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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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    1. Staša Milojević & Cassidy R. Sugimoto & Erjia Yan & Ying Ding, 2011. "The cognitive structure of Library and Information Science: Analysis of article title words," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(10), pages 1933-1953, October.
    2. Ma, Ruimin, 2012. "Author bibliographic coupling analysis: A test based on a Chinese academic database," Journal of Informetrics, Elsevier, vol. 6(4), pages 532-542.
    3. Bo Yang & Ying Sun, 2013. "An exploration of link-based knowledge map in academic web space," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 239-253, July.
    4. Shimelis G. Assefa & Abebe Rorissa, 2013. "A bibliometric mapping of the structure of STEM education using co‐word analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(12), pages 2513-2536, December.
    5. Shimelis G. Assefa & Abebe Rorissa, 2013. "A bibliometric mapping of the structure of STEM education using co-word analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(12), pages 2513-2536, December.
    6. William W. Hood & Concepción S. Wilson, 2001. "The Literature of Bibliometrics, Scientometrics, and Informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(2), pages 291-314, October.
    7. Yu‐Wei Chang & Mu‐Hsuan Huang, 2012. "A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(1), pages 22-33, January.
    8. Chang-Ping Hu & Ji-Ming Hu & Sheng-Li Deng & Yong Liu, 2013. "A co-word analysis of library and information science in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 369-382, November.
    9. Navonil Mustafee & Korina Katsaliaki & Paul Fishwick, 2014. "Exploring the modelling and simulation knowledge base through journal co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2145-2159, March.
    10. Chang-Ping Hu & Ji-Ming Hu & Yan Gao & Yao-Kun Zhang, 2011. "A journal co-citation analysis of library and information science in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(3), pages 657-670, March.
    11. Mike Thelwall, 2008. "Quantitative comparisons of search engine results," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(11), pages 1702-1710, September.
    12. Liang-Chu Chen & Yen-Hsuan Lien, 2011. "Using author co-citation analysis to examine the intellectual structure of e-learning: A MIS perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 867-886, December.
    13. Per Ahlgren & Bo Jarneving, 2008. "Bibliographic coupling, common abstract stems and clustering: A comparison of two document-document similarity approaches in the context of science mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(2), pages 273-290, August.
    14. Vincent Larivière & Cassidy R. Sugimoto & Blaise Cronin, 2012. "A bibliometric chronicling of library and information science's first hundred years," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(5), pages 997-1016, May.
    15. Staša Milojević & Cassidy R. Sugimoto & Erjia Yan & Ying Ding, 2011. "The cognitive structure of Library and Information Science: Analysis of article title words," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1933-1953, October.
    16. Yu-Wei Chang & Mu-Hsuan Huang, 2012. "A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 22-33, January.
    17. Vincent Larivière & Cassidy R. Sugimoto & Blaise Cronin, 2012. "A bibliometric chronicling of library and information science's first hundred years," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(5), pages 997-1016, May.
    18. Ji-ping Gao & Kun Ding & Li Teng & Jie Pang, 2012. "Hybrid documents co-citation analysis: making sense of the interaction between science and technology in technology diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 459-471, November.
    19. Howard D. White & Belver C. Griffith, 1981. "Author cocitation: A literature measure of intellectual structure," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 32(3), pages 163-171, May.
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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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