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Quantitative evaluation of alternative field normalization procedures

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  • Li, Yunrong
  • Radicchi, Filippo
  • Castellano, Claudio
  • Ruiz-Castillo, Javier

Abstract

Wide differences in publication and citation practices make impossible the direct comparison of raw citation counts across scientific disciplines. Recent research has studied new and traditional normalization procedures aimed at suppressing as much as possible these disproportions in citation numbers among scientific domains. Using the recently introduced IDCP (Inequality due to Differences in Citation Practices) method, this paper rigorously tests the performance of six cited-side normalization procedures based on the Thomson Reuters classification system consisting of 172 sub-fields. We use six yearly datasets from 1980 to 2004, with widely varying citation windows from the publication year to May 2011. The main findings are the following three. Firstly, as observed in previous research, within each year the shapes of sub-field citation distributions are strikingly similar. This paves the way for several normalization procedures to perform reasonably well in reducing the effect on citation inequality of differences in citation practices. Secondly, independently of the year of publication and the length of the citation window, the effect of such differences represents about 13% of total citation inequality. Thirdly, a recently introduced two-parameter normalization scheme outperforms the other normalization procedures over the entire period, reducing citation disproportions to a level very close to the minimum achievable given the data and the classification system. However, the traditional procedure of using sub-field mean citations as normalization factors yields also good results.

Suggested Citation

  • Li, Yunrong & Radicchi, Filippo & Castellano, Claudio & Ruiz-Castillo, Javier, 2013. "Quantitative evaluation of alternative field normalization procedures," Journal of Informetrics, Elsevier, vol. 7(3), pages 746-755.
  • Handle: RePEc:eee:infome:v:7:y:2013:i:3:p:746-755
    DOI: 10.1016/j.joi.2013.06.001
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    1. Li, Yunrong & Ruiz-Castillo, Javier, 2013. "The comparison of normalization procedures based on different classification systems," Journal of Informetrics, Elsevier, vol. 7(4), pages 945-958.
    2. Juan A. Crespo & Neus Herranz & Yunrong Li & Javier Ruiz-Castillo, 2014. "The effect on citation inequality of differences in citation practices at the web of science subject category level," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(6), pages 1244-1256, June.
    3. 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.
    4. Davis, Paul & Papanek, Gustav F, 1984. "Faculty Ratings of Major Economics Departments by Citations," American Economic Review, American Economic Association, vol. 74(1), pages 225-230, March.
    5. Loet Leydesdorff & Lutz Bornmann, 2011. "How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 217-229, February.
    6. Alexander I. Pudovkin & Eugene Garfield, 2002. "Algorithmic procedure for finding semantically related journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(13), pages 1113-1119, November.
    7. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "The skewness of science in 219 sub-fields and a number of aggregates," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 385-397, August.
    8. 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.
    9. 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.
    10. Albarrán, Pedro & Ortuño, Ignacio & Ruiz-Castillo, Javier, 2011. "High- and low-impact citation measures: Empirical applications," Journal of Informetrics, Elsevier, vol. 5(1), pages 122-145.
    11. Li, Yunrong & Radicchi, Filippo & Castellano, Claudio & Ruiz-Castillo, Javier, 2013. "Quantitative evaluation of alternative field normalization procedures," Journal of Informetrics, Elsevier, vol. 7(3), pages 746-755.
    12. Michel Zitt & Henry Small, 2008. "Modifying the journal impact factor by fractional citation weighting: The audience factor," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(11), pages 1856-1860, September.
    13. Albarrán, Pedro & Ortuño, Ignacio & Ruiz-Castillo, Javier, 2011. "The measurement of low- and high-impact in citation distributions: Technical results," Journal of Informetrics, Elsevier, vol. 5(1), pages 48-63.
    14. Loet Leydesdorff & Filippo Radicchi & Lutz Bornmann & Claudio Castellano & Wouter Nooy, 2013. "Field-normalized impact factors (IFs): A comparison of rescaling and fractionally counted IFs," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(11), pages 2299-2309, November.
    15. Michael H. MacRoberts & Barbara R. MacRoberts, 1989. "Problems of citation analysis: A critical review," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(5), pages 342-349, September.
    16. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "How important is choice of the scaling factor in standardizing citations?," Journal of Informetrics, Elsevier, vol. 6(4), pages 645-654.
    17. 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.
    18. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    19. Péter Vinkler, 2003. "Relations of relative scientometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 687-694, November.
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