TRUTH AT YOUR FINGERTIPS: AI's FIGHT AGAINST FAKE NEWS
Harsh Rathod, Durvesh Shelar, Rudrapratap Singh, Niki Modi · 2025
The rapid growth of digital media and the widespread use of social platforms have drastically increased the circulation of information-both real and fabricated. Fake news, often intentionally created to mislead, manipulate opinions, or generate online engagement, poses a serious threat to individuals, society, and democratic processes. This paper presents a comprehensive overview of an AIbased Fake News Detector that leverages machine learning and natural language processing (NLP) techniques to identify and classify misleading news content. By examining key features such as linguistic patterns, sentiment tone, propagation behavior, and user interactions, the proposed system aims to detect fake news at an early stage. The model integrates data-driven approaches using deep learning and hybrid propagation networks to improve detection accuracy. This work highlights the need for robust, explainable, and real-time solutions to mitigate the societal impact of misinformation, and also outlines future directions for enhancing model reliability across multiple platforms and languages.