Fake News Detection and Analysis

Abstract

Abstract: The internet is filled with inaccurate information, which makes it tough to distinguish between what is true and what is not. This review paper explores how scholars and IT professionals are countering false information by examining various strategies. We start by looking at different types of fake news and how they circulate. We then discuss a range of methods and tools that can be used to identify false information, including advanced computer programs and language analysis. These approaches can be categorized into three groups: analysing the language used, taking into account contextual data, and studying the distribution trends on the internet. We also discuss a method for teaching computers to detect patterns using machine learning false narratives by learning to differentiate between emotions and language subtleties. The paper also emphasizes the significance of fairness and impartiality in detection technologies. We conclude by discussing possible future research areas for academics and technology professionals it's critical to stay current with the quickly developing field of fake news.