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Fake News Detector

My first NLP app — built to try out all the models and techniques I’ve learned so far. The motive here was not to give you 90% accuracy on blind test but to code everything that i have learned to make myself understand everything clearly. But the goal is to improve this project to make it more interactive , more fun and more accurate. :)

Paste some news, pick a feature extractor and model, and see if it’s Real or Fake. Compare different pipelines and explore what words influenced the prediction.


Features

  • Feature extractors: TF-IDF, n-grams, Word2Vec
  • Models: Logistic Regression, Random Forest, XGBoost
  • Confidence scores and word-level insights
  • Simple clickbait detection

How to Run

pip install -r requirements.txt
python -m spacy download en_core_web_sm
streamlit run app/app.py

About

My first-ever NLP project : built to apply everything I’ve learned so far. This simple app compares different text features and ML models to detect fake news, shows predictions with confidence, and adds basic explainability — all packed into an interactive Streamlit app.

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