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回首往昔,展望未来:5G与新冠疫情阴谋论以及对基础设施的长期恐惧历史。

Looking back to look forward: 5G/COVID-19 conspiracies and the long history of infrastructural fears.

作者信息

Frith Jordan, Campbell Scott, Komen Leah

机构信息

Clemson University, USA.

University of Michigan, USA.

出版信息

Mob Media Commun. 2023 May;11(2):174-192. doi: 10.1177/20501579221133950. Epub 2022 Oct 22.

Abstract

Almost as soon as the COVID-19 pandemic began spreading throughout much of the world, conspiracies arose that blamed the virus on the deployment of fifth-generation cellular networks (5G) infrastructure. These conspiracies had significant consequences, including protests against 5G and the destruction of 5G infrastructure. This article uses a media genealogy approach to place the 5G/COVID-19 conspiracies within the long and recurring cycle of conspiracies focused on mobile infrastructure. Placed within that broader history, this article argues that the 5G/COVID-19 conspiracies should have been unsurprising, and these types of infrastructural conspiracies should be a more significant part of mobile media and communication (MMC) research because infrastructures are an often invisible, yet crucial, part of the mobile practices studied within MMC research. The article concludes by theorizing about why mobile infrastructures are such a frequent target for conspiracy theories and argues that researchers should begin planning now for combatting the conspiracies that will almost inevitably arise when the next generation of mobile infrastructure gets linked to fears about public health.

摘要

几乎在新冠疫情开始在世界大部分地区蔓延之际,就出现了将病毒归咎于第五代蜂窝网络(5G)基础设施部署的阴谋论。这些阴谋论产生了重大影响,包括针对5G的抗议活动以及对5G基础设施的破坏。本文采用媒体谱系学方法,将5G/新冠阴谋论置于围绕移动基础设施的长期且反复出现的阴谋论循环之中。置于这一更广泛的历史背景下,本文认为5G/新冠阴谋论本不应令人惊讶,而且这类基础设施阴谋论应成为移动媒体与通信(MMC)研究中更重要的一部分,因为基础设施是MMC研究中所探讨的移动实践中一个常常无形却至关重要的部分。文章最后对移动基础设施为何如此频繁地成为阴谋论目标进行了理论分析,并认为研究人员现在就应开始规划,以应对当下一代移动基础设施与公众健康担忧联系在一起时几乎不可避免会出现的阴谋论。

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引用本文的文献

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本文引用的文献

1
Unlink the Link Between COVID-19 and 5G Networks: An NLP and SNA Based Approach.
IEEE Access. 2020 Nov 18;8:209127-209137. doi: 10.1109/ACCESS.2020.3039168. eCollection 2020.
2
COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.
J Med Internet Res. 2020 May 6;22(5):e19458. doi: 10.2196/19458.
3
Magnetic fields exposure and childhood leukemia risk: a meta-analysis based on 11,699 cases and 13,194 controls.
Leuk Res. 2014 Mar;38(3):269-74. doi: 10.1016/j.leukres.2013.12.008. Epub 2013 Dec 15.
5
Review of the epidemiologic literature on EMF and Health.
Environ Health Perspect. 2001 Dec;109 Suppl 6(Suppl 6):911-33. doi: 10.1289/ehp.109-1240626.

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