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A Social Network Analysis of Twitter Data Related to Blood Clots and Vaccines

Author

Listed:
  • Wasim Ahmed

    (Management School, University of Stirling, Stirling FK9 4LA, UK)

  • Josep Vidal-Alaball

    (Health Promotion in Rural Areas Research Group, Gerència Territorial de la Catalunya Central, Institut Català de la Salut, 08772 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, 08772 Sant Fruitós de Bages, Spain
    Faculty of Medicine, University of Vic-Central University of Catalonia, 08500 Vic, Spain)

  • Josep M. Vilaseca

    (Faculty of Medicine, University of Vic-Central University of Catalonia, 08500 Vic, Spain
    Primary Care Service, Althaia Xarxa Assistencial Universitària de Manresa, 08243 Manresa, Spain)

Abstract

After the first weeks of vaccination against SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. The data were retrieved from 14 March to 14 April 2021 using the keyword ‘blood clots’. A dataset with n = 266,677 tweets was retrieved, and a systematic random sample of 5% of tweets ( n = 13,334) was entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset–Newman–Moore algorithm. Influential users were identified by drawing upon the betweenness centrality measure. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network comprised retweets, and the largest groups within the network were broadcast clusters in which a number of key users were retweeted. The most popular narratives involved highlighting the low risk of obtaining a blood clot from a vaccine and highlighting that a number of commonly consumed medicine have higher blood clot risks. A wide variety of users drove the discussion on Twitter, including writers, physicians, the general public, academics, celebrities, and journalists. Twitter was used to highlight the low potential of developing a blood clot from vaccines, and users on Twitter encouraged vaccinations among the public.

Suggested Citation

  • Wasim Ahmed & Josep Vidal-Alaball & Josep M. Vilaseca, 2022. "A Social Network Analysis of Twitter Data Related to Blood Clots and Vaccines," IJERPH, MDPI, vol. 19(8), pages 1-8, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4584-:d:791100
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    Cited by:

    1. Patrick Cheong-Iao Pang & Wenjing Jiang & Guanwen Pu & Kin-Sun Chan & Ying Lau, 2022. "Social Media Engagement in Two Governmental Schemes during the COVID-19 Pandemic in Macao," IJERPH, MDPI, vol. 19(15), pages 1-12, July.
    2. Wasim Ahmed & Dilek Önkal & Ronnie Das & Satish Krishnan & Femi Olan & Mariann Hardey & Alex Fenton, 2023. "Developing Techniques to Support Technological Solutions to Disinformation by Analysing Four Conspiracy Networks During COVID-19," Post-Print hal-04692974, HAL.
    3. Carlos Ruiz-Núñez & Ivan Herrera-Peco & Silvia María Campos-Soler & Álvaro Carmona-Pestaña & Elvira Benítez de Gracia & Juan José Peña Deudero & Andrés Ignacio García-Notario, 2023. "Sentiment Analysis on Twitter: Role of Healthcare Professionals in the Global Conversation during the AstraZeneca Vaccine Suspension," IJERPH, MDPI, vol. 20(3), pages 1-13, January.
    4. W. Ahmed & D. Önkal & R. Das & S. Krishnan & F. Olan & M. Mariann Hardey & A. Alex Fenton, 2023. "Developing Techniques to Support Technological Solutions to Disinformation by Analysing Four Conspiracy Networks During COVID-19," Post-Print hal-04693779, HAL.

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