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COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.
J Med Internet Res. 2020 05 06; 22(5):e19458.JM

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.

Authors+Show Affiliations

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. 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.London School of Economics, European Institute, London, United Kingdom.TIC Salut Social, Generalitat de Catalunya, Barcelona, Spain. CRES & CEXS, Universitat Pompeu Fabra, Barcelona, Spain.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32352383

Citation

Ahmed, Wasim, et al. "COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data." Journal of Medical Internet Research, vol. 22, no. 5, 2020, pp. e19458.
Ahmed W, Vidal-Alaball J, Downing J, et al. COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data. J Med Internet Res. 2020;22(5):e19458.
Ahmed, W., Vidal-Alaball, J., Downing, J., & López Seguí, F. (2020). COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data. Journal of Medical Internet Research, 22(5), e19458. https://doi.org/10.2196/19458
Ahmed W, et al. COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data. J Med Internet Res. 2020 05 6;22(5):e19458. PubMed PMID: 32352383.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data. AU - Ahmed,Wasim, AU - Vidal-Alaball,Josep, AU - Downing,Joseph, AU - López Seguí,Francesc, Y1 - 2020/05/06/ PY - 2020/04/18/received PY - 2020/04/25/accepted PY - 2020/04/22/revised PY - 2020/5/1/pubmed PY - 2020/5/19/medline PY - 2020/5/1/entrez KW - 5G KW - COVID-19 KW - coronavirus KW - fake news KW - misinformation KW - pandemic KW - public health KW - social media KW - social network analysis KW - twitter SP - e19458 EP - e19458 JF - Journal of medical Internet research JO - J Med Internet Res VL - 22 IS - 5 N2 - 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. SN - 1438-8871 UR - https://news.unboundmedicine.com/medline/citation/32352383/COVID_19_and_the_5G_Conspiracy_Theory:_Social_Network_Analysis_of_Twitter_Data_ L2 - https://www.jmir.org/2020/5/e19458/ DB - PRIME DP - Unbound Medicine ER -