# Pathways through Conspiracy: The Evolution of Conspiracy Radicalization through Engagement in Online Conspiracy Discussions

arXiv: https://arxiv.org/abs/2204.10729 · HTML: https://mlsanity.com/paper/2204.10729/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 40 references that are in the map.
- First posted on arXiv 22 Apr 2022.

## Builds on (most cited first, 11 of 11)

- [The Pushshift Reddit Dataset](https://mlsanity.com/paper/2001.08435/) (2020)
- [Community Interaction and Conflict on the Web](https://mlsanity.com/paper/1803.03697/) (2018)
- [A Benchmark Study on Time Series Clustering](https://mlsanity.com/paper/2004.09546/) (2020)
- [Loyalty in Online Communities](https://mlsanity.com/paper/1703.03386/) (2017)
- [Science vs Conspiracy: collective narratives in the age of (mis)information](https://mlsanity.com/paper/1408.1667/) (2014)
- [Identifying the social signals that drive online discussions: A case study of Reddit communities](https://mlsanity.com/paper/1705.02673/) (2017)
- [What Makes People Join Conspiracy Communities?: Role of Social Factors in Conspiracy Engagement](https://mlsanity.com/paper/2009.04527/) (2020)
- [To Act or React: Investigating Proactive Strategies For Online Community Moderation](https://mlsanity.com/paper/1906.11932/) (2019)
- [Islamophobes are not all the same! A study of far right actors on Twitter](https://mlsanity.com/paper/1910.05794/) (2019)
- [Behavior Change in Response to Subreddit Bans and External Events](https://mlsanity.com/paper/2101.01793/) (2021)
- [Characterizing Social Imaginaries and Self-Disclosures of Dissonance in Online Conspiracy Discussion Communities](https://mlsanity.com/paper/2107.10204/) (2021)

## Built on by (most cited first, 8 of 8)

- [Spillover of Antisocial Behavior from Fringe Platforms: The Unintended Consequences of Community Banning](https://mlsanity.com/paper/2209.09803/) (2022)
- [Relevance meets Diversity: A User-Centric Framework for Knowledge Exploration through Recommendations](https://mlsanity.com/paper/2408.03772/) (2024)
- [Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls](https://mlsanity.com/paper/2210.08786/) (2022)
- [Understanding Online Migration Decisions Following the Banning of Radical Communities](https://mlsanity.com/paper/2212.04765/) (2022)
- [Stranger Danger! Cross-Community Interactions with Fringe Users Increase the Growth of Fringe Communities on Reddit](https://mlsanity.com/paper/2310.12186/) (2023)
- [Algorithmic Drift: A Simulation Framework to Study the Effects of Recommender Systems on User Preferences](https://mlsanity.com/paper/2409.16478/) (2024)
- [Making Transparency Advocates: An Educational Approach Towards Better Algorithmic Transparency in Practice](https://mlsanity.com/paper/2412.15363/) (2024)
- [Beyond the Rabbit Hole: Mapping the Relational Harms of QAnon Radicalization](https://mlsanity.com/paper/2601.17658/) (2026)

## Abstract (arXiv)

The disruptive offline mobilization of participants in online conspiracy theory (CT) discussions has highlighted the importance of understanding how online users may form radicalized conspiracy beliefs. While prior work researched the factors leading up to joining online CT discussions and provided theories of how conspiracy beliefs form, we have little understanding of how conspiracy radicalization evolves after users join CT discussion communities. In this paper, we provide the empirical modeling of various radicalization phases in online CT discussion participants. To unpack how conspiracy engagement is related to radicalization, we first characterize the users' journey through CT discussions via conspiracy engagement pathways. Specifically, by studying 36K Reddit users through their 169M contributions, we uncover four distinct pathways of conspiracy engagement: steady high, increasing, decreasing, and steady low. We further model three successive stages of radicalization guided by prior theoretical works. Specific sub-populations of users, namely those on steady high and increasing conspiracy engagement pathways, progress successively through various radicalization stages. In contrast, users on the decreasing engagement pathway show distinct behavior: they limit their CT discussions to specialized topics, participate in diverse discussion groups, and show reduced conformity with conspiracy subreddits. By examining users who disengage from online CT discussions, this paper provides promising insights about conspiracy recovery process.