A Two-Fold Approach to Tackle Fake News

Abstract

With the revolution and growth of the media industry, and development of new mediums to update citizens with the latest news, in recent years there has been a spurt in the production of articles spreading fake information. Many media channels leverage on the concept of spreading eye-catching malicious news that attracts readers which has been proven to be quite dangerous in most cases. These channels post an exaggerated version of the truth, thus leading to an emerging trend of spreading fake news. To tackle this problem, we propose a two-step solution involving machine learning and block chain. The proposed solution consists of a news verification portal using a two-fold approach, which first detects whether the news article is fake or real leveraging the accuracy of a machine learning algorithm and then verifies the source using human crowd auditors on a block chain platform based on proof-of-stake.