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- Proceedings of the ACM on Human-Computer Interaction
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Online communities play a crucial role in disseminating conspiracy theories. New theories often emerge in the aftermath of catastrophic events. Despite evidence of their widespread appeal, surprisingly little is known about who participates in these event-specific conspiratorial discussions or how do these discussions evolve over time. We study r/conspiracy, an active Reddit community of more than 200,000 users dedicated to conspiratorial discussions. By focusing on four tragic events and 10 years of discussions, we find three distinct user cohorts: joiners, who never participated in Reddit but joined r/conspiracy only after the event; converts who were active Reddit users but joined r/conspiracy only after the event; and veterans, who are longstanding r/conspiracy members. While joiners and converts have a shorter lifespan in the community in comparison to the veterans, joiners are more active during their shorter tenure, becoming increasingly engaged over time. Finally, to investigate how these events affect users’ conspiratorial discussions, we adopted a causal inference approach to analyze user comments around the time of the events. We find that discussions happening after the event exhibit signs of emotional shock, increased language complexity, and simultaneous expressions of certainty and doubtfulness. Our work provides insight on how online communities may detectmore »
Recent research on conspiracy theories labels conspiracism as a distinct and deficient epistemic process. However, the tendency to pathologize conspiracism obscures the fact that it is a diverse and dynamic collective sensemaking process, transacted in public on the web. Here, we adopt a narrative framework to introduce a new analytical approach for examining online conspiracism. Narrative plays an important role because it is central to human cognition as well as being domain agnostic, and so can serve as a bridge between conspiracism and other modes of knowledge production. To illustrate the utility of our approach, we use it to analyze conspiracy theories identified in conversations across three different anti-vaccination discussion forums. Our approach enables us to capture more abstract categories without hiding the underlying diversity of the raw data. We find that there are dominant narrative themes across sites, but that there is also a tremendous amount of diversity within these themes. Our initial observations raise the possibility that different communities play different roles in the collective construction of conspiracy theories online. This offers one potential route for understanding not only cross-sectional differentiation, but the longitudinal dynamics of the narrative in future work. In particular, we are interested to examinemore »
Characterizing Social Imaginaries and Self-Disclosures of Dissonance in Online Conspiracy Discussion CommunitiesOnline discussion platforms provide a forum to strengthen and propagate belief in misinformed conspiracy theories. Yet, they also offer avenues for conspiracy theorists to express their doubts and experiences of cognitive dissonance. Such expressions of dissonance may shed light on who abandons misguided beliefs and under what circumstances. This paper characterizes self-disclosures of dissonance about QAnon-a conspiracy theory initiated by a mysterious leader "Q" and popularized by their followers ?anons"-in conspiratorial subreddits. To understand what dissonance and disbelief mean within conspiracy communities, we first characterize their social imaginaries-a broad understanding of how people collectively imagine their social existence. Focusing on 2K posts from two image boards, 4chan and 8chan, and 1.2 M comments and posts from 12 subreddits dedicated to QAnon, we adopt a mixed-methods approach to uncover the symbolic language representing the movement,expectations,practices,heroes and foes of the QAnon community. We use these social imaginaries to create a computational framework for distinguishing belief and dissonance from general discussion about QAnon, surfacing in the 1.2M comments. We investigate the dissonant comments to characterize the dissonance expressed along QAnon social imaginaries. Further, analyzing user engagement with QAnon conspiracy subreddits, we find that self-disclosures of dissonance correlate with a significant decrease in usermore »
How Anti-Social Personality Traits and Anti-Establishment Views Promote Beliefs in Election Fraud, QAnon, and COVID-19 Conspiracy Theories and Misinformation
Conspiracy theories and misinformation (CTM) became a salient feature of the Trump era. However, traditional explanations of political attitudes and behaviors inadequately account for beliefs in CTM or the deleterious behaviors they are associated with. Here, we integrate disparate literatures to explain beliefs in CTM regarding COVID-19, QAnon, and voter fraud. We aim to provide a more holistic accounting, and to determine which political, psychological, and social factors are most associated with such beliefs. Using a unique national survey, we find that anti-social personality traits, anti-establishment orientations, and support for Donald Trump are more strongly related to beliefs in CTM than traditional left-right orientations or other frequently posited factors, such as education, science literacy, and social media use. Our findings encourage researchers to move beyond the traditional correlates of political behavior when examining beliefs that express anti-social tendencies or a deep skepticism of social and political institutions.
Daelemans, Walter (Ed.)Much previous work characterizing language variation across Internet social groups has focused on the types of words used by these groups. We extend this type of study by employing BERT to characterize variation in the senses of words as well, analyzing two months of English comments in 474 Reddit communities. The specificity of different sense clusters to a community, combined with the specificity of a community’s unique word types, is used to identify cases where a social group’s language deviates from the norm. We validate our metrics using user-created glossaries and draw on sociolinguistic theories to connect language variation with trends in community behavior. We find that communities with highly distinctive language are medium-sized, and their loyal and highly engaged users interact in dense networks.