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Collaboration in computer science: A network science approach

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  • Massimo Franceschet

Abstract

Co‐authorship in publications within a discipline uncovers interesting properties of the analyzed field. We represent collaboration in academic papers of computer science in terms of differently grained networks, namely affiliation and collaboration networks. We also build those sub‐networks that emerge from either conference or journal co‐authorship only. We take advantage of the network science paraphernalia to take a picture of computer science collaboration including all papers published in the field since 1936. Furthermore, we observe how collaboration in computer science evolved over time since 1960. We investigate bibliometric properties such as size of the discipline, productivity of scholars, and collaboration level in papers, as well as global network properties such as reachability and average separation distance among scholars, distribution of the number of scholar collaborators, network resilience and dependence on star collaborators, network clustering, and network assortativity by number of collaborators.

Suggested Citation

  • Massimo Franceschet, 2011. "Collaboration in computer science: A network science approach," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1992-2012, October.
  • Handle: RePEc:bla:jamist:v:62:y:2011:i:10:p:1992-2012
    DOI: 10.1002/asi.21614
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    File URL: https://doi.org/10.1002/asi.21614
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    Cited by:

    1. Šubelj, Lovro & Fiala, Dalibor & Ciglarič, Tadej & Kronegger, Luka, 2019. "Convexity in scientific collaboration networks," Journal of Informetrics, Elsevier, vol. 13(1), pages 10-31.
    2. Xuan Shi & Lingfei Cai & Junzhi Jia, 2018. "The Evolution of International Scientific Collaboration in Fuel Cells during 1998–2017: A Social Network Perspective," Sustainability, MDPI, Open Access Journal, vol. 10(12), pages 1-20, December.
    3. Lipeng Fan & Yuefen Wang & Shengchun Ding & Binbin Qi, 2020. "Productivity trends and citation impact of different institutional collaboration patterns at the research units’ level," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1179-1196, November.
    4. 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.
    5. Lipeng Fan & Yuefen Wang & Shengchun Ding & Binbin Qi, 0. "Productivity trends and citation impact of different institutional collaboration patterns at the research units’ level," Scientometrics, Springer;Akadémiai Kiadó, vol. 0, pages 1-18.

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