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Dependency, reciprocity, and informal mentorship in predicting long-term research collaboration: A co-authorship matrix-based multivariate time series analysis

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  • Zhu, Yongjun
  • Kim, Donghun
  • Jiang, Ting
  • Zhao, Yi
  • He, Jiangen
  • Chen, Xinyi
  • Lou, Wen

Abstract

In this study, we examine the roles of dependency, reciprocity, and informal mentorship in the prediction of long-term research collaboration in five disciplines. We use co-authorship matrix-based multivariate time series features and interpretable machine learning to train long-term collaboration prediction models and interpret the feature importance of trained models. Overall, long-term research collaboration that is defined using various standards was rare across the examined disciplines, and the prediction results were moderate to good. We found dependency, reciprocity, and informal mentorship to have different roles in different disciplines. Among the three, informal mentorship was important in predicting long-term research collaboration in Agriculture, Geology, and Library and Information Science. Reciprocity, which measures the interdependence between two researchers was important to prediction in the fields of Agriculture and Geology. Finally, dependency was important in all the disciplines with varying degrees of importance.

Suggested Citation

  • Zhu, Yongjun & Kim, Donghun & Jiang, Ting & Zhao, Yi & He, Jiangen & Chen, Xinyi & Lou, Wen, 2024. "Dependency, reciprocity, and informal mentorship in predicting long-term research collaboration: A co-authorship matrix-based multivariate time series analysis," Journal of Informetrics, Elsevier, vol. 18(1).
  • Handle: RePEc:eee:infome:v:18:y:2024:i:1:s1751157723001116
    DOI: 10.1016/j.joi.2023.101486
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    1. Blaise Cronin & Debora Shaw & Kathryn La Barre, 2003. "A cast of thousands: Coauthorship and subauthorship collaboration in the 20th century as manifested in the scholarly journal literature of psychology and philosophy," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(9), pages 855-871, July.
    2. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    3. Bedoor AlShebli & Kinga Makovi & Talal Rahwan, 2020. "RETRACTED ARTICLE: The association between early career informal mentorship in academic collaborations and junior author performance," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    4. Blaise Cronin & Debora Shaw & Kathryn La Barre, 2004. "Visible, less visible, and invisible work: Patterns of collaboration in 20th century chemistry," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 55(2), pages 160-168, January.
    5. Kiran Savanur & R. Srikanth, 2010. "Modified collaborative coefficient: a new measure for quantifying the degree of research collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 365-371, August.
    6. Hoekman, Jarno & Frenken, Koen & Tijssen, Robert J.W., 2010. "Research collaboration at a distance: Changing spatial patterns of scientific collaboration within Europe," Research Policy, Elsevier, vol. 39(5), pages 662-673, June.
    7. Ali Gazni & Mike Thelwall, 2014. "The long-term influence of collaboration on citation patterns," Research Evaluation, Oxford University Press, vol. 23(3), pages 261-271.
    8. Jonathan M. Levitt & Mike Thelwall, 2016. "Long term productivity and collaboration in information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1103-1117, September.
    9. Shen, Hongquan & Xie, Juan & Ao, Weiyi & Cheng, Ying, 2022. "The continuity and citation impact of scientific collaboration with different gender composition," Journal of Informetrics, Elsevier, vol. 16(1).
    10. Vincent Larivière & Yves Gingras & Cassidy R. Sugimoto & Andrew Tsou, 2015. "Team size matters: Collaboration and scientific impact since 1900," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(7), pages 1323-1332, July.
    11. Yi Bu & Ying Ding & Xingkun Liang & Dakota S. Murray, 2018. "Understanding persistent scientific collaboration," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(3), pages 438-448, March.
    12. Bedoor AlShebli & Kinga Makovi & Talal Rahwan, 2020. "Retraction Note: The association between early career informal mentorship in academic collaborations and junior author performance," Nature Communications, Nature, vol. 11(1), pages 1-1, December.
    13. Melin, Goran, 2000. "Pragmatism and self-organization: Research collaboration on the individual level," Research Policy, Elsevier, vol. 29(1), pages 31-40, January.
    14. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
    15. Barry Bozeman & Daniel Fay & Catherine Slade, 2013. "Research collaboration in universities and academic entrepreneurship: the-state-of-the-art," The Journal of Technology Transfer, Springer, vol. 38(1), pages 1-67, February.
    16. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2019. "The collaboration behavior of top scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 215-232, January.
    17. Yi Bu & Ying Ding & Jian Xu & Xingkun Liang & Gege Gao & Yiming Zhao, 2018. "Understanding success through the diversity of collaborators and the milestone of career," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(1), pages 87-97, January.
    18. Giovanni Abramo & Ciriaco D’Angelo & Flavia Di Costa & Marco Solazzi, 2011. "The role of information asymmetry in the market for university–industry research collaboration," The Journal of Technology Transfer, Springer, vol. 36(1), pages 84-100, February.
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