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A triangular model for publication and citation statistics of individual authors

Author

Listed:
  • Wolfgang Glänzel

    (KU Leuven
    Library of the Hungarian Academy of Sciences)

  • Sarah Heeffer

    (KU Leuven)

  • Bart Thijs

    (KU Leuven)

Abstract

One of the most important requirements of building applicable models and meaningful indicators for the use of scientometrics at the micro and meso level is the correct identification and disambiguation of authors and institutes. Platforms like ResearcherID or ORCID with author registration providing high reliability but lower coverage now provide appropriate data sets for the development and testing of stochastic models describing the publication activity and citation impact of individual authors. This paper proposes a triangular model incorporating papers, citations and authors analogously to the dichotomous model used at higher levels of aggregation like countries or fields. This model is applied to a set of authors in any field of science identified by their ResearcherID. However, the main advantage of classical citation indicators to study citation impact under conditional productivity turned out to be the main problem in this triangle: the possible heterogeneity of the collaborating authors results in low robustness. A mere technical solution to this problem would be fractional counting at three levels but the conceptual issue, the different roles of co-authors causing this heterogeneity will never be solved by any algorithm.

Suggested Citation

  • Wolfgang Glänzel & Sarah Heeffer & Bart Thijs, 2016. "A triangular model for publication and citation statistics of individual authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 857-872, May.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1870-0
    DOI: 10.1007/s11192-016-1870-0
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    References listed on IDEAS

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    1. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author-based citation analysis?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    2. J. E. Hirsch, 2010. "An index to quantify an individual’s scientific research output that takes into account the effect of multiple coauthorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 741-754, December.
    3. Wolfgang Glänzel & Bart Thijs & András Schubert & Koenraad Debackere, 2009. "Subfield-specific normalized relative indicators and a new generation of relational charts: Methodological foundations illustrated on the assessment of institutional research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(1), pages 165-188, January.
    4. Wolfgang Glänzel & Bart Thijs & Koenraad Debackere, 2014. "The application of citation-based performance classes to the disciplinary and multidisciplinary assessment in national comparison and institutional research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 939-952, November.
    5. Li Tang & John P. Walsh, 2010. "Bibliometric fingerprints: name disambiguation based on approximate structure equivalence of cognitive maps," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 763-784, September.
    6. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author‐based citation analysis?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    7. 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.
    8. Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," Journal of Informetrics, Elsevier, vol. 8(4), pages 917-934.
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