Fake News Detector

High Accuracy Performance: This model achieves 98.8% accuracy on test data, correctly identifying fake and real news with high confidence. Tested on over 44,000 articles with consistent performance across different sample sizes.

Domain Specialization: Optimized for US political news content (2016-2017 era). Works best with complete articles rather than headlines or fragments. May have reduced accuracy on non-political content or international news.

Responsible Usage: While highly accurate, this tool should complement—not replace—human judgment and fact-checking. Always verify critical information through multiple reliable sources and consider context, source credibility, and supporting evidence.

Technical Foundation: Built using Passive Aggressive Classifier with TF-IDF vectorization, trained on labeled datasets of real and fake political news articles. Regular testing ensures consistent performance standards.