Mitigating the Effects of Fake News using Blockchain and Machine Learning

Abstract

Every second a large amount of news is exchanged amongst people with Internet as its driving force. Cheap and easily accessible Internet services across the world have made it even easier for the fake news to spread quickly than the real ones. Moreover, in order to gain TRP (Television Rating Point), many of the news agencies and media houses themselves indulge in malpractices, contributing towards the spread of false news. This sometimes results in riots and political as well as communal instability. Thus, in order to stop the spread of false news, blockchain technology integrated with artificial intelligence and machine learning techniques can be used. In this paper, we have proposed a model based on the above stated technologies named as Reliable News Sharing Platform (RNSP) that aims at ensuring that only real news is communicated and false news is not only detected but is also stopped from being communicated. Anonymous news publication, no central governance, no external interference, credit system are some of the salient features of our proposed model.