数据驱动社会中的事实信号和事实怀旧

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY Big Data & Society Pub Date : 2023-01-01 DOI:10.1177/20539517231164118
Sun-ha Hong
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引用次数: 2

摘要

Post-truth告诉了一个公众在平台和其他数据驱动系统的帮助和怂恿下陷入非理性的故事。但我认为,这种认知共识的明显崩溃也被对事实和理性理念的大声而激进的承诺所主导——在这个地方,想象中的现代过去正被掠夺以获得残余的合法性。这篇文章确定了这种重新分配和神话化的两种常见做法。(1) 事实信号包括对事实和理性的表演性调用,然后将其武器化,以诋毁交际对手并建立情感团结。这通常与(2)事实怀旧密切相关:当“事实就是事实”时,对想象中的过去的培养,而我们这些优秀的自由主义主体,在看到事实时就能认出事实。这两种趋势都被一种联系的神话所支撑:一种仍然经久不衰的说法是,无论来源或意义如何,信息的最大化流通最终都会产生一个更理性的公众——尽管数据驱动的系统往往会破坏这种公众的条件。根据YouTube上放大的美国右翼“另类影响者”的例子,以及围绕事实核查实践的规范性论述,我认为,这种对现代残余权威的持续依赖是围绕数据驱动的公众的规范性辩论中的一个有害障碍,让我们陷入了英雄般多疑的个人和无知、非理性的大众的死胡同。
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Fact signalling and fact nostalgia in the data-driven society
Post-truth tells the story of a public descending into unreason, aided and abetted by platforms and other data-driven systems. But this apparent collapse of epistemic consensus is, I argue, also dominated by loud and aggressive commitment to the idea of facts and Reason – a site where an imagined modern past is being pillaged for vestigial legitimacy. This article identifies two common practices of such reappropriation and mythologisation. (1) Fact signalling involves performative invocations of facts and Reason, which are then weaponised to discredit communicative rivals and establish affective solidarity. This is often closely tied to (2) fact nostalgia: the cultivation of an imagined past when ‘facts were facts’ and we, the good liberal subjects, could recognise facts when we saw them. Both tendencies are underwritten by a myth of connection: the still enduring narrative that maximising the circulation of information regardless of provenance or meaning will eventually yield a more rational public – even as data-driven systems tend to undermine the very conditions for such a public. Drawing on examples from YouTube-amplified ‘alternative influencers’ in the American right, and the normative discourses around fact-checking practices, I argue that this continued reliance on the vestigial authority of the modern past is a pernicious obstacle in normative debates around data-driven publics, keeping us stuck on the same dead-end scripts of heroically suspicious individuals and ignorant, irrational masses.
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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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