A Survey on Identification of Fake News

Abstract

Fake News is a major problem faced by many agencies and organisations which may seem like a corporate issue but is a threat to the very idea of democracy and every citizen's right to information. It is one of the major false practice issue growing at an enormous rate on online social media platforms disrupting the journalistic practices of spreading the truth to the people unaware of the background of news. Stanford University, in one of its recent studies, has provided a definition of fake news, "We define fake news to be news articles that are intentionally and verifiably false, and could mislead readers". News sensationalism, falsification, and exaggeration are the first steps in spreading these pieces of propaganda. It is one of the biggest problems for news organisations which are trying to report truth to the average citizen but are slowed down in the process due to some culprits for their own gains and compromising all the journalistic effort put in by all the people behind the news cycle. Machine Learning and Data Science are contemporary fields of computer science which are able handle complex problems and are tackling those problems head on. Ours is an effort to use these vast technologies to solve the problem of fake news on social platforms like Twitter.