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The effect of database dirty data on h-index calculation

Author

Listed:
  • Fiorenzo Franceschini

    (Politecnico di Torino)

  • Domenico Maisano

    (Politecnico di Torino)

  • Luca Mastrogiacomo

    (Politecnico di Torino)

Abstract

As all databases, the bibliometric ones (e.g. Scopus, Web of Knowledge and Google Scholar) are not exempt from errors, such as missing or wrong records, which may obviously affect publication/citation statistics and—more in general—the resulting bibliometric indicators. This paper tries to answer to the question “What is the effect of database uncertainty on the evaluation of the h-index?”, breaking the paradigm of deterministic database analysis and treating responses to database queries as random variables. Precisely an informetric model of the h-index is used to quantify the variability of this indicator with respect to the variability stemming from errors in database records. Some preliminary results are presented and discussed.

Suggested Citation

  • Fiorenzo Franceschini & Domenico Maisano & Luca Mastrogiacomo, 2013. "The effect of database dirty data on h-index calculation," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 1179-1188, June.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:3:d:10.1007_s11192-012-0871-x
    DOI: 10.1007/s11192-012-0871-x
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    References listed on IDEAS

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    1. repec:ebl:ecbull:v:3:y:2008:i:78:p:1-9 is not listed on IDEAS
    2. Franceschini, Fiorenzo & Maisano, Domenico A., 2010. "Analysis of the Hirsch index's operational properties," European Journal of Operational Research, Elsevier, vol. 203(2), pages 494-504, June.
    3. Leo Egghe & Ronald Rousseau, 2006. "An informetric model for the Hirsch-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 121-129, October.
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    5. Fiorenzo Franceschini & Maurizio Galetto & Domenico Maisano & Luca Mastrogiacomo, 2012. "The success-index: an alternative approach to the h-index for evaluating an individual’s research output," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 621-641, September.
    6. Monika Henzinger & Jacob Suñol & Ingmar Weber, 2010. "The stability of the h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 465-479, August.
    7. Jean-Michel Courtault & Naïla Hayek, 2008. "On the Robustness of the h-index: a mathematical approach," Economics Bulletin, AccessEcon, vol. 3(78), pages 1-9.
    8. Bar-Ilan, Judit & Levene, Mark & Lin, Ayelet, 2007. "Some measures for comparing citation databases," Journal of Informetrics, Elsevier, vol. 1(1), pages 26-34.
    9. Tibor Braun & Wolfgang Glänzel & András Schubert, 2006. "A Hirsch-type index for journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 169-173, October.
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    11. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
    12. Franceschini, Fiorenzo & Maisano, Domenico, 2010. "The Hirsch spectrum: A novel tool for analyzing scientific journals," Journal of Informetrics, Elsevier, vol. 4(1), pages 64-73.
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    Cited by:

    1. Fiorenzo Franceschini & Domenico Maisano & Luca Mastrogiacomo, 2015. "Errors in DOI indexing by bibliometric databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2181-2186, March.
    2. Malesios, C., 2016. "Measuring the robustness of the journal h-index with respect to publication and citation values: A Bayesian sensitivity analysis," Journal of Informetrics, Elsevier, vol. 10(3), pages 719-731.

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