Project Overview
This NLP-based project detects fake news articles by analyzing their textual content. The dataset was preprocessed with stopword removal, tokenization, and TF-IDF vectorization before being trained on Logistic Regression and PassiveAggressiveClassifier.
Tools & Techniques
Python NLTK TF-IDF Scikit-learn Pandas
Key Outcomes
- Achieved 95% accuracy using TF-IDF + Logistic Regression.
- Reduced false positives through text normalization.
- Effective on real-world article datasets.