Twitter&apos;s Role in Combating the Magnetic Vaccine Conspiracy Theory: Social Network Analysis of Tweets

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Abstract

Background

The popularity of the magnetic vaccine conspiracy theory and other conspiracy theories of a similar nature creates challenges to promoting vaccines and disseminating accurate health information.

Objective

Health conspiracy theories are gaining in popularity. This study's objective was to evaluate the Twitter social media network related to the magnetic vaccine conspiracy theory and apply social capital theory to analyze the unique social structures of influential users. As a strategy for web-based public health surveillance, we conducted a social network analysis to identify the important opinion leaders sharing the conspiracy, the key websites, and the narratives.

Methods

A total of 18,706 tweets were retrieved and analyzed by using social network analysis. Data were retrieved from June 1 to June 13, 2021, using the keyword vaccine magnetic. Tweets were retrieved via a dedicated Twitter application programming interface. More specifically, the Academic Track application programming interface was used, and the data were analyzed by using NodeXL Pro (Social Media Research Foundation) and Gephi.

Results

There were a total of 22,762 connections between Twitter users within the data set. This study found that the most influential user within the network consisted of a news account that was reporting on the magnetic vaccine conspiracy. There were also several other users that became influential, such as an epidemiologist, a health economist, and a retired sports athlete who exerted their social capital within the network.

Conclusions

Our study found that influential users were effective broadcasters against the conspiracy, and their reach extended beyond their own networks of Twitter followers. We emphasize the need for trust in influential users with regard to health information, particularly in the context of the widespread social uncertainty resulting from the COVID-19 pandemic, when public sentiment on social media may be unpredictable. This study highlights the potential of influential users to disrupt information flows of conspiracy theories via their unique social capital.

Related collections

Most cited references 46

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Using social and behavioural science to support COVID-19 pandemic response

Jay Bavel, Katherine Baicker, Paulo S Boggio … (2020)

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

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Finding community structure in very large networks

Aaron Clauset, M. Newman, Cristopher Moore (2004)

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Conspiracy theories as barriers to controlling the spread of COVID-19 in the U.S.

Daniel Romer, Kathleen Jamieson (2020)

Rationale The COVID-19 pandemic poses extraordinary challenges to public health. Objective Because the novel coronavirus is highly contagious, the widespread use of preventive measures such as masking, physical distancing, and eventually vaccination is needed to bring it under control. We hypothesized that accepting conspiracy theories that were circulating in mainstream and social media early in the COVID-19 pandemic in the US would be negatively related to the uptake of preventive behaviors and also of vaccination when a vaccine becomes available. Method A national probability survey of US adults (N = 1050) was conducted in the latter half of March 2020 and a follow-up with 840 of the same individuals in July 2020. The surveys assessed adoption of preventive measures recommended by public health authorities, vaccination intentions, conspiracy beliefs, perceptions of threat, belief about the safety of vaccines, political ideology, and media exposure patterns. Results Belief in three COVID-19-related conspiracy theories was highly stable across the two periods and inversely related to the (a) perceived threat of the pandemic, (b) taking of preventive actions, including wearing a face mask, (c) perceived safety of vaccination, and (d) intention to be vaccinated against COVID-19. Conspiracy beliefs in March predicted subsequent mask-wearing and vaccination intentions in July even after controlling for action taken and intentions in March. Although adopting preventive behaviors was predicted by political ideology and conservative media reliance, vaccination intentions were less related to political ideology. Mainstream television news use predicted adopting both preventive actions and vaccination. Conclusions Because belief in COVID-related conspiracy theories predicts resistance to both preventive behaviors and future vaccination for the virus, it will be critical to confront both conspiracy theories and vaccination misinformation to prevent further spread of the virus in the US. Reducing those barriers will require continued messaging by public health authorities on mainstream media and in particular on politically conservative outlets that have supported COVID-related conspiracy theories.

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Author and article information

Contributors

Josep Vidal-Alaball:

ORCID: https://orcid.org/0000-0002-3527-4242

Unitat de Suport a la Recerca de la Catalunya CentralFundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i GurinaC/ Pica d'Estats 13-15Sant Fruitós de Bages, 08272Spain34 93 693 0040jvidal.cc.ics@gencat.cat

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J Med Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: 2023

Publication date (Electronic): 31 March 2023

Publication date PMC-release: 31 March 2023

Volume: 25

Electronic Location Identifier: e43497

Affiliations

[1 ] Management School Stirling University Stirling United Kingdom

[2 ] Department of Marketing Audencia Business School Nantes France

[3 ] 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

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

[5 ] Faculty of Medicine University of Vic-Central University of Catalonia Vic Spain

[6 ] Business School Durham University Durham United Kingdom

Author notes

Corresponding Author: Josep Vidal-Alaball jvidal.cc.ics@ 123456gencat.cat

Author information

Wasim Ahmed https://orcid.org/0000-0001-8923-1865

Ronnie Das https://orcid.org/0000-0003-3623-5859

Josep Vidal-Alaball https://orcid.org/0000-0002-3527-4242

Mariann Hardey https://orcid.org/0000-0002-1027-0165

Aïna Fuster-Casanovas https://orcid.org/0000-0001-9128-9580

Article

Publisher ID: v25i1e43497

DOI: 10.2196/43497

PMC ID: 10131940

PubMed ID: 36927550

SO-VID: c548dcac-e88e-422e-b074-1a6996993cda

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 13 October 2022

Date revision requested : 14 December 2022

Date revision received : 18 December 2022

Date accepted : 10 March 2023

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