Fake News Buster : AI-Driven Detection and Elimination of Misinformation

Author(s)	Suraj Kumar S, Soundarya
Country	India
Abstract	News Guard, an innovative platform, aims to combat misinformation by employing advanced Natural Language Processing (NLP) techniques, specifically Recurrent Neural Networks (RNNs}.This research focuses on enhancing the accuracy of distinguishing between fake and real news articles.By analysing linguistic patterns, semantic structures, and contextual clues embedded in textual data, the RNN model developed by News Guard demonstrates promising results in classifying news articles. This abstract highlights the pivotal role of NLP-driven RNNs in the ongoing battle against misinformation, offering a robust framework for identifying and verifying trustworthy news sources amidst the deluge of information on the internet.
Keywords	— Fake news detection, Real news classification, NLP for news verification, recurrent neural networks for news analysis, Natural language processing in journalism, Text classification for news authenticity, Sentiment analysis in news articles
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-04-14
Cite This	Fake News Buster : AI-Driven Detection and Elimination of Misinformation - Suraj Kumar S, Soundarya - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.3088
DOI	https://doi.org/10.71097/IJSAT.v16.i2.3088
Short DOI	https://doi.org/g9fmxc

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