Tracking Fringe and Coordinated Activity on Twitter Leading Up To the US Capitol Attack
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Abstract (arXiv)
The aftermath of the 2020 US Presidential Election witnessed an unprecedented attack on the democratic values of the country through the violent insurrection at Capitol Hill on January 6th, 2021. The attack was fueled by the proliferation of conspiracy theories and misleading claims about the integrity of the election pushed by political elites and fringe communities on social media. In this study, we explore the evolution of fringe content and conspiracy theories on Twitter in the seven months leading up to the Capitol attack. We examine the suspicious coordinated activity carried out by users sharing fringe content, finding evidence of common adversarial manipulation techniques ranging from targeted amplification to manufactured consensus. Further, we map out the temporal evolution of, and the relationship between, fringe and conspiracy theories, which eventually coalesced into the rhetoric of a stolen election, with the hashtag #stopthesteal, alongside QAnon-related narratives. Our findings further highlight how social media platforms offer fertile ground for the widespread proliferation of conspiracies during major societal events, which can potentially lead to offline coordinated actions and organized violence.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Feb 2023.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 3; 2026: 3.
9 papers.
- 2023Leveraging Large Language Models to Detect Influence Campaigns in Social Mediacited by 13
- 2024Detection and Characterization of Coordinated Online Behavior: A Surveycited by 6
- 2025Emergent Coordinated Behaviors in Networked LLM Agents: Modeling the Strategic Dynamics of Information Operationscited by 6
- 2024IOHunter: Graph Foundation Model to Uncover Online Information Operationscited by 4
- 2025Density-aware Walks for Coordinated Campaign Detectioncited by 0
- 2025Quantifying Feature Importance for Online Content Moderationcited by 0
- 2026Unsupervised Anomaly Detection of Information Operations Users via Behavioral and Language Patternscited by 0
- 2026Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behaviorcited by 0
- 2026Not All Duplicates Are Coordination: Generic vs. Non-Generic Duplicate Campaigns in Information Operationscited by 0
- 2026Not All Duplicates Are Coordination: Generic vs. Non-Generic Duplicate Campaigns in Information Operations12 Sep 2026
- 2026Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior17 Aug 2026
- 2026Unsupervised Anomaly Detection of Information Operations Users via Behavioral and Language Patterns7 Jul 2026
- 2025Emergent Coordinated Behaviors in Networked LLM Agents: Modeling the Strategic Dynamics of Information Operations28 Oct 2025
- 2025Quantifying Feature Importance for Online Content Moderation22 Oct 2025
- 2025Density-aware Walks for Coordinated Campaign Detection16 Jun 2025
- 2024IOHunter: Graph Foundation Model to Uncover Online Information Operations19 Dec 2024
- 2024Detection and Characterization of Coordinated Online Behavior: A Survey2 Aug 2024
- 2023Leveraging Large Language Models to Detect Influence Campaigns in Social Media14 Nov 2023