Machine Learning Approaches based Fake News Detection

The accuracy of information on the Internet, particularly on social media, is a growing problem. In these arenas, erroneous information, or so-called false news, cannot be identified, analyzed, or corrected using web-based data. This paper discusses where to look for "fake news" and how to use it on Facebook, one of the most popular social media sites. The Naïve Bayes Classifier is used in this method to guess whether a post will be labeled FAKE or REAL. A number of techniques discussed in the paper can be used to improve results. The findings show that machine learning approaches can be used to solve the challenge of detecting misleading information.