A social network analysis published in the Journal of Medical Internet Research examined tweets discussing the COVID-19 and 5G conspiracy theory. The analysis found that while 35% of tweets about the conspiracy expressed support for the theory, 32% denounced the theory, unintentionally driving the topic into trending status.
In early January 2020, a theory linking the launch of the 5G mobile network to the emergence of COVID-19 took off on social media. The fifth generation global wireless network replaces the current 4G network and the theory posits that this new technology is responsible for COVID-19.
“The 5G and COVID-19 conspiracy theory became a trending topic on Twitter, which we saw and this initially sparked our interest in the subject,” explained study author Wasim Ahmed of Newcastle University Business School.
Despite a lack of scientific proof, the 5G conspiracy theory spread rapidly on social media and had serious consequences, leading to the burning of cell phone towers in various parts of Europe. These attacks on mobile towers are particularly concerning during a time when the population is so reliant on wireless connection. Ahmed and his team wanted to explore how the 5G conspiracy theory is being circulated on social media, whether users truly believe in the conspiracy, and what actions might be taken by public health to prevent its propagation.
A social network analysis examined Twitter data containing the keyword “5Gcoronavirus” or using the hashtag #5GCoronavirus, during a 7-day period when the topic was trending in the United Kingdom, from March 27, 2020, to April 4, 2020. The analysis included a total of 10,140 tweets from 6,556 Twitter users.
User analysis identified ten accounts deemed the most influential, based on what researchers call “betweenness centrality.” The term measures the extent that a node within a social network bridges connections between other users. A higher score suggests a user has a higher influence within a network since they have indirect control over the sharing of information between users.
The majority of these influential users were regular citizens whose accounts showed a tendency for sharing conspiracy theories. The fifth most influential user was an account under the name “5gcoronavirus19” that was being expressly used to spread the 5G conspiracy theory and had published 303 tweets during the time of the study, before being shut down by Twitter. The account was part of a “cluster” in the network which included 408 other Twitter accounts.
Researchers also conducted a manual analysis on a sample of 10% of the 5G coronavirus tweets. It was found that 35% of the tweets expressed support for the link between the 5G network and COVID-19, suggesting that a fair number of people did believe in the accuracy of the conspiracy. However, 33% of tweets were absent of any personal opinion and 32% were actively denouncing the conspiracy theory.
Given that nearly as many tweets were against the 5G conspiracy as were in support of it, the authors point out that those who tweeted against the theory were unknowingly adding fuel to the discussion and driving the topic into trending status. As the researchers say, “when users joined the discussion to dispel, ridicule, or piggyback on the hashtag, the topic was raised to new heights and had increased visibility.”
Ahmed told PsyPost that he hopes the findings highlight “that one of the best ways to fight COVID-19 misinformation on Twitter (or other social platforms) is to report the content rather than share and/or engage with it.”
The researchers suggest that public health authorities should advise the public against engaging with false information and direct users to instead report these posts to the respective social media companies. They further suggest that policymakers should increase efforts to shut down propaganda accounts that spread such misinformation.
“Our focus was on a single conspiracy theory. Our future work intends to examine other conspiracy theories shared around COVID-19,” Ahmed said.
The study, “COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data”, was authored by Wasim Ahmed, Josep Vidal-Alaball, Joseph Downing, and Francesc López Seguí.