Detection_Fake_News.ipynb

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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import classification_report\n",
        "import re\n",
        "import string\n"
      ]
    },
    {
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      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
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      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset_fake = pd.read_csv('/content/drive/MyDrive/news dataset/Fake[1].csv')\n",
        "dataset_true = pd.read_csv('/content/drive/MyDrive/news dataset/True[1].csv')"
      ],
      "metadata": {
        "id": "cxnmuZB2H0My"
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      "execution_count": 3,
      "outputs": []
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        "dataset_fake.head(5)"
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              "                                               title  \\\n",
              "0   Donald Trump Sends Out Embarrassing New Year’...   \n",
              "1   Drunk Bragging Trump Staffer Started Russian ...   \n",
              "2   Sheriff David Clarke Becomes An Internet Joke...   \n",
              "3   Trump Is So Obsessed He Even Has Obama’s Name...   \n",
              "4   Pope Francis Just Called Out Donald Trump Dur...   \n",
              "\n",
              "                                                text subject  \\\n",
              "0  Donald Trump just couldn t wish all Americans ...    News   \n",
              "1  House Intelligence Committee Chairman Devin Nu...    News   \n",
              "2  On Friday, it was revealed that former Milwauk...    News   \n",
              "3  On Christmas day, Donald Trump announced that ...    News   \n",
              "4  Pope Francis used his annual Christmas Day mes...    News   \n",
              "\n",
              "                date  \n",
              "0  December 31, 2017  \n",
              "1  December 31, 2017  \n",
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              "                                               title  \\\n",
              "0  As U.S. budget fight looms, Republicans flip t...   \n",
              "1  U.S. military to accept transgender recruits o...   \n",
              "2  Senior U.S. Republican senator: 'Let Mr. Muell...   \n",
              "3  FBI Russia probe helped by Australian diplomat...   \n",
              "4  Trump wants Postal Service to charge 'much mor...   \n",
              "\n",
              "                                                text       subject  \\\n",
              "0  WASHINGTON (Reuters) - The head of a conservat...  politicsNews   \n",
              "1  WASHINGTON (Reuters) - Transgender people will...  politicsNews   \n",
              "2  WASHINGTON (Reuters) - The special counsel inv...  politicsNews   \n",
              "3  WASHINGTON (Reuters) - Trump campaign adviser ...  politicsNews   \n",
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        "for i in range(23480,23470,-1):\n",
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        "dataset_true_manual_testing = dataset_true.tail(10)\n",
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              "                                               title  \\\n",
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              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
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              "      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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\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-b549f77a-8347-4a7a-86d7-126d8e1701b9 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-b549f77a-8347-4a7a-86d7-126d8e1701b9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset_merge.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D4uyZSZTEqU6",
        "outputId": "072fcc7e-c77f-4201-8980-e008eaabaa8d"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['title', 'text', 'subject', 'date', 'class'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset=dataset_merge.drop([\"title\",\"subject\",\"date\"], axis=1)"
      ],
      "metadata": {
        "id": "TlCkZlrTqDgT"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.isnull().sum()"
      ],
      "metadata": {
        "id": "oc2pZB3jiVAK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2159a78a-09ae-429e-8a04-c037af23f098"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "text     0\n",
              "class    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset = dataset.sample(frac = 1)"
      ],
      "metadata": {
        "id": "EYJxVVM3FHBP"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "BbQOiojbFSO_",
        "outputId": "7c0ce738-3b06-4430-986c-79a0d51dde6c"
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      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    text  class\n",
              "7668   WASHINGTON (Reuters) - President Barack Obama ...      1\n",
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              "5005   BERLIN (Reuters) - She is controlled and cauti...      1\n",
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f2533be9-718b-4e0a-a7c4-b93998938b5a')\"\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "          document.querySelector('#df-f2533be9-718b-4e0a-a7c4-b93998938b5a button.colab-df-convert');\n",
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              "\n",
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              "          const element = document.querySelector('#df-f2533be9-718b-4e0a-a7c4-b93998938b5a');\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",
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              "          element.appendChild(docLink);\n",
              "        }\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.reset_index(inplace = True)\n",
        "dataset.drop([\"index\"], axis = 1, inplace = True)"
