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新冠疫情与5G阴谋论:基于推特数据的社交网络分析

COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.

作者信息

Ahmed Wasim, Vidal-Alaball Josep, Downing Joseph, López Seguí Francesc

机构信息

Newcastle University, Newcastle upon Tyne, United Kingdom.

Health Promotion in Rural Areas Research Group, Gerència Territorial de la Catalunya Central, Institut Català de la Salut, Sant Fruitós de Bages, Spain.

出版信息

J Med Internet Res. 2020 May 6;22(5):e19458. doi: 10.2196/19458.

DOI:10.2196/19458
PMID:32352383
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7205032/
Abstract

BACKGROUND

Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it.

OBJECTIVE

The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation.

METHODS

This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph's vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined.

RESULTS

Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter.

CONCLUSIONS

The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36ab/7205032/3ce2319322f7/jmir_v22i5e19458_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36ab/7205032/3ce2319322f7/jmir_v22i5e19458_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36ab/7205032/3ce2319322f7/jmir_v22i5e19458_fig1.jpg
摘要

背景

自2019年12月初以来,冠状病毒病(COVID-19)在全球迅速传播,这引发了在线平台上越来越多的讨论。这些对话还包括社交媒体用户分享的各种阴谋论。其中,一个流行的理论将5G与COVID-19的传播联系起来,导致了错误信息的传播以及英国5G基站被烧毁。了解虚假新闻的驱动因素以及针对隔离和反驳错误信息的快速政策是打击虚假新闻的关键。

目的

本研究的目的是了解5G与COVID-19阴谋论的驱动因素以及应对此类错误信息的策略。

方法

本文对2020年3月27日星期五至2020年4月4日星期六这7天期间英国推特上#5G冠状病毒#标签趋势的推特数据进行了社会网络分析和内容分析。通过社会网络图聚类分析有影响力的用户。节点大小根据其介数中心性得分进行排名,图的顶点使用克劳塞特-纽曼-摩尔算法按聚类进行分组。还检查了所使用的主题和网络来源。

结果

社会网络分析发现,两个最大的网络结构由一个孤立群体和一个传播群体组成。分析还表明,缺乏一个积极打击此类错误信息的权威人物。内容分析显示,在233条样本推文中,34.8%(n = 81)包含5G与COVID-19有关联的观点,32.2%(n = 75)谴责了该阴谋论,33.0%(n = 77)是不表达任何个人观点或意见的普通推文。因此,65.2%(n = 152)的推文来自非阴谋论支持者,这表明尽管该话题吸引了大量关注,但只有少数用户真正相信这个阴谋论。本文还表明,虚假新闻网站是用户分享最多的网络来源;不过,YouTube视频也有被分享。该研究还识别出一个在推特上专门传播该阴谋论的账号。

结论

采取快速且有针对性的干预措施以使虚假信息来源失去合法性,是减少其影响的关键。那些表达反对阴谋论观点、链接诱饵或分享幽默推文的用户无意中提高了该话题的关注度,这表明政策制定者应坚持努力隔离基于虚假新闻的观点。许多社交媒体平台为用户提供了举报不当内容的功能,应该加以利用。本研究首次在推特上COVID-19背景下分析5G阴谋论,为卫生当局在大流行背景下未来如何打击谣言提供了实际指导。

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