How does Twitter account moderation work? Dynamics of account creation and suspension on Twitter during major geopolitical events
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Abstract (arXiv)
Social media moderation policies are often at the center of public debate, and their implementation and enactment are sometimes surrounded by a veil of mystery. Unsurprisingly, due to limited platform transparency and data access, relatively little research has been devoted to characterizing moderation dynamics, especially in the context of controversial events and the platform activity associated with them. Here, we study the dynamics of account creation and suspension on Twitter during two global political events: Russia's invasion of Ukraine and the 2022 French Presidential election. Leveraging a large-scale dataset of 270M tweets shared by 16M users in multiple languages over several months, we identify peaks of suspicious account creation and suspension, and we characterize behaviours that more frequently lead to account suspension. We show how large numbers of accounts get suspended within days from their creation. Suspended accounts tend to mostly interact with legitimate users, as opposed to other suspicious accounts, often making unwarranted and excessive use of reply and mention features, and predominantly sharing spam and harmful content. While we are only able to speculate about the specific causes leading to a given account suspension, our findings shed light on patterns of platform abuse and subsequent moderation during major events.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Sep 2022.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 2; 2025: 0; 2026: 1.
6 papers.
- 2023Social-LLM: Modeling User Behavior at Scale using Language Models and Social Network Datacited by 11
- 2023The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social Mediacited by 10
- 2022Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trollscited by 8
- 2024Harm Mitigation in Recommender Systems under User Preference Dynamicscited by 5
- 2024Safeguarding Decentralized Social Media: LLM Agents for Automating Community Rule Compliancecited by 5
- 2026The Enforcement and Feasibility of Hate Speech Moderationcited by 1
- 2026The Enforcement and Feasibility of Hate Speech Moderation14 Apr 2026
- 2024Safeguarding Decentralized Social Media: LLM Agents for Automating Community Rule Compliance13 Sep 2024
- 2024Harm Mitigation in Recommender Systems under User Preference Dynamics14 Jun 2024
- 2023Social-LLM: Modeling User Behavior at Scale using Language Models and Social Network Data31 Dec 2023
- 2023The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social Media16 Dec 2023
- 2022Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls17 Oct 2022