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理解一场大流行:在知识黑暗网络中对新冠疫情进行推理。

Making sense of a pandemic: reasoning about COVID-19 in the intellectual dark web.

作者信息

Doody Sean

机构信息

National Consortium for the Study of Terrorism and Responses to Terrorism, University of Maryland, College Park, MD, United States.

出版信息

Front Sociol. 2024 Sep 16;9:1374042. doi: 10.3389/fsoc.2024.1374042. eCollection 2024.

Abstract

In this study, I examine how users of an online Reddit community, r/IntellectualDarkWeb, forged an anti-establishment collective identity through practices of "heterodox scientific" reasoning. I do so through a discursive analysis of comments and posts made to r/IntellectualDarkWeb during the COVID-19 pandemic. First, I deploy the BERTopic algorithm to cluster my corpus and surface topics pertaining to COVID-19. Second, I engage in a qualitative content analysis of the relevant clusters to understand how discourses about COVID-19 were mobilized by subreddit users. I show that discussions about COVID-19 were polarized along "contrarian" and "anti-contrarian" lines, with significant implications for the subreddit's process of collective identity. Overwhelmingly, contrarian content that expressed skepticism towards vaccines, mistrust towards experts, and cynicism about the medical establishment was affirmed by r/IntellectualDarkWeb users. By contrast, anti-contrarian content that sought to counter anti-vaccine rhetoric, defend expertise, or criticize subreddit users for their contrarianism was penalized. A key factor in this dynamic was Reddit's scoring mechanism, which empowered users to publicly upvote contrarian affirming content while simultaneously downvoting anti-contrarian content. As users participated in sense making about COVID-19, they deployed Reddit's scoring mechanism to reinforce a contrarian collective identity oriented around a practice of heterodox science. My research shows the continued relevance of the concept of collective identity in the digital age and its utility for understanding contemporary reactionary social movements.

摘要

在本研究中,我考察了在线Reddit社区r/IntellectualDarkWeb的用户如何通过“异见科学”推理实践塑造反建制集体身份。我通过对新冠疫情期间r/IntellectualDarkWeb上的评论和帖子进行话语分析来开展此项研究。首先,我运用BERTopic算法对我的语料库进行聚类,并找出与新冠疫情相关的主题。其次,我对相关聚类进行定性内容分析,以了解该子版块用户如何调动有关新冠疫情的话语。我发现,关于新冠疫情的讨论沿着“反主流”和“非反主流”的路线两极分化,这对该子版块的集体身份形成过程具有重大影响。绝大多数情况下,表达对疫苗的怀疑、对专家的不信任以及对医疗机构冷嘲热讽的反主流内容得到了r/IntellectualDarkWeb用户的肯定。相比之下,试图反驳反疫苗言论、捍卫专业知识或批评该子版块用户反主流立场的非反主流内容则受到打压。这种动态变化的一个关键因素是Reddit的评分机制,该机制使用户能够公开点赞反主流的肯定性内容,同时对非反主流内容进行踩低。当用户参与对新冠疫情的意义建构时,他们利用Reddit的评分机制强化了一种围绕异见科学实践形成的反主流集体身份。我的研究表明,集体身份概念在数字时代仍具有相关性,且有助于理解当代反动社会运动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ceb0/11440435/fb387f8e2534/fsoc-09-1374042-g001.jpg

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