Fake News Detection In Social Media Using Machine Learning Techniques

Authors: Shalini, Rajesh M, Gowthami T, Kavya MK, Kajal

Abstract: Fake News (FN) in online platform distress today's society. With the rapid growth of technology, news content is being created and shared very quickly. Much of this content is designed to influence readers or viewers into believing false information. Although such content may not always cause serious harm, it is still important to detect fake news so that internet users can access accurate and trustworthy information. Unfortunately, identifying fake content is not easy for ordinary users.Fake news usually appears in either visual form (images or videos) or linguistic form (text). Therefore, detecting false information requires proper analysis methods along with machine learning (ML)–based artificial intelligence techniques. While current methods are able to detect fake content to a certain extent, each approach has its own advantages and limitations.The main goal of social media analysis is to examine the features and weaknesses of existing models and to understand suitable fake news detection (FND) techniques for research purposes. Accordingly, this study analyzes the working methods, strengths, and limitations of various fake news detection approaches.