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Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR

Author

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  • Yuen-Hsien Tseng

    (National Taiwan Normal University)

  • Ming-Yueh Tsay

    (National Chengchi University)

Abstract

A series of techniques based on bibliometric clustering and mapping for scientometrics analysis was implemented in a software toolkit called CATAR for free use. Application of the toolkit to the field of library and information science (LIS) based on journal clustering for subfield identification and analysis to suggest a proper set of LIS journals for research evaluation is described. Two sets of data from Web of Science in the Information Science & Library Science (IS&LS) subject category of Journal Citation Reports were analyzed: one ranges from year 2000 to 2004, the other from 2005 to 2009. The clustering results in graphic dendrograms and multi-dimensional scaling maps from both datasets consistently show that some IS&LS journals clustered in the management information systems subfield are distant from the other journals in terms of their intellectual base. Additionally, the cluster characteristics analyzed based on a diversity index reveals the regional characteristics for some identified subfields. Since journal classification has become a high-stake issue that affects the evaluation of scholars and universities in some East Asian countries, both cases (isolation in intellectual base and regionalism in national interest) should be taken into consideration when developing research evaluation in LIS based on journal classification and ranking for the evaluation to be fairly implemented without biasing future LIS research.

Suggested Citation

  • Yuen-Hsien Tseng & Ming-Yueh Tsay, 2013. "Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 503-528, May.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:2:d:10.1007_s11192-013-0964-1
    DOI: 10.1007/s11192-013-0964-1
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    6. A. Abrizah & A. Noorhidawati & A. N. Zainab, 2015. "LIS journals categorization in the Journal Citation Report: a stated preference study," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1083-1099, February.
    7. Shu, Fei & Julien, Charles-Antoine & Zhang, Lin & Qiu, Junping & Zhang, Jing & Larivière, Vincent, 2019. "Comparing journal and paper level classifications of science," Journal of Informetrics, Elsevier, vol. 13(1), pages 202-225.
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    9. Zhang, Baolong & Wang, Hao & Deng, Sanhong & Su, Xinning, 2020. "Measurement and analysis of Chinese journal discriminative capacity," Journal of Informetrics, Elsevier, vol. 14(1).
    10. A. I. M. Jakaria Rahman & Raf Guns & Loet Leydesdorff & Tim C. E. Engels, 2016. "Measuring the match between evaluators and evaluees: cognitive distances between panel members and research groups at the journal level," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1639-1663, December.
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