Battling Fake News: A Survey on Mitigation Techniques and Identification

Abstract

Fake news are generally characterized as misdirected news, which are often constructed with a feeling of conviction and tricking people towards accepting a specific incident. Fake news spread widely due to its social associations. The multiplication of fake news via web-based media has opened up a new plethora for performing recognizable testing and regulation on fake news ideals and to alleviate its great influence on the popular hypothesis. Although different existing research works focuses on the distinguishing evidence obtained from fake news that depends on its substance or that abuses customer engagement with news via web-based media, there has been a growing enthusiasm on proactive advocacy methodologies in order to counteract the spread, deception, and its effect on society. This study describes the current topic of fake news and specifically presents the specialist difficulties related to it. This research work discusses about the existing strategies and procedures relevant to both DI and moderation by leveraging significant attention to the critical progress in each strategy along with their points of interest and constraints. Furthermore, the search was regularly limited by the nature of the existing datasets and their particular application settings. To mitigate this problem, this research work completely sort and summarizes the brand highlights obtained from the accessible datasets. Additionally, new exploration headings to further advance workable interdisciplinary agreements are also reported.