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FakeNewsDetector.py (1334, 2023-10-25)
news.zip (12046622, 2023-10-25)

# Fake News Data Analysis This repository contains a Python script for analyzing fake news using the Passive Aggressive Classifier. The script takes a dataset of news articles and classifies them into "FAKE" or "REAL" categories. In this README, you'll find information about the project, how to run the code, and the project's structure. ## Table of Contents - [Project Overview](https://github.com/kayteekay1412/Fake-news-detector/blob/master/#project-overview) - [Requirements](https://github.com/kayteekay1412/Fake-news-detector/blob/master/#requirements) - [Usage](https://github.com/kayteekay1412/Fake-news-detector/blob/master/#usage) - [Project Structure](https://github.com/kayteekay1412/Fake-news-detector/blob/master/#project-structure) - [License](https://github.com/kayteekay1412/Fake-news-detector/blob/master/#license) ## Project Overview Fake news has become a significant concern in the era of information overload. This project aims to classify news articles as either "FAKE" or "REAL" using the Passive Aggressive Classifier and TF-IDF vectorization. The code provided here allows you to load a dataset, preprocess the text data, train the classifier, and evaluate its accuracy. ## Requirements Before you run the code, you'll need to make sure you have the following dependencies installed: - Python 3.x - NumPy - pandas - scikit-learn You can install the required packages using the following command: ```bash pip install numpy pandas scikit-learn ``` ## Usage 1. **Clone the Repository** Clone this repository to your local machine using Git: ```bash git clone https://github.com/kayteekay1412/Fake-news-detector.git cd Fake-news-detector ``` 2. **Download and Extract the Dataset** The dataset is included in a zip file (`news.zip`) within the repository. You'll need to extract it. Run the following command in the project directory: ```bash unzip news.zip ``` 3. **Run the Code** Open a terminal or command prompt and navigate to the project directory. Run the Python script `FakeNewsDetector.py` using the following command: ```bash python FakeNewsDetector.py ``` The script will load the dataset, preprocess the text data, train the Passive Aggressive Classifier, and display the accuracy score and a confusion matrix. 4. **Interpret the Results** The script will output the accuracy of the model in classifying fake and real news articles. You can also observe the confusion matrix for further analysis. ## Project Structure The project is organized as follows: ``` Fake-news-detector/ │ ├── FakeNewsDetector.py # Python script for fake news analysis │ ├── news.zip # Dataset (zipped for distribution) │ ├── README.md # This README file ```

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