A Comparative Study of Computational Fake News Detection on Social Media

Abstract Social media platforms has become widely popular among netizens to share views and news. This can be attributed to easy affordability of digital devices, low cost Internet and free subscription to social media platforms. Individuals find social media platforms quite appealing where they can find like-minded people to exchange views and news. Studies have shown that a less credible person is more likely to propagate fake news in order to fulfill their objectives of any form - seeking attention, gaining financial benefits or influencing political views. Hence, fake news detection on social media has become one of the most envisaged research topics in recent times. Fake news detection on social media can be done through various methods based on sources, transmission, styles, and knowledge. The major contribution of this survey paper is to provide a comparative study of major computational methods for fake news detection on social media. The objective of this study is to help researchers carry further research using the details and the research gaps presented in the paper.