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“Heterogeneous couplings”: Operationalizing network perspectives to study science‐society interactions through social media metrics

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  • Rodrigo Costas
  • Sarah de Rijcke
  • Noortje Marres

Abstract

Social media metrics have a genuine networked nature, reflecting the networking characteristics of the social media platform from where they are derived. This networked nature has been relatively less explored in the literature on altmetrics, although new network‐level approaches are starting to appear. A general conceptualization of the role of social media networks in science communication, and particularly of social media as a specific type of interface between science and society, is still missing. The aim of this paper is to provide a conceptual framework for appraising interactions between science and society in multiple directions, in what we call heterogeneous couplings. Heterogeneous couplings are conceptualized as the co‐occurrence of science and non‐science objects, actors, and interactions in online media environments. This conceptualization provides a common framework to study the interactions between science and non‐science actors as captured via online and social media platforms. The conceptualization of heterogeneous couplings opens wider opportunities for the development of network applications and analyses of the interactions between societal and scholarly entities in social media environments, paving the way toward more advanced forms of altmetrics, social (media) studies of science, and the conceptualization and operationalization of more advanced science‐society studies.

Suggested Citation

  • Rodrigo Costas & Sarah de Rijcke & Noortje Marres, 2021. "“Heterogeneous couplings”: Operationalizing network perspectives to study science‐society interactions through social media metrics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(5), pages 595-610, May.
  • Handle: RePEc:bla:jinfst:v:72:y:2021:i:5:p:595-610
    DOI: 10.1002/asi.24427
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    Cited by:

    1. Enrique Orduña-Malea & Cristina I. Font-Julián, 2022. "Are patents linked on Twitter? A case study of Google patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6339-6362, November.
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    3. Ting Cong & Zhichao Fang & Rodrigo Costas, 2022. "WeChat uptake of chinese scholarly journals: an analysis of CSSCI-indexed journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7091-7110, December.

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