Related papers: Characterizing Social Imaginaries and Self-Disclosures of Dissonance in Online Conspiracy Discussion Communities

Characterizing Social Imaginaries and Self-Disclosures of Dissonance in Online Conspiracy Discussion Communities

URL: http://arxiv.org/abs/2107.10204v1
Date: Wed, 21 Jul 2021 16:49:21 GMT
Title: Characterizing Social Imaginaries and Self-Disclosures of Dissonance in Online Conspiracy Discussion Communities
Authors: Shruti Phadke, Mattia Samory, Tanushree Mitra
Abstract summary: This paper characterizes self-disclosures of dissonance about QAnon, a conspiracy theory initiated by a mysterious leader Q. We focus on 2K posts from two image boards, 4chan and 8chan, and 1.2 M comments and posts from 12 subreddits dedicated to QAnon. We find that self-disclosures of dissonance correlate with a significant decrease in user contributions and ultimately with their departure from the community.
Score: 8.680081568962997
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: Online discussion platforms offer 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 which 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 conspiracy theory 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. Further, analyzing user engagement with QAnon conspiracy subreddits, we find that self-disclosures of dissonance correlate with a significant decrease in user contributions and ultimately with their departure from the community. We contribute a computational framework for identifying dissonance self-disclosures and measuring the changes in user engagement surrounding dissonance. Our work can provide insights into designing dissonance-based interventions that can potentially dissuade conspiracists from online conspiracy discussion communities.

Related papers

The Conspiracy Money Machine: Uncovering Telegram's Conspiracy Channels and their Profit Model [53.83179030955546]
We find that Telegram is a perfect breeding ground for a complex ecosystem of conspiracy channels. Conspiracy channels can be clustered into four distinct communities comprising over 17,000 channels. We uncover the "Conspiracy Money Machine," revealing how most conspiracy channels actively seek to profit from their subscribers.
arXiv Detail & Related papers (2023-10-24T16:25:52Z)
Characterizing Reddit Participation of Users Who Engage in the QAnon Conspiracy Theories [10.161390454133821]
This paper focuses on the QAnon conspiracy theory, a consequential conspiracy theory that started on and disseminated successfully through social media. Our work characterizes how Reddit users who have participated in QAnon-focused subreddits engage in activities on the platform. We collected the 2.1 million submissions and 10.8 million comments posted by these users across all of Reddit from October 2016 to January 2021.
arXiv Detail & Related papers (2022-03-14T18:41:40Z)
Where the Earth is flat and 9/11 is an inside job: A comparative algorithm audit of conspiratorial information in web search results [62.997667081978825]
We examine the distribution of conspiratorial information in search results across five search engines: Google, Bing, DuckDuckGo, Yahoo and Yandex. We find that all search engines except Google consistently displayed conspiracy-promoting results and returned links to conspiracy-dedicated websites in their top results. Most conspiracy-promoting results came from social media and conspiracy-dedicated websites while conspiracy-debunking information was shared by scientific websites and, to a lesser extent, legacy media.
arXiv Detail & Related papers (2021-12-02T14:29:21Z)
Comparing the Language of QAnon-related content on Parler, Gab, and Twitter [68.8204255655161]
Parler, a "free speech" platform popular with conservatives, was taken offline in January 2021 due to the lack of moderation of hateful and QAnon- and other conspiracy-related content. We compare posts with the hashtag #QAnon on Parler over a month-long period with posts on Twitter and Gab. Gab has the highest proportion of #QAnon posts with hate terms, and Parler and Twitter are similar in this respect. On all three platforms, posts mentioning female political figures, Democrats, or Donald Trump have more anti-social language than posts mentioning male politicians, Republicans, or
arXiv Detail & Related papers (2021-11-22T11:19:15Z)
A network-based approach to QAnon user dynamics and topic diversity during the COVID-19 infodemic [1.776746672434207]
QAnon is an umbrella conspiracy theory that encompasses a wide spectrum of people. The COVID-19 pandemic has helped raise the QAnon conspiracy theory to a wide-spreading movement. We study users' dynamics on Twitter related to the QAnon movement.
arXiv Detail & Related papers (2021-10-31T16:34:43Z)
How do climate change skeptics engage with opposing views? Understanding mechanisms of social identity and cognitive dissonance in an online forum [0.0]
We study the impact of opposing views within a major climate change skeptic online community on Reddit. We find that ideologically dissonant submissions act as a stimulant to activity in the community. Users who engaged with dissonant submissions were also more likely to return to the forum.
arXiv Detail & Related papers (2021-02-12T13:39:00Z)
The Gospel According to Q: Understanding the QAnon Conspiracy from the Perspective of Canonical Information [10.788583114755838]
We study the QAnon conspiracy theory from the perspective of "Q" themself. We build a dataset of 4,949 canonical Q drops collected from six "aggregation sites" We analyze the Q drops' contents to identify topics of discussion and find statistically significant indications that drops were not authored by a single individual.
arXiv Detail & Related papers (2021-01-21T18:03:24Z)
The Truth is Out There: Investigating Conspiracy Theories in Text Generation [66.01545519772527]
We investigate the propensity for language models to generate conspiracy theory text. Our study focuses on testing these models for the elicitation of conspiracy theories. We introduce a new dataset consisting of conspiracy theory topics, machine-generated conspiracy theories, and human-written conspiracy theories.
arXiv Detail & Related papers (2021-01-02T05:47:39Z)
"Is it a Qoincidence?": An Exploratory Study of QAnon on Voat [12.14455026524814]
The QAnon conspiracy theory emerged in 2017 on 4chan. We study the most popular named entities mentioned in the posts, along with the most prominent topics of discussion. Our graph visualization shows that some of the QAnon-related ones are closely related to those from the Pizzagate conspiracy theory.
arXiv Detail & Related papers (2020-09-10T14:25:28Z)
Racism is a Virus: Anti-Asian Hate and Counterspeech in Social Media during the COVID-19 Crisis [51.39895377836919]
COVID-19 has sparked racism and hate on social media targeted towards Asian communities. We study the evolution and spread of anti-Asian hate speech through the lens of Twitter. We create COVID-HATE, the largest dataset of anti-Asian hate and counterspeech spanning 14 months.
arXiv Detail & Related papers (2020-05-25T21:58:09Z)
Echo Chambers on Social Media: A comparative analysis [64.2256216637683]
We introduce an operational definition of echo chambers and perform a massive comparative analysis on 1B pieces of contents produced by 1M users on four social media platforms. We infer the leaning of users about controversial topics and reconstruct their interaction networks by analyzing different features. We find support for the hypothesis that platforms implementing news feed algorithms like Facebook may elicit the emergence of echo-chambers.
arXiv Detail & Related papers (2020-04-20T20:00:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.