Emotional Analysis of Bogus Statistics in Social Media

Abstract

Fake info or bogus statistics is a new term and it is now considered as a greatest threat to democracy. Since the world is full of surprises and humans have developed their delicate nature to detect unexcepted information. Social media plays a vital role in information spreading, since the impact towards fake information has gained more attention due to the social media platforms. Trending the hot topic without analyzing the information will introduce great impact over millions of people. So, it is essential to analyze the message and its truthfulness. Emotional analysis is an important factor in bogus statistics as the information gets reshared among other based on individual emotions. Considering these facts in social media information analysis, an efficient emotional analysis for bogus statistics in social media is proposed in this research work using recurrent neural network. In an emotional perspective, fake messages are compared with actual message and false messages are identified experimentally using recurrent neural network.