Are You a Cyborg, Bot or Human?—A Survey on Detecting Fake News Spreaders

Abstract

One of the major components of Societal Digitalization is Online social networks (OSNs). OSNs can expose people to different popular trends in various aspects of life and alter people’s beliefs, behaviors, and decisions and communication. Social bots and malicious users are the significant sources for spreading misinformation on social media and can pose serious cyber threats in society. The degree of similarity of user profiles of a cyber bot and a malicious user spreading fake news is so great that it is very difficult to differentiate both based on their attributes. Over the years, researchers have attempted to find a way to mitigate this problem. However, the detection of fake news spreaders across OSNs remains a challenge. In this paper, we have provided a comprehensive survey of the state of art methods for detecting malicious users and bots based on different features proposed in our novel taxonomy. We have also aimed to avert the crucial problem of fake news detection by discussing several key challenges and potential future research areas to help researchers who are new to this field.