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Bibliometric indicators of young authors in astrophysics: Can later stars be predicted?

Author

Listed:
  • Frank Havemann

    (Humboldt-Universität zu Berlin)

  • Birger Larsen

    (Aalborg University)

Abstract

We test 16 bibliometric indicators with respect to their validity at the level of the individual researcher by estimating their power to predict later successful researchers. We compare the indicators of a sample of astrophysics researchers who later co-authored highly cited papers before their first landmark paper with the distributions of these indicators over a random control group of young authors in astronomy and astrophysics. We find that field and citation-window normalisation substantially improves the predicting power of citation indicators. The sum of citation numbers normalised with expected citation numbers is the only indicator which shows differences between later stars and random authors significant on a 1 % level. Indicators of paper output are not very useful to predict later stars. The famous h-index makes no difference at all between later stars and the random control group.

Suggested Citation

  • Frank Havemann & Birger Larsen, 2015. "Bibliometric indicators of young authors in astrophysics: Can later stars be predicted?," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1413-1434, February.
    • Handle: RePEc:spr:scient:v:102:y:2015:i:2:d:10.1007_s11192-014-1476-3
    DOI: 10.1007/s11192-014-1476-3
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    1. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2013. "Which percentile-based approach should be preferred for calculating normalized citation impact values? An empirical comparison of five approaches including a newly developed citation-rank approach (P1," Journal of Informetrics, Elsevier, vol. 7(4), pages 933-944.
    2. George A. Lozano & Vincent Larivière & Yves Gingras, 2012. "The weakening relationship between the impact factor and papers' citations in the digital age," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2140-2145, November.
    3. van Eck, Nees Jan & Waltman, Ludo, 2008. "Generalizing the h- and g-indices," Journal of Informetrics, Elsevier, vol. 2(4), pages 263-271.
    4. Sune Lehmann & Andrew D. Jackson & Benny E. Lautrup, 2006. "Measures for measures," Nature, Nature, vol. 444(7122), pages 1003-1004, December.
    5. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, August.
    6. Waltman, Ludo & van Eck, Nees Jan, 2013. "A systematic empirical comparison of different approaches for normalizing citation impact indicators," Journal of Informetrics, Elsevier, vol. 7(4), pages 833-849.
    7. Radicchi, Filippo & Castellano, Claudio, 2012. "Testing the fairness of citation indicators for comparison across scientific domains: The case of fractional citation counts," Journal of Informetrics, Elsevier, vol. 6(1), pages 121-130.
    8. Alberto Pepe & Michael J Kurtz, 2012. "A Measure of Total Research Impact Independent of Time and Discipline," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    9. Zhou, Ping & Leydesdorff, Loet, 2011. "Fractional counting of citations in research evaluation: A cross- and interdisciplinary assessment of the Tsinghua University in Beijing," Journal of Informetrics, Elsevier, vol. 5(3), pages 360-368.
    10. Schreiber, Michael, 2008. "A modification of the h-index: The hm-index accounts for multi-authored manuscripts," Journal of Informetrics, Elsevier, vol. 2(3), pages 211-216.
    11. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, August.
    12. 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.
    13. A. Pudovkin & H. Kretschmer & J. Stegmann & E. Garfield, 2012. "Research evaluation. Part I: productivity and citedness of a German medical research institution," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 3-16, October.
    14. Kosmulski, Marek, 2012. "Calibration against a reference set: A quantitative approach to assessment of the methods of assessment of scientific output," Journal of Informetrics, Elsevier, vol. 6(3), pages 451-456.
    15. Michael Schreiber, 2008. "The influence of self-citation corrections on Egghe’s g index," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(1), pages 187-200, July.
    16. Ludo Waltman & Nees Jan van Eck, 2012. "The inconsistency of the h-index," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 406-415, February.
    17. Lundberg, Jonas, 2007. "Lifting the crown—citation z-score," Journal of Informetrics, Elsevier, vol. 1(2), pages 145-154.
    18. Opthof, Tobias & Leydesdorff, Loet, 2010. "Caveats for the journal and field normalizations in the CWTS (“Leiden”) evaluations of research performance," Journal of Informetrics, Elsevier, vol. 4(3), pages 423-430.
    19. Johannes Hönekopp & Julie Khan, 2012. "Future publication success in science is better predicted by traditional measures than by the h index," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 843-853, March.
    20. van Eck, N.J.P. & Waltman, L., 2008. "Generalizing the h- and g-indices," ERIM Report Series Research in Management ERS-2008-049-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    21. 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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    5. Danielle H. Lee, 2019. "Predicting the research performance of early career scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1481-1504, December.
    6. Lindahl, Jonas, 2018. "Predicting research excellence at the individual level: The importance of publication rate, top journal publications, and top 10% publications in the case of early career mathematicians," Journal of Informetrics, Elsevier, vol. 12(2), pages 518-533.
    7. Bin Wang & Feng Wu & Lukui Shi, 2023. "AGSTA-NET: adaptive graph spatiotemporal attention network for citation count prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 511-541, January.
    8. Cena, Anna & Gagolewski, Marek & Siudem, Grzegorz & Żogała-Siudem, Barbara, 2022. "Validating citation models by proxy indices," Journal of Informetrics, Elsevier, vol. 16(2).
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    10. 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.

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