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Detecting the intellectual structure of library and information science based on formal concept analysis

Author

Listed:
  • Ping Liu

    (Wuhan University)

  • Qiong Wu

    (Wuhan University)

  • Xiangming Mu

    (University of Wisconsin-Milwaukee)

  • Kaipeng Yu

    (Wuhan University)

  • Yiting Guo

    (Wuhan University)

Abstract

Detecting intellectual structure of a knowledge domain is valuable to track the dynamics of scientific research. Formal concept analysis (FCA) provides a new perspective for knowledge discovery and data mining. In this paper we introduce a FCA-based approach to detect intellectual structure of library and information science (LIS). Our approach relies on the mathematical theory which formulates the understanding of “concept” as a unit of extension (scholars) and intension (keywords) as a way of modelling the intellectual structure of a domain. By analyzing the papers published in sixteen prominent journals of LIS domain from 2001 to 2013, the intellectual structure of LIS in the new century has been identified and visualized. Nine major research themes of LIS were detected together with the core keywords and authors to describe each theme. The significant advantage of our approach is that the mathematical formulae produce a conceptual structure which automatically provides generalization and specialization relationships among the concepts. This provides additional information not available from other methods, especially when shared interests of authors from different granularities are also visualized in concept lattice.

Suggested Citation

  • Ping Liu & Qiong Wu & Xiangming Mu & Kaipeng Yu & Yiting Guo, 2015. "Detecting the intellectual structure of library and information science based on formal concept analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 737-762, September.
    • Handle: RePEc:spr:scient:v:104:y:2015:i:3:d:10.1007_s11192-015-1629-z
    DOI: 10.1007/s11192-015-1629-z
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    References listed on IDEAS

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    Cited by:

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    3. Sabrina Petersohn & Thomas Heinze, 2018. "Professionalization of bibliometric research assessment. Insights from the history of the Leiden Centre for Science and Technology Studies (CWTS)," Science and Public Policy, Oxford University Press, vol. 45(4), pages 565-578.
    4. Xiaoyao Han, 2020. "Evolution of research topics in LIS between 1996 and 2019: an analysis based on latent Dirichlet allocation topic model," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2561-2595, December.

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