      ],
      "metadata": {
        "id": "D6tJIUH2FeeN"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kEWJJEFAF2p1",
        "outputId": "ded0d15a-21a3-427d-d1f5-0ec345c97b14"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['text', 'class'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "VN4BcEIqF8qu",
        "outputId": "08921158-e553-4351-c384-9e2c4e7105ef"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                text  class\n",
              "0  WASHINGTON (Reuters) - President Barack Obama ...      1\n",
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              "2  BERLIN (Reuters) - She is controlled and cauti...      1\n",
              "3  As time goes on, it becomes ever clearer that ...      0\n",
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            ],
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              "      <th>3</th>\n",
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              "</table>\n",
              "</div>\n",
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              "              style=\"display:none;\">\n",
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              "  </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",
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              "      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-32ad475d-0ed9-479b-bbd7-15ec8dd48d6b 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-32ad475d-0ed9-479b-bbd7-15ec8dd48d6b');\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": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def word_drop(text):\n",
        "  text = text.lower()\n",
        "  text = re.sub(\"\\[.*?\\]\",\" \", text)\n",
        "  text = re.sub(\"\\\\W\",\" \", text)\n",
        "  text = re.sub(\"https?://\\S+www\\.\\S+\",\" \", text)\n",
        "  text = re.sub(\"<.*?>+\",\" \", text)\n",
        "  text = re.sub(\"[%s]\" % re.escape(string.punctuation),\" \", text)\n",
        "  text = re.sub(\"\\n\",\" \", text)\n",
        "  text = re.sub(\"\\w*\\d\\w*\",\" \", text)\n",
        "  return text"
      ],
      "metadata": {
        "id": "mFO-1D30DJfc"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        " dataset[\"text\"] = dataset[\"text\"].apply(word_drop)"
      ],
      "metadata": {
        "id": "cGB5F9VsJddW"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x = dataset[\"text\"]\n",
        "y = dataset[\"class\"]"
      ],
      "metadata": {
        "id": "oua2gZnhGlGr"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train, x_test, y_train, y_test = train_test_split(x,y, test_size = 0.25)"
      ],
      "metadata": {
        "id": "Y0VD2GfbKd4o"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer"
      ],
      "metadata": {
        "id": "rJ6iJU5YK_VO"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "vectorization = TfidfVectorizer()\n",
        "xv_train = vectorization.fit_transform(x_train)\n",
        "xv_test = vectorization.transform(x_test)"
      ],
      "metadata": {
        "id": "YNjIoCFCLmfb"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "###Logistic Regression"
      ],
      "metadata": {
        "id": "c_RFk6vGOP0Y"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LogisticRegression"
      ],
      "metadata": {
        "id": "9nfLLUyTMfO1"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "LR = LogisticRegression()\n",
        "LR.fit(xv_train, y_train)"
      ],
      "metadata": {
        "id": "IXV21j5dMq6Y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "44abcd5e-3459-4ff4-8c9e-16dad7cbaf17"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression()"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "LR.score(xv_test, y_test)"
      ],
      "metadata": {
        "id": "qSmv9OwqM5Zc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2cd11e07-140f-4bca-c711-db729a62f838"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9876114081996435"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pred_LR = LR.predict(xv_test)"
      ],
      "metadata": {
        "id": "_1Tmt5PGNzAN"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_test, pred_LR))"
      ],
      "metadata": {
        "id": "6u9yednXN5zA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8b728d65-d060-48fa-ae69-ed021e2764a3"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      0.99      0.99      5968\n",
            "           1       0.98      0.99      0.99      5252\n",
            "\n",
            "    accuracy                           0.99     11220\n",
            "   macro avg       0.99      0.99      0.99     11220\n",
            "weighted avg       0.99      0.99      0.99     11220\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def output_lable(n):\n",
        "  if n == 0:\n",
        "    return \"Fake News\"\n",
        "  elif n == 1:\n",
        "    return \"True News\"\n",
        "\n",
        "def manual_testing(news):\n",
        "  testing_news = {\"text\":[news]}\n",
        "  new_def_test = pd.DataFrame(testing_news)\n",
        "  new_def_test[\"text\"] = new_def_test[\"text\"].apply(word_drop)\n",
        "  new_x_test = new_def_test[\"text\"]\n",
        "  new_xv_test = vectorization.transform(new_x_test)\n",
        "  pred_LR = LR.predict(new_xv_test)\n",
        "  \n",
        "  return print(\"\\n\\nLR Prediction: {} \".format(output_lable(pred_LR[0])))\n",
        "                                                                                                            "
      ],
      "metadata": {
        "id": "XIknxXVxW4rR"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "news = input()\n",
        "manual_testing(str(news))"
      ],
      "metadata": {
        "id": "_FRcTYk29n4i",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5d00c3df-2f57-4169-c1f9-0826625bbee9"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "fhdhd\n",
            "\n",
            "\n",
            "LR Prediction: Fake News \n"
          ]
        }
      ]
    }
  ]
}