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Quantitative evaluation of alternative field normalization procedures

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

The use of citation numbers for the assessment of research quality has become highly relevant in modern science. Although it is well known that scientific domains strongly differ in terms of citation rates, bibliometric indicators currently used in research assessment are often based on the sole use of raw citation numbers. This necessarily leads to unfair evaluation procedures in cross-disciplinary contexts. For this reason, there is an increasing trend towards the formulation of normalization procedures able to suppress disproportions in citation numbers among scientific domains, and thus to lead to more fair cross-disciplinary evaluation criteria. In this paper, we rigorously test the performance of several field normalization procedures devoted to this purpose. We find that four procedures discussed in the literature do worse than the usual normalization with field averages. The latter drastically reduces citation disproportions among scientific disciplines. Finally, we find that a recently introduced two-parameters normalization scheme reduces citation disproportions to a level very close to the best achievable level of reduction.

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Paper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we1305.

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Date of creation: Mar 2013
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Handle: RePEc:cte:werepe:we1305
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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. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "The skewness of science in 219 sub-fields and a number of aggregates," Economics Working Papers we1109, Universidad Carlos III, Departamento de Economía.
  3. 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.
  4. Li Yunrong & Filippo Radicchi & Claudio Castellano & Javier Ruiz-Castillo, 2013. "Quantitative evaluation of alternative field normalization procedures," Economics Working Papers we1305, Universidad Carlos III, Departamento de Economía.
  5. 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.
  6. Davis, Paul & Papanek, Gustav F, 1984. "Faculty Ratings of Major Economics Departments by Citations," American Economic Review, American Economic Association, vol. 74(1), pages 225-30, March.
  7. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
  8. 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.
  9. 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.
  10. Pedro Albarrán & Ignacio Ortuño & Javier Ruiz-Castillo, 2010. "High - and low-impact citation measures: empirical applications," Economics Working Papers we10_09, Universidad Carlos III, Departamento de Economía.
  11. Juan A. Crespo & Neus Herranz & Yunrongs Li & Javier Ruiz-Castillo, 2013. "The effect on citation inequality of differences in citation practices at the Web of Sciences subject category level," Economics Working Papers we1303, Universidad Carlos III, Departamento de Economía.
  12. 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.
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