Evaluating Fake News Detection Models

Abstract

Fake news is untrue information presented as news. It often the aim of damaging the reputation of a person or entity or making money through advertising like a picture, short film, song, etc., revenue. Due to exponential growth of information in online, it is very impossible to figure out the true from the false. Some of the social media networks such as Twitter, Instagram and Facebook are affected by their user through fake news, and it is very hard to catch the fake stories before they go viral. Today most of the people prefer to search and absorb media news instead conventional one. Now days the widespread distribution of fake news may affect people and society. So we decide to build a web app to detect the fake news. The credibility and trust in the news media are at an all-time low with an object that is made to look real or valuable in order to deceive people. It is becoming increasingly difficult to determine which news is real and which is fake various machine learning methods have been used to separate real news from fake ones like experts revealed that the painting was a fake. There are some of the aspects that has to be kept in mind considering the factas something is believable, it seems possible, real, or true that fake news detection is not only a simple web interface but also a quite complex thing that includes a lot of backend work to identify the information or reports about recent events.