Fake News Detection on Social Networks

Adhithya Sundar, Sarang Agarwal, Mahesh HB

Abstract: The project titled 'Fake News Detection on Social Networks' aims to combat the rising threat of misinformation in the digital age. With the exponential growth of online content, the spread of false news has become a critical challenge, leading to various social, political, and economic consequences. This project focuses on developing a machine learning-based model that can accurately classify news articles as either true or fake. By employing a combination of Natural Language Processing (NLP) techniques and algorithms such as Recurrent Neural Networks (RNN), K-Nearest Neighbors (KNN), and Long Short- Term Memory (LSTM), the system will analyze the linguistic patterns and contextual information in news content.

Keywords: Fake News, Machine Learning, KNN, NLP, RNN and LSTM

How to Cite?: Adhithya Sundar, Sarang Agarwal, Mahesh HB, "Fake News Detection on Social Networks", Volume 14 Issue 5, May 2025, International Journal of Science and Research (IJSR), Pages: 901-905, https://www.ijsr.net/getabstract.php?paperid=MR25514154043, DOI: https://dx.doi.org/10.21275/MR25514154043