Jones, Keenan, Nurse, Jason R. C., Li, Shujun (2021) Out of the Shadows: Analyzing Anonymous’ Twitter Resurgence during the 2020 Black Lives Matter Protests. In: Proceedings of the 16th International AAAI Conference on Web and Social Media (ICWSM-22). . Association for the Advancement of Artificial Intelligence, USA (KAR id:89408)
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Abstract
Recently, there had been little notable activity from the once prominent hacktivist group, Anonymous. The group, responsible for activist-based cyber attacks on major businesses and governments, appeared to have fragmented after key members were arrested in 2013. In response to the major Black Lives Matter (BLM) protests that occurred after the killing of George Floyd, however, reports indicated that the group was back. To examine this apparent resurgence, we conduct a large-scale study of Anonymous affiliates on Twitter. To this end, we first use machine learning to identify a significant network of more than 33,000 Anonymous accounts. Through topic modelling of tweets collected from these accounts, we find evidence of sustained interest in topics related to BLM. We then use sentiment analysis on tweets focused on these topics, finding evidence of a united approach amongst the group, with positive tweets typically being used to express support towards BLM, and negative tweets typically being used to criticize police actions. Finally, we examine the presence of automation in the network, identifying indications of bot-like behavior across the majority of Anonymous accounts. These findings show that whilst the group has seen a resurgence during the protests, bot activity may be responsible for exaggerating the extent of this resurgence.
Item Type: | Conference or workshop item (Paper) |
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Uncontrolled keywords: | Anonymous, We are legion, Topic Modelling, Sentiment Analysis, Bot Detection, Twitter, Social Media, Cybercrime, Cybercriminal, Hacktivism |
Subjects: |
H Social Sciences H Social Sciences > HM Sociology Q Science 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 |
Depositing User: | Keenan Jones |
Date Deposited: | 22 Jul 2021 09:59 UTC |
Last Modified: | 10 Oct 2023 11:55 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/89408 (The current URI for this page, for reference purposes) |
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