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Discoverers in scientific citation data

Author

Listed:
  • Shi, Gui-Yuan
  • Kong, Yi-Xiu
  • Yuan, Guang-Hui
  • Wu, Rui-Jie
  • Zeng, An
  • Medo, Matúš

Abstract

Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to the citation network setting, and show that there are authors who frequently cite recent papers that become highly-cited in the future; these authors are referred to as discoverers. We develop a method for early identification of highly-cited papers based on the early citations from discoverers. The results show that the identified discoverers have a consistent citing pattern over time, and the early citations from them can be used as a valuable indicator to predict the future citation counts of a paper. The discoverers themselves are potential future outstanding researchers as they receive more citations than average.

Suggested Citation

  • Shi, Gui-Yuan & Kong, Yi-Xiu & Yuan, Guang-Hui & Wu, Rui-Jie & Zeng, An & Medo, Matúš, 2019. "Discoverers in scientific citation data," Journal of Informetrics, Elsevier, vol. 13(2), pages 717-725.
    • Handle: RePEc:eee:infome:v:13:y:2019:i:2:p:717-725
    DOI: 10.1016/j.joi.2019.03.017
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    Cited by:

    1. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    2. Feng Hu & Lin Ma & Xiu-Xiu Zhan & Yinzuo Zhou & Chuang Liu & Haixing Zhao & Zi-Ke Zhang, 2021. "The aging effect in evolving scientific citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4297-4309, May.

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