Behind the Mask: A Computational Study of Anonymous’ Presence on Twitter Keenan Jones, Jason R. C. Nurse, Shujun Li School of Computing & Kent Interdisciplinary Research Centre in Cyber Security (KirCCS) University of Kent, UK fksj5, j.r.c.nurse,
[email protected] Abstract Interestingly, there are a significant number of Twitter accounts claiming some form of affiliation with Anony- The hacktivist group Anonymous is unusual in its public- mous. From these accounts’ interactions and posts, one can facing nature. Unlike other cybercriminal groups, which rely begin to establish a sense of how the structure and mes- on secrecy and privacy for protection, Anonymous is preva- sage of Anonymous as a group is presented. Accordingly, lent on the social media site, Twitter. In this paper we re- examine some key findings reported in previous small-scale in this research we aim to use the findings of our large- qualitative studies of the group using a large-scale compu- scale study of Anonymous Twitter accounts to examine the tational analysis of Anonymous’ presence on Twitter. We contentions of smaller-scale, often interview-focused stud- specifically refer to reports which reject the group’s claims ies of the group. Such studies reject claims by the group of leaderlessness, and indicate a fracturing of the group af- to its nebulous, leaderless nature (Uitermark 2017; Olson ter the arrests of prominent members in 2011-2013. In our 2013). Furthermore, they suggest that Anonymous fractured research, we present the first attempts to use machine learn- as the result of the arrests of key affiliates (Goode 2015; ing to identify and analyse the presence of a network of over Olson 2013); a factor which again refutes the argument of 20,000 Anonymous accounts spanning from 2008-2019 on a decentralised group structure.