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Sub-field normalization in the multiplicative case : average-based citation indicators

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  • Herranz, Neus
  • Ruiz-Castillo, Javier

Abstract

This paper investigates the citation impact of three large geographical areas –the U.S., the European Union (EU), and the rest of the world (RW)– at different aggregation levels. The difficulty is that 42% of the 3.6 million articles in our Thomson Scientific dataset are assigned to several sub-fields among a set of 219 Web of Science categories. We follow a multiplicative approach in which every article is wholly counted as many times as it appears at each aggregation level. We compute the crown indicator and the Mean Normalized Citation Score (MNCS) using for the first time sub-field normalization procedures for the multiplicative case. We also compute a third indicator that does not correct for differences in citation practices across sub-fields. It is found that: (1) No geographical area is systematically favored (or penalized) by any of the two normalized indicators. (2) According to the MNCS, only in six out of 80 disciplines –but in none of 20 fields– is the EU ahead of the U.S. In contrast, the normalized U.S./EU gap is greater than 20% in 44 disciplines, 13 fields, and for all sciences as a whole. The dominance of the EU over the RW is even greater. (3) The U.S. appears to devote relatively more –and the RW less– publication effort to subfields with a high mean citation rate, which explains why the U.S./EU and EU/RW gaps for all sciences as a whole increase by 4.5 and 5.6 percentage points in the un-normalized case. The results with a fractional approach are very similar indeed

Suggested Citation

  • Herranz, Neus & Ruiz-Castillo, Javier, 2012. "Sub-field normalization in the multiplicative case : average-based citation indicators," UC3M Working papers. Economics we1130, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:werepe:we1130
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    1. Herranz, Neus & Ruiz-Castillo, Javier, 2012. "Sub-field normalization in the multiplicative case: Average-based citation indicators," Journal of Informetrics, Elsevier, vol. 6(4), pages 543-556.
    2. Javier Ruiz-Castillo, 2012. "The evaluation of citation distributions," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(1), pages 291-310, March.
    3. 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.
    4. Neus Herranz & Javier Ruiz-Castillo, 2012. "Sub-field normalization in the multiplicative case: High- and low-impact citation indicators," Research Evaluation, Oxford University Press, vol. 21(2), pages 113-125, April.
    5. 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.
    6. Neus Herranz & Javier Ruiz-Castillo, 2012. "Multiplicative and fractional strategies when journals are assigned to several subfields," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2195-2205, November.
    7. Pedro Albarrán & Javier Ruiz‐Castillo, 2011. "References made and citations received by scientific articles," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(1), pages 40-49, January.
    8. Waltman, Ludo & van Eck, Nees Jan & van Leeuwen, Thed N. & Visser, Martijn S. & van Raan, Anthony F.J., 2011. "Towards a new crown indicator: Some theoretical considerations," Journal of Informetrics, Elsevier, vol. 5(1), pages 37-47.
    9. 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.
    10. R E de Bruin & A Kint & M Luwel & H F Moed, 1993. "A study of research evaluation and planning: the University of Ghent," Research Evaluation, Oxford University Press, vol. 3(1), pages 25-41, April.
    11. Pedro Albarrán & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "Average-based versus high- and low-impact indicators for the evaluation of scientific distributions," Research Evaluation, Oxford University Press, vol. 20(4), pages 325-339, October.
    12. 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.
    13. van Raan, Anthony F.J. & van Leeuwen, Thed N. & Visser, Martijn S. & van Eck, Nees Jan & Waltman, Ludo, 2010. "Rivals for the crown: Reply to Opthof and Leydesdorff," Journal of Informetrics, Elsevier, vol. 4(3), pages 431-435.
    14. Ludo Waltman & Nees Jan Eck & Thed N. Leeuwen & Martijn S. Visser & Anthony F. J. Raan, 2011. "Towards a new crown indicator: an empirical analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 467-481, June.
    15. Aksnes, Dag W. & Schneider, Jesper W. & Gunnarsson, Magnus, 2012. "Ranking national research systems by citation indicators. A comparative analysis using whole and fractionalised counting methods," Journal of Informetrics, Elsevier, vol. 6(1), pages 36-43.
    16. Albarrán, Pedro & Crespo, Juan A. & Ortuño, Ignacio & Ruiz-Castillo, Javier, 2009. "A comparison of the scientific performance of the U. S. and the European Union at the turn of the XXI century," UC3M Working papers. Economics we095534, Universidad Carlos III de Madrid. Departamento de Economía.
    17. Per O. Seglen, 1992. "The skewness of science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 628-638, October.
    18. Larivière, Vincent & Gingras, Yves, 2011. "Averages of ratios vs. ratios of averages: An empirical analysis of four levels of aggregation," Journal of Informetrics, Elsevier, vol. 5(3), pages 392-399.
    19. Wolfgang Glänzel & András Schubert, 2003. "A new classification scheme of science fields and subfields designed for scientometric evaluation purposes," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(3), pages 357-367, March.
    20. David A. King, 2004. "The scientific impact of nations," Nature, Nature, vol. 430(6997), pages 311-316, July.
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    Citations

