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

By Wasim Ahmed, Josep Vidal-Alaball, J. Downing, F. López Seguí. Journal of Medical Internet Research, 2020

568 citations recorded by the source corpus.

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.

Subfields: Communication, Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/c55424e723193df3991474c36f89a6e8ebdb1f78

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Citations in the corpus

The changes in the effects of social media use of Cypriots due to COVID-19 pandemic (2020, unknown): “[31] analyze COVID-19 and the 5G conspiracy theory on Twitter, and they outline that one fake profile formed the cluster with 408 Twitter users and posted 303 tweets before their closure by Twitter.”
High Rates of COVID-19 Vaccine Hesitancy and Its Association with Conspiracy Beliefs: A Study in Jordan and Kuwait among Other Arab Countries (2021, background): “Such claims without any evidence circulated on some social media platforms and can have a tremendous negative impact on the general public’s attitude towards the prospective vaccines [37,39,40].”
Social media and vaccine hesitancy: new updates for the era of COVID-19 and globalized infectious diseases (2020, background): “cies can have severe consequences, including the dissemination of theories linking 5 G cellular networks to the spread of COVID-19, which has led to vandalism of cellular towers.(47)”
The Truth is Out There: Investigating Conspiracy Theories in Text Generation (2021, background): “Previous conspiracy theory studies contain datasets that are either small in size (Oliver and Wood, 2014), contain non-English data (Bessi et al., 2015), or pertain to events occurring after the release of GPT-2 (Ahmed et al., 2020; Uscinski et al., 2020).”
Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach (2020, background): “Since the COVID-19 outbreak, a growing number of studies have collected Twitter data to understand the public responses to and discussions around COVID-19 [11-18].”