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How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index

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  • Schreiber, Michael

Abstract

The h-index has been shown to have predictive power. Here I report results of an empirical study showing that the increase of the h-index with time often depends for a long time on citations to rather old publications. This inert behavior of the h-index means that it is difficult to use it as a measure for predicting future scientific output.

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  • Schreiber, Michael, 2013. "How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index," Journal of Informetrics, Elsevier, vol. 7(2), pages 325-329.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:2:p:325-329
    DOI: 10.1016/j.joi.2013.01.001
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    References listed on IDEAS

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    1. Thed van Leeuwen, 2008. "Testing the validity of the Hirsch-index for research assessment purposes," Research Evaluation, Oxford University Press, vol. 17(2), pages 157-160, June.
    2. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
    3. Freeman Dyson, 2004. "A meeting with Enrico Fermi," Nature, Nature, vol. 427(6972), pages 297-297, January.
    4. Sune Lehmann & Andrew D. Jackson & Benny E. Lautrup, 2008. "A quantitative analysis of indicators of scientific performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(2), pages 369-390, August.
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    Cited by:

    1. Shaibu Mohammed & Anthony Morgan & Emmanuel Nyantakyi, 2020. "On the influence of uncited publications on a researcher’s h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1791-1799, March.
    2. Miguel A. García-Pérez, 2013. "Limited validity of equations to predict the future h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 901-909, September.
    3. James C. Ryan, 2016. "A validation of the individual annual h-index (hIa): application of the hIa to a qualitatively and quantitatively different sample," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 577-590, October.
    4. 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.
    5. Schreiber, Michael, 2015. "Restricting the h-index to a publication and citation time window: A case study of a timed Hirsch index," Journal of Informetrics, Elsevier, vol. 9(1), pages 150-155.
    6. Tohalino, Jorge A.V. & Amancio, Diego R., 2022. "On predicting research grants productivity via machine learning," Journal of Informetrics, Elsevier, vol. 16(2).
    7. 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.
    8. Samreen Ayaz & Nayyer Masood & Muhammad Arshad Islam, 2018. "Predicting scientific impact based on h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 993-1010, March.

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