Evaluating the Spread of Fake News and its Detection Techniques on Social Networking Sites

Abstract

The phenomenon of fake news has become a much contentious issue recently. The controversy regarding this issue has further been intensified by the openness of social media platforms. Via a systematic review, this paper offers a discussion on the spread and detection techniques of fake news on Social Networking Sites (SNSs). A total of 47 articles eventually fulfilled the inclusion criteria and were coded for the literature synthesis. The overall findings from the literature on fake news and social media have been extracted and synthesized to explore the creation, influence and popular techniques and dimensions used for fake news detection on SNSs. The results showed that various entities are involved in the creation and spread of fake news on SNSs, including malicious social and software agents. It was also found that early registered users, old people, female users, delusion-prone persons, dogmatic persons, and religious fundamentalists are more likely to believe in fake news than other groups of individuals. One of the major problems of the existing techniques is their deficiency in datasets. Therefore, future studies on fake news detection should focus on developing an all-inclusive model with comprehensive datasets. Social media users require fake news detection skills especially using linguistic approach. This study provides the public with valuable information about the spread and detection of fake news on SNSs. This is because SNSs are an important avenue for fake news providers.