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Power laws in citation distributions: Evidence from Scopus

Author

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  • Michał Brzeziński

    () (Faculty of Economic Sciences, University of Warsaw)

Abstract

Modeling distributions of citations to scientific papers is crucial for understanding how science develops. However, there is a considerable empirical controversy on which statistical model fits the citation distributions best. This paper is concerned with rigorous empirical detection of power-law behaviour in the distribution of citations received by the most highly cited scientific papers. We have used a large, novel data set on citations to scientific papers published between 1998 and 2002 drawn from Scopus. The power-law model is compared with a number of alternative models using a likelihood ratio test. We have found that the power-law hypothesis is rejected for around half of the Scopus fields of science. For these fields of science, the Yule, power-law with exponential cut-off and log-normal distributions seem to fit the data better than the pure power-law model. On the other hand, when the power-law hypothesis is not rejected, it is usually empirically indistinguishable from most of the alternative models.

Suggested Citation

  • Michał Brzeziński, 2014. "Power laws in citation distributions: Evidence from Scopus," Working Papers 2014-05, Faculty of Economic Sciences, University of Warsaw.
  • Handle: RePEc:war:wpaper:2014-05
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    File URL: http://www.wne.uw.edu.pl/inf/wyd/WP/WNE_WP122.pdf
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    References listed on IDEAS

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    1. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 4(2), pages 131-134, July.
    2. repec:spr:scient:v:83:y:2010:i:1:d:10.1007_s11192-009-0023-0 is not listed on IDEAS
    3. Pedro Albarrán & Javier Ruiz-Castillo, 2011. "References made and citations received by scientific articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(1), pages 40-49, January.
    4. 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.
    5. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    6. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    7. López-Illescas, Carmen & de Moya-Anegón, Félix & Moed, Henk F., 2008. "Coverage and citation impact of oncological journals in the Web of Science and Scopus," Journal of Informetrics, Elsevier, vol. 2(4), pages 304-316.
    8. Aghaei Chadegani, Arezoo & Salehi, Hadi & Md Yunus, Melor & Farhadi, Hadi & Fooladi, Masood & Farhadi, Maryam & Ale Ebrahim, Nader, 2013. "A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases," MPRA Paper 46898, University Library of Munich, Germany, revised 18 Mar 2013.
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    Cited by:

    1. repec:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2285-2 is not listed on IDEAS
    2. Antonio Perianes-Rodriguez & Javier Ruiz-Castillo, 2016. "A comparison of two ways of evaluating research units working in different scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 539-561, February.
    3. repec:eee:infome:v:12:y:2018:i:1:p:31-41 is not listed on IDEAS
    4. repec:spr:scient:v:105:y:2015:i:3:d:10.1007_s11192-015-1737-9 is not listed on IDEAS
    5. Mike Thelwall, 2016. "Interpreting correlations between citation counts and other indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 337-347, July.
    6. repec:spr:scient:v:114:y:2018:i:3:d:10.1007_s11192-017-2612-7 is not listed on IDEAS
    7. repec:eee:infome:v:12:y:2018:i:1:p:315-329 is not listed on IDEAS
    8. repec:spr:scient:v:112:y:2017:i:3:d:10.1007_s11192-017-2459-y is not listed on IDEAS

    More about this item

    Keywords

    power law; Pareto model; citation distribution; bibliometrics; scientometrics; Scopus; model selection;

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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