Social Bots and Their Coordination During Online Campaigns: A Survey

Abstract

Online social networks (OSNs) are a major component of societal digitalization. OSNs alter how people communicate, make decisions, and form or change their beliefs, attitudes, and behaviors. Thus, they can now impact social groups, financial systems, and political communication at scale. As one type of OSN, social media platforms, such as Facebook, Twitter, and YouTube, serve as outlets for users to convey information to an audience as broad or targeted as the user desires. Over the years, these social media platforms have been infected with automated accounts, or bots, that are capable of hijacking conversations, influencing other users, and manipulating content dissemination. Although benign bots exist to facilitate legitimate activities, we focus on bots designed to perform malicious acts through social media platforms. Bots that mimic the social behaviors of humans are referred to as social bots. Social bots help automate sociotechnical behaviors, such as “liking” tweets, tweeting/retweeting a message, following users, and coordinating with or even competing against other bots. Some advanced social bots exhibit highly sophisticated traits of coordination and communication with complex organizational structures. This article presents a detailed survey of social bots, their types and behaviors, and how they impact social media, identification algorithms, and their coordination strategies in OSNs. The survey also discusses coordination in areas such as biological systems, interorganizational networks, and coordination games. Existing research extensively studied bot detection, but bot coordination is still emerging and requires more in-depth analysis. The survey covers existing techniques and open research issues on the analysis of social bots, their behaviors, and how social network theories can be leveraged to assess coordination during online campaigns.