FAKE NEWS DETECTION USING MACHINE LEARNING

Abstract

Fake news has been increasingly prevalent in recent years due to the quick growth of online social networks, which are used for a variety of political and commercial goals. Users of online social networks can easily become infected by these online fake news with deceptive language, and this has already had a significant impact on offline culture. Finding bogus news quickly is a crucial step in enhancing the reliability of information in online social networks. In order to identify false news pieces, creators, and subjects from online social networks and assess the performance of these methods and algorithms, this research looks at them. The report also discusses the difficulties posed by the varied linkages across news sources and the unknowable characteristics of fake news.