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Understanding and predicting future research impact at different career stages—A social network perspective

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  • Zhiya Zuo
  • Kang Zhao

Abstract

Performance assessment is ubiquitous and crucial in people analytics. Scientific impact, particularly, plays a significant role in the academia. This paper attempts to understand researchers' career trajectories by considering the research community as a social network, where individuals build ties with each other via coauthorship. The resulting linkage facilitates information flow and affects researchers' future impact. Consequently, we systematically investigate the career trajectories of researchers with respect to research impact using the social capital theory as our theoretical foundation. Specifically, for early‐stage and mid‐career academics, we find that connections with prominent researchers associate with greater impact. Brokerage positions, in addition, are beneficial to a researcher's research impact in the long run. For senior researchers, however, the only social network feature that significantly affects their future impact is the reputation of their recently built ties. Finally, we build predictive models on future research impact which can be leveraged by both organizations and individuals. This paper provides empirical evidence for how social networks provide signals on researchers' career dynamics guided by social capital theory. Our findings have implications for individual researchers to strategically plan and promote their careers and for research institutions to better evaluate current as well as prospective employees.

Suggested Citation

  • Zhiya Zuo & Kang Zhao, 2021. "Understanding and predicting future research impact at different career stages—A social network perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 454-472, April.
  • Handle: RePEc:bla:jinfst:v:72:y:2021:i:4:p:454-472
    DOI: 10.1002/asi.24415
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    as
    1. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. Cao, Xuanyu & Chen, Yan & Ray Liu, K.J., 2016. "A data analytic approach to quantifying scientific impact," Journal of Informetrics, Elsevier, vol. 10(2), pages 471-484.
    3. Zuo, Zhiya & Zhao, Kang, 2018. "The more multidisciplinary the better? – The prevalence and interdisciplinarity of research collaborations in multidisciplinary institutions," Journal of Informetrics, Elsevier, vol. 12(3), pages 736-756.
    4. Susan Washburn Taylor & Blakely Fox Fender & Kimberly Gladden Burke, 2006. "Unraveling the Academic Productivity of Economists: The Opportunity Costs of Teaching and Service," Southern Economic Journal, John Wiley & Sons, vol. 72(4), pages 846-859, April.
    5. Stefan Hornbostel & Susan Böhmer & Bernd Klingsporn & Jörg Neufeld & Markus Ins, 2009. "Funding of young scientist and scientific excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(1), pages 171-190, April.
    6. Lutz Bornmann & Alexander Tekles, 2019. "Productivity does not equal usefulness," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 705-707, February.
    7. Anthony F. J. van Raan, 2004. "Sleeping Beauties in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 467-472, March.
    8. Li, Eldon Y. & Liao, Chien Hsiang & Yen, Hsiuju Rebecca, 2013. "Co-authorship networks and research impact: A social capital perspective," Research Policy, Elsevier, vol. 42(9), pages 1515-1530.
    9. Marc Bertin & Iana Atanassova & Cassidy R. Sugimoto & Vincent Lariviere, 2016. "The linguistic patterns and rhetorical structure of citation context: an approach using n-grams," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1417-1434, December.
    10. van Rijnsoever, Frank J. & Hessels, Laurens K., 2011. "Factors associated with disciplinary and interdisciplinary research collaboration," Research Policy, Elsevier, vol. 40(3), pages 463-472, April.
    11. Tian Yu & Guang Yu & Peng-Yu Li & Liang Wang, 2014. "Citation impact prediction for scientific papers using stepwise regression analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1233-1252, November.
    12. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
    13. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
    14. Yves Gingras & Vincent Larivière & Benoît Macaluso & Jean-Pierre Robitaille, 2008. "The Effects of Aging on Researchers' Publication and Citation Patterns," PLOS ONE, Public Library of Science, vol. 3(12), pages 1-8, December.
    15. Mario Biagioli, 2016. "Watch out for cheats in citation game," Nature, Nature, vol. 535(7611), pages 201-201, July.
    16. Jian Wang, 2013. "Citation time window choice for research impact evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 851-872, March.
    17. Zuo, Zhiya & Zhao, Kang & Ni, Chaoqun, 2019. "Standing on the shoulders of giants?—Faculty hiring in information schools," Journal of Informetrics, Elsevier, vol. 13(1), pages 341-353.
    18. Zhiya Zuo & Kang Zhao & David Eichmann, 2017. "The state and evolution of U.S. iSchools: From talent acquisitions to research outcome," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(5), pages 1266-1277, May.
    19. Lindell Bromham & Russell Dinnage & Xia Hua, 2016. "Interdisciplinary research has consistently lower funding success," Nature, Nature, vol. 534(7609), pages 684-687, June.
    20. Amin Mazloumian, 2012. "Predicting Scholars' Scientific Impact," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-5, November.
    21. Radicchi, Filippo & Weissman, Alexander & Bollen, Johan, 2017. "Quantifying perceived impact of scientific publications," Journal of Informetrics, Elsevier, vol. 11(3), pages 704-712.
    22. Strathern, Marilyn, 1997. "‘Improving ratings’: audit in the British University system," European Review, Cambridge University Press, vol. 5(3), pages 305-321, July.
    23. Mikko Packalen & Jay Bhattacharya, 2015. "Age and the Trying Out of New Ideas," NBER Working Papers 20920, National Bureau of Economic Research, Inc.
    24. Lutz Bornmann & Hans-Dieter Daniel, 2006. "Selecting scientific excellence through committee peer review - A citation analysis of publications previously published to approval or rejection of post-doctoral research fellowship applicants," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 427-440, September.
    25. ., 2017. "Standing on the shoulders of giants," Chapters, in: Endogenous Innovation, chapter 1, pages 3-24, Edward Elgar Publishing.
    26. Mikko Packalen & Jay Bhattacharya, 2019. "Age and the Trying Out of New Ideas," Journal of Human Capital, University of Chicago Press, vol. 13(2), pages 341-373.
    27. Kaur, Jasleen & Ferrara, Emilio & Menczer, Filippo & Flammini, Alessandro & Radicchi, Filippo, 2015. "Quality versus quantity in scientific impact," Journal of Informetrics, Elsevier, vol. 9(4), pages 800-808.
    28. Amjad, Tehmina & Ding, Ying & Xu, Jian & Zhang, Chenwei & Daud, Ali & Tang, Jie & Song, Min, 2017. "Standing on the shoulders of giants," Journal of Informetrics, Elsevier, vol. 11(1), pages 307-323.
    29. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
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    Cited by:

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    4. Orzechowski, Kamil P. & Mrowinski, Maciej J. & Fronczak, Agata & Fronczak, Piotr, 2023. "Asymmetry of social interactions and its role in link predictability: The case of coauthorship networks," Journal of Informetrics, Elsevier, vol. 17(2).
    5. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.

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