Based and confused: Tracing the political connotations of a memetic phrase across the web

IF 6.5 1区社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY

Big Data & Society Pub Date : 2023-01-01 DOI:10.1177/20539517231163175

S. Hagen, D. de Zeeuw

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引用次数: 1

Abstract

Current research on the weaponisation of far-right discourse online has mostly focused on the dangers of normalising hate speech. However, this often operates on questionable assumptions about how far-right terms retain problematic meanings over time and across different platforms. Yet contextual meaning-change, we argue, is key to assessing the normalisation of problematic but fuzzy terms as they spread across the Web. To redress this, our article traces the changing meaning of the term based, a word that was appropriated from Black Twitter to become a staple of online far-right slang in the mid-2010s. Through a quali-quantitative cross-platform approach, we analyse the evolution of the term between 2010 and 2021 on Twitter, Reddit and 4chan. We find that while the far right meaning of based partially survived, its meaning changed and was rendered diffuse as it was adopted by other communities, afforded by a repurposable kernel of meaning to based as ‘not caring about what other people think’ and ‘being true to yourself’ to which different (political) connotations were attached. This challenges the understanding of far-right memes and hate speech as carrying a single and persistent problematic message, and instead emphasises their varied meanings and subcultural functions within specific online communities.

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基于和困惑：在网络上追踪一个模因短语的政治含义

目前关于极右翼网络言论武器化的研究主要集中在仇恨言论正常化的危险上。然而，这通常基于有问题的假设，即随着时间的推移，极右翼术语在不同平台上保留了有问题的含义。然而，我们认为，上下文意义的变化是评估有问题但模糊的术语在网络上传播时是否正常化的关键。为了纠正这一点，我们的文章追溯了“基于”一词含义的变化，这个词从黑色推特中被挪用，在2010年代中期成为网络极右翼俚语的主要内容。通过quali量化跨平台方法，我们在推特、Reddit和4chan上分析了2010年至2021年间该术语的演变。我们发现，虽然“基于”的极右翼含义部分保留了下来，但随着它被其他社区采用，它的含义发生了变化，并变得分散开来，这是由一个可重新调整用途的核心含义提供的，即“不在乎别人的想法”和“忠于自己”，而不同的（政治）含义则附加于此。这挑战了人们对极右翼模因和仇恨言论的理解，认为它们携带着单一而持久的问题信息，反而强调了它们在特定网络社区中的不同含义和亚文化功能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-

CiteScore

10.90

自引率

10.60%

发文量

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.