port_stem = PorterStemmer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "50960f54",
   "metadata": {},
   "outputs": [],
   "source": [
    "def stemming(content):\n",
    "    stemmed_content = re.sub('[^a-zA-Z]',' ',content)\n",
    "    stemmed_content = stemmed_content.lower()\n",
    "    stemmed_content = stemmed_content.split()\n",
    "    stemmed_content = [port_stem.stem(word) for word in stemmed_content if not word in stopwords.words('english')]\n",
    "    stemmed_content = ' '.join(stemmed_content)\n",
    "    return stemmed_content"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca43e3bf",
   "metadata": {},
   "source": [
    "### Before Stemming"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9f51f499",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    darrel lucu hous dem aid even see comey letter...\n",
       "1    daniel j flynn flynn hillari clinton big woman...\n",
       "2               consortiumnew com truth might get fire\n",
       "3    jessica purkiss civilian kill singl us airstri...\n",
       "4    howard portnoy iranian woman jail fiction unpu...\n",
       "Name: content, dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['content'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ce399d9",
   "metadata": {},
   "source": [
    "### Stemming"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "64a0ec77",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['content'] = data['content'].apply(stemming)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9f6e1bf",
   "metadata": {},
   "source": [
    "### After Stemming"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c25b4914",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0        darrel lucu hou dem aid even see comey letter ...\n",
      "1        daniel j flynn flynn hillari clinton big woman...\n",
      "2                   consortiumnew com truth might get fire\n",
      "3        jessica purkiss civilian kill singl us airstri...\n",
      "4        howard portnoy iranian woman jail fiction unpu...\n",
      "                               ...                        \n",
      "20795    jerom hudson rapper trump poster child white s...\n",
      "20796    benjamin hoffman n f l playoff schedul matchup...\n",
      "20797    michael j de la merc rachel abram maci said re...\n",
      "20798    alex ansari nato russia hold parallel exerci b...\n",
      "20799                            david swanson keep f aliv\n",
      "Name: content, Length: 20800, dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(data['content'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "25355bbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Since text is huge, we are not using it as a feature\n",
    "# Seperating the data and label\n",
    "x = data['content'].values\n",
    "y = data['label'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "4ee186cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['darrel lucu hou dem aid even see comey letter jason chaffetz tweet'\n",
      " 'daniel j flynn flynn hillari clinton big woman campu breitbart'\n",
      " 'consortiumnew com truth might get fire' ...\n",
      " 'michael j de la merc rachel abram maci said receiv takeov approach hudson bay new york time'\n",
      " 'alex ansari nato russia hold parallel exerci balkan'\n",
      " 'david swanson keep f aliv']\n"
     ]
    }
   ],
   "source": [
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "cb5af4be",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 0 1 ... 0 1 1]\n"
     ]
    }
   ],
   "source": [
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4c4ad628",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20800,)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "0423ef7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20800,)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "033a863f",
   "metadata": {},
   "source": [
    "### Converting the text of content into numerical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b1a3e235",
   "metadata": {},
   "outputs": [],
   "source": [
    "# converting the textual data to numerical data\n",
    "vectorizer = TfidfVectorizer()\n",
    "vectorizer.fit(x)\n",
    "\n",
