The Gospel According to Q: Understanding the QAnon Conspiracy from the Perspective of Canonical Information
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Abstract (arXiv)
The QAnon conspiracy theory claims that a cabal of (literally) blood-thirsty politicians and media personalities are engaged in a war to destroy society. By interpreting cryptic "drops" of information from an anonymous insider calling themself Q, adherents of the conspiracy theory believe that Donald Trump is leading them in an active fight against this cabal. QAnon has been covered extensively by the media, as its adherents have been involved in multiple violent acts, including the January 6th, 2021 seditious storming of the US Capitol building. Nevertheless, we still have relatively little understanding of how the theory evolved and spread on the Web, and the role played in that by multiple platforms. To address this gap, we study QAnon from the perspective of "Q" themself. We build a dataset of 4,949 canonical Q drops collected from six "aggregation sites," which curate and archive them from their original posting to anonymous and ephemeral image boards. We expose that these sites have a relatively low (overall) agreement, and thus at least some Q drops should probably be considered apocryphal. We then analyze the Q drops' contents to identify topics of discussion and find statistically significant indications that drops were not authored by a single individual. Finally, we look at how posts on Reddit are used to disseminate Q drops to wider audiences. We find that dissemination was (initially) limited to a few sub-communities and that, while heavy-handed moderation decisions have reduced the overall issue, the "gospel" of Q persists on the Web.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Jan 2021.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 1.
4 papers.
- 2022Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbotscited by 33
- 2021Characterizing Social Imaginaries and Self-Disclosures of Dissonance in Online Conspiracy Discussion Communitiescited by 2
- 2023Who could be behind QAnon? Authorship attribution with supervised machine-learningcited by 2
- 2025Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websitescited by 1
- 2025Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websites15 Jan 2025
- 2023Who could be behind QAnon? Authorship attribution with supervised machine-learning3 Mar 2023
- 2022Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots7 Sep 2022
- 2021Characterizing Social Imaginaries and Self-Disclosures of Dissonance in Online Conspiracy Discussion Communities21 Jul 2021