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Fake News Detection System with NLP Analytics

Beginner Machine Learning
12/26/2025 vv1.0

Objective

The Fake News Detection System is a Flask-based web application that uses Machine Learning and NLP to classify news content as Real or Fake. Users log in securely and submit news text for analysis. The system processes the input using a pre-trained ML pipeline and provides prediction results along with a confidence score.

To enhance transparency, the application also generates text analytics, including word count, character count, sentiment polarity, and subjectivity using TextBlob. This makes the system not only a classifier but also an insightful tool for understanding news tone and credibility.

The project demonstrates the practical application of NLP, text preprocessing, and probabilistic ML models in combating misinformation and can be extended for journalism, media monitoring, and content verification platforms.

Tech Stack

Bootstrap CSS Flask HTML Python

Project File Includes

  • Complete Source Code
  • Structured MySQL Database (.sql - if applicable)
  • Comprehensive Project Report (DOC/PDF)
  • Presentation Slides (PPT)
  • Step-by-Step Installation Guide

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