Combating misinformation dissemination through verification and content driven recommendation

Abstract

The COVID 19 pandemic is a humanitarian emergency that poses an enormous threat to society and has impacted various social media platforms and journalism. News and social media has become an immensely popular platform for consumption of information. However, these platforms are also the bearer of fake news and information which causes negative effects and creates panic. Thus, this research work aim to tackle this problem by creating a unique hybrid model using Machine learning algorithms with Natural Language Processing (NLP) techniques to verify news. In order to make the proposed system foolproof, a superior content based recommendation system is developed which will encourage users to consume authenticated news and content from verified sources. Thus, such a system will provide a holistic approach as it not only verifies but also provides genuine and true recommendations for the same.