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NLP Fake News Analysis A machine learning-based project to detect fake news using natural language processing (NLP) techniques. The model processes news articles and predicts their authenticity (real or fake). This repository includes a trained model, preprocessing pipeline, and a simple Flask app for web-based analysis.

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chaimaaskri/NLP_fake-news-analysis11

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NLP Fake News Analysis - v1.1

Short Repo Description

NLP Fake News Analysis
A machine learning-based project to detect fake news using natural language processing (NLP) techniques. The model processes news articles and predicts their authenticity (real or fake). This repository includes a trained model, preprocessing pipeline, and a simple Flask app for web-based analysis.

Project Overview

This project utilizes Natural Language Processing (NLP) techniques to detect fake news in articles. Using a machine learning model, the system can predict whether a news article is real or fake based on its text. The model is trained on a dataset of labeled news articles and serves as a tool for analyzing news URLs via a Flask web app.

Technologies Used

  • Python
  • Flask
  • Scikit-learn
  • nltk (Natural Language Toolkit)
  • Pickle for model serialization
  • Newspaper3k for article scraping

Features

  • Web Interface: Allows users to input a news article URL, automatically fetches the article content, and analyzes its authenticity.
  • Model: A trained machine learning model to classify news articles as either fake or real.
  • Flask API: A lightweight Python web framework that powers the prediction API.

Installation

Clone the Repository

git clone https://github.com/chaimaaskri/NLP_fake-news-analysis11.git
cd NLP_fake-news-analysis11

About

NLP Fake News Analysis A machine learning-based project to detect fake news using natural language processing (NLP) techniques. The model processes news articles and predicts their authenticity (real or fake). This repository includes a trained model, preprocessing pipeline, and a simple Flask app for web-based analysis.

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