DNN based fake news identification and analysis

Abstract

In this project we show an approach for detecting fake statements made by public figures by means of artificial intelligence. Several approaches were implemented as a software system and tested against a data set of statements. The best achieved result in binary classification problem (true or false statement) is 86%. The results may be improved in several ways that are described in the article as well. The progress in modern informational technologies brings us to the era where information is as accessible as ever. It is possible to find the answers to the questions we are interested in a matter of seconds. Availability of mobile devices makes it even more convenient for the users. This factor changed the way of how people get the news information a lot. Every mainstream mass media has its own online portal, Facebook account, Twitter account etc., so people can access news information really quickly.