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    Cited by:

    1. Herranz, Neus & Ruiz-Castillo, Javier, 2012. "Sub-field normalization in the multiplicative case: Average-based citation indicators," Journal of Informetrics, Elsevier, vol. 6(4), pages 543-556.
    2. Finardi, Ugo, 2013. "Correlation between Journal Impact Factor and Citation Performance: An experimental study," Journal of Informetrics, Elsevier, vol. 7(2), pages 357-370.
    3. Guillermo Armando Ronda-Pupo, 2020. "The performance of Latin American research on economics & business," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 573-590, January.
    4. Richard S.J. Tol, 2013. "Measuring catch-up growth in malnourished populations," Working Paper Series 6013, Department of Economics, University of Sussex Business School.
    5. Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," Journal of Informetrics, Elsevier, vol. 8(4), pages 917-934.
    6. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    7. Franceschini, Fiorenzo & Maisano, Domenico, 2014. "Sub-field normalization of the IEEE scientific journals based on their connection with Technical Societies," Journal of Informetrics, Elsevier, vol. 8(3), pages 508-533.
    8. Yunrong Li & Javier Ruiz-Castillo, 2014. "The impact of extreme observations in citation distributions," Research Evaluation, Oxford University Press, vol. 23(2), pages 174-182.
    9. Maria Cláudia Cabrini Gracio & Ely Francina Tannuri Oliveira & Júlio Araujo Gurgel & Maria Isabel Escalona & Antonio Pulgarin Guerrero, 2013. "Dentistry scientometric analysis: a comparative study between Brazil and other most productive countries in the area," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 753-769, May.
    10. Hu, Zhigang & Tian, Wencan & Xu, Shenmeng & Zhang, Chunbo & Wang, Xianwen, 2018. "Four pitfalls in normalizing citation indicators: An investigation of ESI’s selection of highly cited papers," Journal of Informetrics, Elsevier, vol. 12(4), pages 1133-1145.
    11. Tol, Richard S.J., 2013. "Identifying excellent researchers: A new approach," Journal of Informetrics, Elsevier, vol. 7(4), pages 803-810.
    12. Maximiano Ortiz-Pimentel & Carlos Molina & Guillermo Armando Ronda-Pupo, 2020. "Bibliometric assessment of papers on generations in management and business journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 445-469, October.
    13. Waltman, Ludo & van Eck, Nees Jan, 2015. "Field-normalized citation impact indicators and the choice of an appropriate counting method," Journal of Informetrics, Elsevier, vol. 9(4), pages 872-894.
    14. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "On the interplay between normalisation, bias, and performance of paper impact metrics," Journal of Informetrics, Elsevier, vol. 13(1), pages 270-290.

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    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • Y80 - Miscellaneous Categories - - Related Disciplines - - - Related Disciplines
    • Z00 - Other Special Topics - - General - - - General

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