NLP Fake News Detector
Advanced NLP-powered misinformation classifier utilizing BERT architecture with a real-time web interface and confidence scoring.
Combatting Misinformation at Scale
With the rise of AI-generated content and misleading journalism, we built an enterprise tool to score semantic authenticity and factual bias in real-time.
Context Aware
Understands sarcasm, bias, and leading tones, not just keywords.
Real-time Web App
Instantaneous results via a Flask streaming backend.
Cross-Referencing
Automatically compares claims against trusted data warehouses.
Technical Strategy
Traditional TF-IDF algorithms failed at understanding semantics. We upgraded the stack to transformer architectures.
DistilBERT Fine-Tuning
Trained the HuggingFace DistilBERT model on a massive corpus of verified vs debunked news articles.
Attention Visualizer
Extracted the internal attention weights of the model to literally highlight the words driving the 'Fake' classification.
Async API Workers
Managed high-load API requests using Celery and Redis to prevent blocking during intensive NLP tokenization.