Abstract:
Social network and online news media are becoming
popular in today’s era. Due to low cost, easy access and
rapid diffusion, social media platform becomes a source to
distribute false information. Fake news propagation on
social media can cause serious negative effects on human
society especially in politic, reputation and finance. So,
automatic fake news detection plays a vital role to robust
news media platform on social network. Defining news
authenticity is insufficient based on news content only. It also
needs to analyze social features of news. In this paper, we
propose an approach to detect fake news on social media that
covers both news content and social context. We use
synonym-based feature extraction method and three different
classifiers based on multidimensional dataset. Experimental
result shows the effective as an accuracy way to define news
authenticity on online news media.