This project aims to detect fake news articles by analyzing textual content using Natural Language Processing and supervised machine learning techniques, helping users verify information authenticity and reduce misinformation spread.
Collect real and fake news datasets Clean and preprocess textual data Apply NLP techniques like tokenization and stemming Convert text to numerical features Train classifiers such as Naive Bayes and SVM Evaluate accuracy and precision Build a web interface for news verification Enable article submission and result display Implement confidence scoring Test with real-world examples Document methodology and results
