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Identifying prize-winning scientists by a competition-aware ranking

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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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    References listed on IDEAS

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    Cited by:

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    3. Zhu, Wanying & Jin, Ching & Ma, Yifang & Xu, Cong, 2023. "Earlier recognition of scientific excellence enhances future achievements and promotes persistence," Journal of Informetrics, Elsevier, vol. 17(2).
    4. Zhao, Zhi-Dan & Chen, Jiahao & Lu, Yichuan & Zhao, Na & Jiang, Dazhi & Wang, Bing-Hong, 2021. "Dynamic patterns of open review process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    5. Yanbo Zhou & Xin-Li Xu & Xu-Hua Yang & Qu Li, 2022. "The influence of disruption on evaluating the scientific significance of papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5931-5945, October.
    6. 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.
    7. Yuhao Zhou & Ruijie Wang & An Zeng, 2022. "Predicting the impact and publication date of individual scientists’ future papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1867-1882, April.
    8. 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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