Design and Implementation of a Fake News Detection System Using Machine Learning
Computer Science — 2025, Undergraduate
fake newsnatural language processingdetectionmachine learning
This study designed and implemented a Fake News Detection System that classifies news articles as genuine or false using text analysis. The rapid spread of misinformation on digital platforms poses serious social consequences. The system pre-processes article text, extracts relevant features, and applies classification models to determine credibility. Built with Python Django and SQLite, the system was evaluated using labelled news datasets. Findings revealed strong classification accuracy across article categories. The study recommends use of the system by news aggregators and social platforms together with human verification.
For reference and learning only. Do not submit this work as your own.
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