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Identifying prize-winning scientists by a competition-aware ranking

Author

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  • Zhou, Yuhao
  • Wang, Ruijie
  • Zeng, An
  • Zhang, Yi-Cheng

Abstract

Evaluating scholars’ achievements is an important problem in the science of science with applications in the evaluation of grant proposals and promotion applications. Since the number of scholars and the number of scholarly outputs grow exponentially with time, well-designed ranking metrics that have the potential to assist in these tasks are of prime importance. To rank scholars, it is important to put their achievements in perspective by comparing them with the achievements of other scholars active in the same period. We propose here a particular way of doing so: by computing the evaluated scholar's share on each year's citations which quantifies how the scholar fares in competition with the others. We assess the resulting ranking method using the American Physical Society citation data and four prestigious physics awards. Our results show that the new method significantly outperforms other ranking methods in identifying the prize laureates.

Suggested Citation

  • Zhou, Yuhao & Wang, Ruijie & Zeng, An & Zhang, Yi-Cheng, 2020. "Identifying prize-winning scientists by a competition-aware ranking," Journal of Informetrics, Elsevier, vol. 14(3).
    • Handle: RePEc:eee:infome:v:14:y:2020:i:3:s1751157719304766
    DOI: 10.1016/j.joi.2020.101038
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    Cited by:

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    7. Jingda Ding & Yifan Chen & Chao Liu, 2023. "Exploring the research features of Nobel laureates in Physics based on the semantic similarity measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5247-5275, September.
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    9. Bilal Barış Alkan & Leyla Karakuş & Bekir Direkci, 2023. "Knowledge discovery from the texts of Nobel Prize winners in literature: sentiment analysis and Latent Dirichlet Allocation," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5311-5334, September.

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