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A bibliometric approach to the role of author self-citations in scientific communication

Author

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  • Glänzel Wolfgang

    (Hungarian Academy of Sciences, Institute for Research Organisation Budapest ()

  • Thijs Bart

    (Katholieke Universiteit Leuven, Steunpunt O&O Statistieken)

  • Schlemmer Balázs

    (Katholieke Universiteit Leuven, Steunpunt O&O Statistieken)

Abstract

The present paper analyses the role of author self-citations aiming at finding basic regularities of self-citations within the process of documented scientific communication and thus laying the methodological groundwork for a possible critical view at self-citation patterns in empirical studies at any level of aggregation. The study consists of three parts; the first part of the study is concerned with the comparative analysis of the ageing of self-citations and of non-self citations, in the second part the possible interdependence between self-citations and foreign citations is analysed and in the third part the interrelation of the share of self-citations in all citations with other citation-based indicators is studied. The outcomes of this study are two-fold; first, the results characterise author self-citations - at least at the macro level - as an organic part of the citation process obeying rules that can be measured and described with the help of mathematical models. Second, these rules can be used in evaluative micro and meso analyses to identify significant deviations from the reference standards.

Suggested Citation

  • Glänzel Wolfgang & Thijs Bart & Schlemmer Balázs, 2004. "A bibliometric approach to the role of author self-citations in scientific communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(1), pages 63-77, January.
    • Handle: RePEc:spr:scient:v:59:y:2004:i:1:d:10.1023_b:scie.0000013299.38210.74
    DOI: 10.1023/B:SCIE.0000013299.38210.74
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    References listed on IDEAS

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    1. 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.
    2. Quentin L. Burrell, 2002. "Modelling citation age data: Simple graphical methods from reliability theory," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(2), pages 273-285, August.
    3. 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.
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    Cited by:

    1. Liang, Liming & Rousseau, Ronald, 2007. "Transformations of basic publication–citation matrices," Journal of Informetrics, Elsevier, vol. 1(3), pages 249-255.
    2. Wang, Jian & Hicks, Diana, 2015. "Scientific teams: Self-assembly, fluidness, and interdependence," Journal of Informetrics, Elsevier, vol. 9(1), pages 197-207.
    3. Schmoch, Ulrich & Michels, Carolin & Schulze, Nicole & Neuhäusler, Peter, 2012. "Performance and Structures of the German Science System 2011: Germany in an international comparison, China's profile, behaviour of German authors, comparison of the Web of Science and Scopus," Studien zum deutschen Innovationssystem 9-2012, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    4. Glänzel, Wolfgang, 2010. "On reliability and robustness of scientometrics indicators based on stochastic models. An evidence-based opinion paper," Journal of Informetrics, Elsevier, vol. 4(3), pages 313-319.
    5. Georgina Guilera & Juana Gómez-Benito & M. Hidalgo, 2010. "Citation analysis in research on differential item functioning," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(6), pages 1249-1255, October.
    6. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    7. Tehmina Amjad & Yusra Rehmat & Ali Daud & Rabeeh Ayaz Abbasi, 2020. "Scientific impact of an author and role of self-citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 915-932, February.
    8. Shubhanshu Mishra & Brent D Fegley & Jana Diesner & Vetle I Torvik, 2018. "Self-citation is the hallmark of productive authors, of any gender," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-21, September.
    9. Stefano Mammola & Diego Fontaneto & Alejandro Martínez & Filipe Chichorro, 2021. "Impact of the reference list features on the number of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 785-799, January.
    10. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    11. Panagopoulos, George & Tsatsaronis, George & Varlamis, Iraklis, 2017. "Detecting rising stars in dynamic collaborative networks," Journal of Informetrics, Elsevier, vol. 11(1), pages 198-222.
    12. Zaggl, Michael A., 2017. "Manipulation of explicit reputation in innovation and knowledge exchange communities: The example of referencing in science," Research Policy, Elsevier, vol. 46(5), pages 970-983.

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