DECIDING METRICS FOR DETECTING FALSE NEWS AND INFLUENCE ON TWITTER

Abstract

The era of the social media brings with it quite some information and news that is untrue and misleading to the masses. This issue is such that needs to be addressed as people today are highly dependent on their mobile devices and online news portals that they tend to make uninformed decisions based on these pieces of false information they get. The purpose of this paper is to help people and industries alike, to differentiate good quality sources from bad ones based on a certain distinction of metrics and methodologies. This paper probes into current trends adopted by fake information promulgators and how to spot and work around those.