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The stability of co-authorship structures

Author

Listed:
  • Marjan Cugmas

    (University of Ljubljana)

  • Anuška Ferligoj

    (University of Ljubljana)

  • Luka Kronegger

    (University of Ljubljana)

Abstract

This article examines the structure of co-authorship networks’ stability in time. The goal of the article is to analyse differences in the stability and size of groups of researchers that co-author with each other (core research groups) formed in disciplines from the natural and technical sciences on one hand and the social sciences and humanities on the other. The cores were obtained by a pre-specified blockmodeling procedure assuming a multi-core–semi-periphery–periphery structure. The stability of the obtained cores was measured with the Modified Adjusted Rand Index. The assumed structure was confirmed in all analysed disciplines. The average size of the cores obtained is higher in the second time period and the average core size is greater in the natural and technical sciences than in the social sciences and humanities. There are no differences in average core stability between the natural and technical sciences and the social sciences and humanities. However, if the stability of cores is defined by the splitting of cores and not also by the percentage of researchers who left the cores, the average stability of the cores is higher in disciplines from the scientific fields of Engineering sciences and technologies and Medical sciences than in disciplines of the Humanities, if controlling for the networks’ and disciplines’ characteristics. The analysis was performed on disciplinary co-authorship networks of Slovenian researchers in two time periods (1991–2000 and 2001–2010).

Suggested Citation

  • Marjan Cugmas & Anuška Ferligoj & Luka Kronegger, 2016. "The stability of co-authorship structures," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 163-186, January.
  • Handle: RePEc:spr:scient:v:106:y:2016:i:1:d:10.1007_s11192-015-1790-4
    DOI: 10.1007/s11192-015-1790-4
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    References listed on IDEAS

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    Cited by:

    1. Jie Zheng & Jianya Gong & Rui Li & Kai Hu & Huayi Wu & Siluo Yang, 2017. "Community evolution analysis based on co-author network: a case study of academic communities of the journal of “Annals of the Association of American Geographers”," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 845-865, November.
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    3. Fabio Ashtar Telarico & Franc Mali & Aleš Žiberna, 2024. "Revealing dynamic co-authorship structure in the social sciences through blockmodeling: the Slovenian case (1991–2020)," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5635-5672, September.
    4. Matjašič, Miha & Cugmas, Marjan & Žiberna, Aleš, 2021. "blockmodeling: an R package for Generalized Blockmodeling," SocArXiv b8cxp, Center for Open Science.
    5. Noémi Gaskó & Rodica Ioana Lung & Mihai Alexandru Suciu, 2016. "A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 613-632, August.
    6. Marjan Cugmas & Franc Mali & Aleš Žiberna, 2020. "Scientific collaboration of researchers and organizations: a two-level blockmodeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2471-2489, December.
    7. Zewen Hu & Angela Lin & Peter Willett, 2019. "Identification of research communities in cited and uncited publications using a co-authorship network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 1-19, January.

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