Methods and Challenges in Social Bots Detection: A Systematic Review - de Morais, Daniel Marques; Digiampietri, Luciano Antonio (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI); 2021: Anais do XVII Simpósio Brasileiro de Sistemas de Informação, 2021)
Social bots are automated users who make use of social networks to produce content and interact with network users, in order to mimic or attempt to alter user behaviors, with the purposes, among others, of spreading spam and malicious content, violate users privacy or mislead information in order to influence financial markets or electoral disputes, causing numerous losses. Detecting these bots is a major challenge since, as detection mechanisms evolve, its hiding properties are also enhanced to avoid such mechanisms, either by more sophisticated strategies for emulating real users or by organizing groups of bots in sophisticated networks with the same purpose (botnets). This paper presents a survey about social bot detection approaches, considering the techniques used, the set of characteristics considered for the classification as well as the target of identification (individual or botnets). The main open points identified as well as possible advances in research in the area are also discussed.