    "x = vectorizer.transform(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "a8de53d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  (0, 15553)\t0.28485063562728646\n",
      "  (0, 13348)\t0.2565896679337957\n",
      "  (0, 8822)\t0.3635963806326075\n",
      "  (0, 8546)\t0.29212514087043684\n",
      "  (0, 7612)\t0.24785219520671603\n",
      "  (0, 6930)\t0.21874169089359144\n",
      "  (0, 4917)\t0.233316966909351\n",
      "  (0, 3759)\t0.2705332480845492\n",
      "  (0, 3567)\t0.3598939188262559\n",
      "  (0, 2933)\t0.2468450128533713\n",
      "  (0, 2464)\t0.3676519686797209\n",
      "  (0, 263)\t0.27010124977708766\n",
      "  (1, 16656)\t0.3025156488372128\n",
      "  (1, 6744)\t0.19152496072048605\n",
      "  (1, 5440)\t0.7186013955384664\n",
      "  (1, 3535)\t0.2653147533915268\n",
      "  (1, 2790)\t0.19208753385709676\n",
      "  (1, 2206)\t0.36915639258038363\n",
      "  (1, 1877)\t0.15614790568229528\n",
      "  (1, 1481)\t0.2957471154505952\n",
      "  (2, 15478)\t0.41544962664721613\n",
      "  (2, 9532)\t0.49351492943649944\n",
      "  (2, 5903)\t0.3474613386728292\n",
      "  (2, 5326)\t0.3866530551182615\n",
      "  (2, 3072)\t0.46097489583229645\n",
      "  :\t:\n",
      "  (20797, 12998)\t0.2483705036831893\n",
      "  (20797, 12227)\t0.27276402145717243\n",
      "  (20797, 12022)\t0.24790022252744132\n",
      "  (20797, 10216)\t0.0804189541935242\n",
      "  (20797, 9500)\t0.17463635692029988\n",
      "  (20797, 9431)\t0.2939494781564304\n",
      "  (20797, 8901)\t0.3617803783368178\n",
      "  (20797, 8282)\t0.22333184464489023\n",
      "  (20797, 6969)\t0.21809398920480086\n",
      "  (20797, 3610)\t0.211655450844435\n",
      "  (20797, 1274)\t0.33553980418478896\n",
      "  (20797, 689)\t0.30700415486138355\n",
      "  (20797, 43)\t0.29724348057612154\n",
      "  (20798, 12923)\t0.22363267488270608\n",
      "  (20798, 10949)\t0.4460515589182236\n",
      "  (20798, 10088)\t0.3192496370187028\n",
      "  (20798, 6816)\t0.32496285694299426\n",
      "  (20798, 4974)\t0.4083701450239529\n",
      "  (20798, 1112)\t0.4460515589182236\n",
      "  (20798, 580)\t0.3112141524638974\n",
      "  (20798, 345)\t0.28446937819072576\n",
      "  (20799, 14723)\t0.5677577267055112\n",
      "  (20799, 7955)\t0.45983893273780013\n",
      "  (20799, 3590)\t0.37927626273066584\n",
      "  (20799, 372)\t0.5677577267055112\n"
     ]
    }
   ],
   "source": [
    "print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c269070",
   "metadata": {},
   "source": [
    "### Splitting our data into training and testing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "c8ebbee4",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test = train_test_split(x,y,test_size = 0.2,random_state = 2,stratify = y)\n",
    "#Stratify makes sure that the proportion of real news vs fake news in the real data set is maintained in the train test split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "5606ece8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(20800,) (16640,) (4160,)\n"
     ]
    }
   ],
   "source": [
    "print(y.shape,y_train.shape,y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a207f153",
   "metadata": {},
   "source": [
    "### Logistic Regression Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "ff15a389",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = LogisticRegression()\n",
    "model.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69240656",
   "metadata": {},
   "source": [
    "### Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c3194e77",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9790865384615385\n"
     ]
    }
   ],
   "source": [
    "pred = model.predict(x_test)\n",
    "acc = accuracy_score(pred,y_test)\n",
    "print(acc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b81a0a1e",
   "metadata": {},
   "source": [
    "### Making a predictive system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "72865cd9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0] 0\n",
      "The news is fake\n"
     ]
    }
   ],
   "source": [
    "x_new = x_test[1]\n",
    "\n",
    "prediction = model.predict(x_new)\n",
    "print(prediction,y_test[1])\n",
    "if prediction == 1:\n",
    "    print(\"The news is true\")\n",
    "else:\n",
    "    print(\"The news is fake\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}