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The impact of classification systems in the evaluation of the research performance of the Leiden Ranking universities

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  • Antonio Perianes‐Rodriguez
  • Javier Ruiz‐Castillo

Abstract

In this article, we investigate the consequences of choosing different classification systems—namely, the way publications (or journals) are assigned to scientific fields—for the ranking of research units. We study the impact of this choice on the ranking of 500 universities in the 2013 edition of the Leiden Ranking in two cases. First, we compare a Web of Science (WoS) journal‐level classification system, consisting of 236 subject categories, and a publication‐level algorithmically constructed system, denoted G8, consisting of 5,119 clusters. The result is that the consequences of the move from the WoS to the G8 system using the Top 1% citation impact indicator are much greater than the consequences of this move using the Top 10% indicator. Second, we compare the G8 classification system and a publication‐level alternative of the same family, the G6 system, consisting of 1,363 clusters. The result is that, although less important than in the previous case, the consequences of the move from the G6 to the G8 system under the Top 1% indicator are still of a large order of magnitude.

Suggested Citation

  • Antonio Perianes‐Rodriguez & Javier Ruiz‐Castillo, 2018. "The impact of classification systems in the evaluation of the research performance of the Leiden Ranking universities," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(8), pages 1046-1053, August.
    • Handle: RePEc:bla:jinfst:v:69:y:2018:i:8:p:1046-1053
    DOI: 10.1002/asi.24017
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    Cited by:

    1. Huang, Shengzhi & Huang, Yong & Bu, Yi & Luo, Zhuoran & Lu, Wei, 2023. "Disclosing the interactive mechanism behind scientists’ topic selection behavior from the perspective of the productivity and the impact," Journal of Informetrics, Elsevier, vol. 17(2).
    2. Mike Thelwall, 2019. "The influence of highly cited papers on field normalised indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 519-537, February.
    3. Xiaomei Bai & Fuli Zhang & Jinzhou Li & Zhong Xu & Zeeshan Patoli & Ivan Lee, 2021. "Quantifying scientific collaboration impact by exploiting collaboration-citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7993-8008, September.

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