The role of evidence-based misogyny in antifeminist online communities of the ‘manosphere’

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY Big Data & Society Pub Date : 2023-01-01 DOI:10.1177/20539517221145671
A. Rothermel
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引用次数: 1

Abstract

In recent years, there have been a growing number of online and offline attacks linked to a loosely connected network of misogynist and antifeminist online communities called ‘the manosphere’. Since 2016, the ideas spread among and by groups of the manosphere have also become more closely aligned with those of other Far-Right online networks. In this commentary, I explore the role of what I term ‘evidence-based misogyny’ for mobilization and radicalization into the antifeminist and misogynist subcultures of the manosphere. Evidence-based misogyny is a discursive strategy, whereby members of the manosphere refer to (and misinterpret) knowledge in the form of statistics, studies, news items and pop-culture and mimic accepted methods of knowledge presentation to support their essentializing, polarizing views about gender relations in society. Evidence-based misogyny is a core aspect for manosphere-related mobilization as it provides a false sense of authority and forges a collective identity, which is framed as a supposed ‘alternative’ to mainstream gender knowledge. Due to its core function to justify and confirm the misogynist sentiments of users, evidence-based misogyny serves as connector between the manosphere and both mainstream conservative as well as other Far-Right and conspiratorial discourses.
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基于证据的厌女症在“管理圈”的反女权主义网络社区中的作用
近年来,越来越多的线上和线下攻击事件与一个由厌女症和反女权主义者组成的松散网络社区“管理圈”(the manosphere)有关。自2016年以来,政治圈团体之间传播的观点也与其他极右翼在线网络的观点更加一致。在这篇评论中,我探讨了我所说的“基于证据的厌女症”在动员和激进化管理圈的反女权主义和厌女主义亚文化方面的作用。基于证据的厌女症是一种话语策略,男性圈的成员以统计、研究、新闻和流行文化的形式引用(并误解)知识,并模仿公认的知识呈现方法,以支持他们对社会性别关系的本质化、两极分化的观点。基于证据的厌女症是管理圈相关动员的一个核心方面,因为它提供了一种虚假的权威感,并伪造了一种集体身份,这种身份被视为主流性别知识的“替代”。由于其核心功能是证明和确认用户的厌女情绪,基于证据的厌女症充当了管理圈与主流保守派以及其他极右翼和阴谋论话语之间的纽带。
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来源期刊
Big Data & Society
Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
10.90
自引率
10.60%
发文量
59
审稿时长
11 weeks
期刊介绍: Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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