A Machine Learning Framework for Countering Fake News Propagation

A Machine Learning Framework for Countering Fake News Propagation

Ms.M.Lalitha1, G.Gayathri2, S.Kiruthika3, S.Nethra4
1 Professor, Department of Computer Science and Engineering, Muthayammal Engineering College, Namakkal.

2 3 4 Students, Department of Computer Science and Engineering, Muthayammal Engineering College, Namakkal.

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Abstract - The widespread use of social media has accelerated the spread of fake news, eroding public trust and making fact verification difficult. This project presents a machine learning framework using Natural Language Processing (NLP) and Decision Tree algorithms to classify news articles as real or fake. The system includes data preprocessing, TF-IDF-based feature extraction, and model training to detect misinformation accurately. Designed for both accuracy and interpretability, the framework offers a scalable solution for real-time fake news detection, with strong potential for integration into social media platforms and automated fact-checking tools.

Keywords : Fake News Detection, Machine Learning Natural Language Processing (NLP),Decision Tree Classifier , TF-IDF , Text Classification , Misinformation,Social Media Analysis, Data Preprocessing, Feature Extraction