newsLime

News Lime is a Flask-based web application that employs a machine learning model to determine the authenticity of news articles. It helps users discern whether a given news article is fake or real, offering a valuable tool to combat misinformation and fake news.

Features

Fake News Detection: newsLime uses a powerful machine learning model to predict whether a news article is real or fake.
User-Friendly Web Interface: The Flask web application provides an easy-to-use interface for users to input news articles and receive predictions.
Data Processing: The application leverages data processing libraries like Numpy and Pandas to prepare the text data for the model.
Scalability: As it's built on Flask, you can easily scale and deploy this application to reach a wider audience.

Getting Started

Follow these steps to get the newsLime web application up and running on your local machine:

Prerequisites

Python 3.9
Virtual environment (recommended)

Installation

Clone the repository:

   git clone https://github.com/oyeadii/newsLime.git

Change to the project directory:

   cd newsLime

Create a virtual environment (optional but recommended):

   python -m venv venv

Activate the virtual environment: On Windows:

   venv\Scripts\activate

On macOS and Linux:

   source venv/bin/activate

Install the required packages:

   pip install -r requirements.txt

Run the Flask application:

   python app.py

Access the application in your web browser by navigating to http://localhost:5000.

Usage

Enter the text of the news article you want to analyze in the provided input field on the web interface.
Click the "Submit" button to get the model's prediction.
The application will display whether the news article is "Real" or "Fake."

Technology Stack

Flask: Web application framework
Python: Language for machine learning and web development
Scikit-learn: Machine learning library for model training and prediction
Numpy and Pandas: Data processing libraries

oyeadii/newsLime