PERFORMANCE ANALYSIS OF DIFFERENT DEEP LEARNING TECHNIQUES FOR DETECTING FAKE NEWS

ABSTRACT

Fake news is defined as news items which are not real, genuine and are generated to deceive or mislead users. With the rise in great demand for social networking sites, the distribution of fake news has become a major threat to various sectors. The process of seeking news articles from social networking sites is like a double-edged weapon [1]. On one side it is easy to access news from social networking sites. And on the other hand, the news being obtained on social media is being manipulated for personal interests. So there is a great need to identify fake news and promote the spread of genuine information. In this paper, different deep learning techniques are described and their performance is evaluated in detecting fake news