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Communities of shared interests and cognitive bridges: the case of the anti-vaccination movement on Twitter

Author

Listed:
  • Francois Schalkwyk

    (Stellenbosch University)

  • Jonathan Dudek

    (Leiden University)

  • Rodrigo Costas

    (Leiden University
    Stellenbosch University)

Abstract

This paper presents an analysis of the anti-vaccination movement’s referencing of research articles on the topic of vaccination in the social media network Twitter. Drawing on the concept of bibliographic coupling, the paper demonstrates how Twitter users can be coupled based on articles mentioned on Twitter. The sample applied consists of 113 open access journal articles. The combination of tweeter coupling with the respective stance of Twitter accounts vis-à-vis vaccination makes possible the creation of a network graph of tweeters mentioning this corpus of articles. In addition to a common interest in the scientific literature, the findings show distinct communities of shared interests within the anti-vaccination movement, and demonstrate that tweeter coupling can be used to map these distinctive interests. The emergence of Twitter accounts serving as cognitive bridges within and between communities is noted and discussed with regard to their relative positions in the network. This paper’s results extend the knowledge on the application of altmetric data to study the interests of non-scientific publics in science; more specifically, it adds to the understanding of the potentials of open science and science–society interactions arising from increased access by non-scientists to scientific publications.

Suggested Citation

  • Francois Schalkwyk & Jonathan Dudek & Rodrigo Costas, 2020. "Communities of shared interests and cognitive bridges: the case of the anti-vaccination movement on Twitter," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1499-1516, November.
  • Handle: RePEc:spr:scient:v:125:y:2020:i:2:d:10.1007_s11192-020-03551-0
    DOI: 10.1007/s11192-020-03551-0
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    1. Blaise Cronin & Herbert W. Snyder & Howard Rosenbaum & Anna Martinson & Ewa Callahan, 1998. "Invoked on the Web," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(14), pages 1319-1328.
    2. José van Dijck & Thomas Poell, 2013. "Understanding Social Media Logic," Media and Communication, Cogitatio Press, vol. 1(1), pages 2-14.
    3. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    4. Cassidy R. Sugimoto & Sam Work & Vincent Larivière & Stefanie Haustein, 2017. "Scholarly use of social media and altmetrics: A review of the literature," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(9), pages 2037-2062, September.
    5. Julia Vainio & Kim Holmberg, 2017. "Highly tweeted science articles: who tweets them? An analysis of Twitter user profile descriptions," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 345-366, July.
    6. Dangzhi Zhao & Andreas Strotmann, 2008. "Evolution of research activities and intellectual influences in information science 1996–2005: Introducing author bibliographic‐coupling analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(13), pages 2070-2086, November.
    7. Didegah, Fereshteh & Mejlgaard, Niels & Sørensen, Mads P., 2018. "Investigating the quality of interactions and public engagement around scientific papers on Twitter," Journal of Informetrics, Elsevier, vol. 12(3), pages 960-971.
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    Cited by:

    1. Yingxin Estella Ye & Jin-Cheon Na & Poong Oh, 2022. "Are automated accounts driving scholarly communication on Twitter? a case study of dissemination of COVID-19 publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2151-2172, May.
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    3. Zhichao Fang & Rodrigo Costas & Wencan Tian & Xianwen Wang & Paul Wouters, 2021. "How is science clicked on Twitter? Click metrics for Bitly short links to scientific publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(7), pages 918-932, July.

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