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Methods to account for citation inflation in research evaluation

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  • Petersen, Alexander M.
  • Pan, Raj K.
  • Pammolli, Fabio
  • Fortunato, Santo

Abstract

Quantitative research evaluation requires measures that are transparent, relatively simple, and free of disciplinary and temporal bias. We document and provide a solution to a hitherto unaddressed temporal bias – citation inflation – which arises from the basic fact that scientific publication is steadily growing at roughly 4% per year. Moreover, because the total production of citations grows by a factor of 2 every 12 years, this means that the real value of a citation depends on when it was produced. Consequently, failing to convert nominal citation values into real citation values produces significant mis-measurement of scientific impact. To address this problem, we develop a citation deflator method, outline the steps to generalize and implement it using the Web of Science portal, and analyze a large set of researchers from biology and physics to demonstrate how two common evaluation metrics – total citations and h-index – can differ by a remarkable amount depending on whether the underlying citation counts are deflated or not. In particular, our results show that the scientific impact of prior generations is likely to be significantly underestimated when citations are not deflated, often by 100% or more of the nominal value. Thus, our study points to the need for a systemic overhaul of the counting methods used evaluating citation impact – especially in the case of researchers, journals, and institutions – which can span several decades and thus several doubling periods.

Suggested Citation

  • Petersen, Alexander M. & Pan, Raj K. & Pammolli, Fabio & Fortunato, Santo, 2019. "Methods to account for citation inflation in research evaluation," Research Policy, Elsevier, vol. 48(7), pages 1855-1865.
  • Handle: RePEc:eee:respol:v:48:y:2019:i:7:p:1855-1865
    DOI: 10.1016/j.respol.2019.04.009
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    1. Iina Hellsten & Renaud Lambiotte & Andrea Scharnhorst & Marcel Ausloos, 2007. "Self-citations, co-authorships and keywords: A new approach to scientists’ field mobility?," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(3), pages 469-486, September.
    2. Seeber, Marco & Cattaneo, Mattia & Meoli, Michele & Malighetti, Paolo, 2019. "Self-citations as strategic response to the use of metrics for career decisions," Research Policy, Elsevier, vol. 48(2), pages 478-491.
    3. David J. Solomon & Bo‐Christer Björk, 2012. "A study of open access journals using article processing charges," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(8), pages 1485-1495, August.
    4. Moed, H. F. & Burger, W. J. M. & Frankfort, J. G. & Van Raan, A. F. J., 1985. "The use of bibliometric data for the measurement of university research performance," Research Policy, Elsevier, vol. 14(3), pages 131-149, June.
    5. Benjamin M. Althouse & Jevin D. West & Carl T. Bergstrom & Theodore Bergstrom, 2009. "Differences in impact factor across fields and over time," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(1), pages 27-34, January.
    6. A. M. Petersen & O. Penner & H. E. Stanley, 2011. "Methods for detrending success metrics to account for inflationary and deflationary factors," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 79(1), pages 67-78, January.
    7. Bornmann, Lutz & Leydesdorff, Loet & Mutz, Rüdiger, 2013. "The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits," Journal of Informetrics, Elsevier, vol. 7(1), pages 158-165.
    8. Pan, Raj K. & Petersen, Alexander M. & Pammolli, Fabio & Fortunato, Santo, 2018. "The memory of science: Inflation, myopia, and the knowledge network," Journal of Informetrics, Elsevier, vol. 12(3), pages 656-678.
    9. Rodrigo Costas & Thed N. Leeuwen & María Bordons, 2010. "Self-citations at the meso and individual levels: effects of different calculation methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 517-537, March.
    10. 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.
    11. 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.
    12. Yin, Yian & Wang, Dashun, 2017. "The time dimension of science: Connecting the past to the future," Journal of Informetrics, Elsevier, vol. 11(2), pages 608-621.
    13. James H. Fowler & Dag W. Aksnes, 2007. "Does self-citation pay?," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(3), pages 427-437, September.
    14. Haeussler, Carolin & Sauermann, Henry, 2013. "Credit where credit is due? The impact of project contributions and social factors on authorship and inventorship," Research Policy, Elsevier, vol. 42(3), pages 688-703.
    15. Terttu Luukkonen, 1991. "Citation indicators and peer review: their time-scales, criteria of evaluation, and biases," Research Evaluation, Oxford University Press, vol. 1(1), pages 21-30, April.
    16. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    17. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
    18. Bornmann, Lutz & Marx, Werner, 2015. "Methods for the generation of normalized citation impact scores in bibliometrics: Which method best reflects the judgements of experts?," Journal of Informetrics, Elsevier, vol. 9(2), pages 408-418.
    19. David J. Solomon & Bo-Christer Björk, 2012. "A study of open access journals using article processing charges," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(8), pages 1485-1495, August.
    20. Filippo Radicchi & Claudio Castellano, 2012. "A Reverse Engineering Approach to the Suppression of Citation Biases Reveals Universal Properties of Citation Distributions," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-9, March.
    21. Parolo, Pietro Della Briotta & Pan, Raj Kumar & Ghosh, Rumi & Huberman, Bernardo A. & Kaski, Kimmo & Fortunato, Santo, 2015. "Attention decay in science," Journal of Informetrics, Elsevier, vol. 9(4), pages 734-745.
    22. Vincent Larivière & Éric Archambault & Yves Gingras, 2008. "Long‐term variations in the aging of scientific literature: From exponential growth to steady‐state science (1900–2004)," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(2), pages 288-296, January.
    23. Zhou, Ping & Leydesdorff, Loet, 2006. "The emergence of China as a leading nation in science," Research Policy, Elsevier, vol. 35(1), pages 83-104, February.
    24. Vaccario, Giacomo & Medo, Matúš & Wider, Nicolas & Mariani, Manuel Sebastian, 2017. "Quantifying and suppressing ranking bias in a large citation network," Journal of Informetrics, Elsevier, vol. 11(3), pages 766-782.
    25. Zaggl, Michael A., 2017. "Manipulation of explicit reputation in innovation and knowledge exchange communities: The example of referencing in science," Research Policy, Elsevier, vol. 46(5), pages 970-983.
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