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Tytuł pozycji:

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

Tytuł:
COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.
Autorzy:
Ahmed W; Newcastle University, Newcastle upon Tyne, United Kingdom.
Vidal-Alaball J; Health Promotion in Rural Areas Research Group, Gerència Territorial de la Catalunya Central, Institut Català de la Salut, Sant Fruitós de Bages, Spain.; Unitat de Suport a la Recerca de la Catalunya Central, Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina, Sant Fruitós de Bages, Spain.
Downing J; London School of Economics, European Institute, London, United Kingdom.
López Seguí F; TIC Salut Social, Generalitat de Catalunya, Barcelona, Spain.; CRES & CEXS, Universitat Pompeu Fabra, Barcelona, Spain.
Źródło:
Journal of medical Internet research [J Med Internet Res] 2020 May 06; Vol. 22 (5), pp. e19458. Date of Electronic Publication: 2020 May 06.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Publication: <2011- > : Toronto : JMIR Publications
Original Publication: [Pittsburgh, PA? : s.n., 1999-
MeSH Terms:
Betacoronavirus*
Communication*
Public Opinion*
Coronavirus Infections/*epidemiology
Fraud/*prevention & control
Fraud/*statistics & numerical data
Pneumonia, Viral/*epidemiology
Social Media/*statistics & numerical data
COVID-19 ; Coronavirus Infections/virology ; Humans ; Pandemics ; Pneumonia, Viral/virology ; Public Health/methods ; SARS-CoV-2 ; Social Networking ; Truth Disclosure ; United Kingdom/epidemiology
References:
PLoS One. 2010 Nov 29;5(11):e14118. (PMID: 21124761)
JMIR Public Health Surveill. 2020 Apr 21;6(2):e18700. (PMID: 32293582)
Int J Surg. 2020 Apr;76:71-76. (PMID: 32112977)
JAMA. 2020 Mar 17;:. (PMID: 32181795)
J Med Internet Res. 2016 Aug 09;18(8):e219. (PMID: 27507563)
Soc Sci Med. 2006 Dec;63(12):3113-23. (PMID: 16978751)
Int J Environ Res Public Health. 2020 Mar 26;17(7):. (PMID: 32225020)
Public Health. 2018 Oct;163:35-41. (PMID: 30059806)
Nature. 2020 Mar;579(7798):265-269. (PMID: 32015508)
Contributed Indexing:
Keywords: 5G; COVID-19; coronavirus; fake news; misinformation; pandemic; public health; social media; social network analysis; twitter
Entry Date(s):
Date Created: 20200501 Date Completed: 20200512 Latest Revision: 20201218
Update Code:
20240105
PubMed Central ID:
PMC7205032
DOI:
10.2196/19458
PMID:
32352383
Czasopismo naukowe
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.
(©Wasim Ahmed, Josep Vidal-Alaball, Joseph Downing, Francesc López Seguí. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.05.2020.)
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