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Behind the Mask: A Computational Study of Anonymous' Presence on Twitter

Jones, Keenan, Nurse, Jason R. C., Li, Shujun (2020) Behind the Mask: A Computational Study of Anonymous' Presence on Twitter. In: 14th International AAAI Conference on Web and Social Media (ICWSM). . (KAR id:80660)

Abstract

The hacktivist group Anonymous is unusual in its public-facing nature. Unlike other cybercriminal groups, which rely on secrecy and privacy for protection, Anonymous is prevalent on the social media site, Twitter. In this paper we re-examine some key findings reported in previous small-scale qualitative studies of the group using a large-scale computational analysis of Anonymous' presence on Twitter. We specifically refer to reports which reject the group's claims of leaderlessness, and indicate a fracturing of the group after the arrests of prominent members in 2011-2013. In our research, we present the first attempts to use machine learning to identify and analyse the presence of a network of over 20,000 Anonymous accounts spanning from 2008-2019 on the Twitter platform. In turn, this research utilises social network analysis (SNA) and centrality measures to examine the distribution of influence within this large network, identifying the presence of a small number of highly influential accounts. Moreover, we present the first study of tweets from some of the identified key influencer accounts and, through the use of topic modelling, demonstrate a similarity in overarching subjects of discussion between these prominent accounts. These findings provide robust, quantitative evidence to support the claims of smaller-scale, qualitative studies of the Anonymous collective.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: Anonymous, Anon, We are legion, Social Network Analysis, Topic Modelling, Online Social Networks, Social Media, Cybercrime, Cybercriminal, Hacktivism
Subjects: H Social Sciences
H Social Sciences > HM Sociology
Q Science > QA Mathematics (inc Computing science)
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Divisions > Division of Human and Social Sciences > School of Psychology
Depositing User: Jason Nurse
Date Deposited: 30 Mar 2020 15:34 UTC
Last Modified: 16 Feb 2021 14:12 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/80660 (The current URI for this page, for reference purposes)

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