Identifying Fake News via Machine Learning and Web Scrapping

Abstract

Abstract: After digitalization, the increase in use of social media has led the flow of information among the social network users unchecked. The news is immediately transported to social networks, where it is quickly read, marked with opinions (on Facebook), and shared (on Twitter and Facebook) without being verified as accurate or false numerous times. In the modern world, fake news is an issue that has grown difficult to detect. Its impact on the judgement of commonfolk is noticeable, society has witnessed numerous events where the rampant flow of unverified news had affected the society as a whole. The sharing of fake news has become a major issue to the society. Our project aims to aid in reduction of e-crimes like use of social media for sharing of fake content. This will be achieved by training the machine to identify text based fake content. Using this the time for work of filtering out the fake content will be reduced by great lengths whilst helping the mass to get verified and credible news.