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Understanding of evolutionary features in the library and information science with interdisciplinary network analysis

Author

Listed:
  • Yunhan Liu

    (Nanjing University of Finance & Economics)

  • Xia Xu

    (Nanjing University of Posts and Telecommunications)

  • Shuqing Li

    (Nanjing University of Finance & Economics)

Abstract

The new round of industrial revolution has put forward new development direction and requirements for Library and Information Science (LIS) research. Compared with other research fields, LIS often reflects a distinctive interdisciplinary character. The theoretical system and research methods of LIS are affected by the internal characteristics and external environment, and also need the support of knowledge and methods from other disciplines to accelerate upgrading of the discipline structure. In this paper, we collect international and domestic literature data to present the panoramic interdisciplinary system in LIS research field. The evolutionary characteristics and changes in the network structure of the interdisciplinary system in LIS research field are analyzed by measuring the relationships between the full set of disciplines. Combined with the real requirement of the current social development, we explain a series of practical problems based on the discipline development that have emerged in the stage of Inter-Disciplinary Research (IDR) carried out by important disciplines in the LIS field. Not only can this paper provide reference for clarifying the future positioning of LIS discipline, but also contribute to opening up a broader prospect and development space for the LIS research. Meanwhile, the conclusion of this paper can also help related or emerging disciplines to seek more cooperative research opportunities and application situations in the LIS.

Suggested Citation

  • Yunhan Liu & Xia Xu & Shuqing Li, 2025. "Understanding of evolutionary features in the library and information science with interdisciplinary network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(2), pages 781-808, February.
    • Handle: RePEc:spr:scient:v:130:y:2025:i:2:d:10.1007_s11192-025-05236-y
    DOI: 10.1007/s11192-025-05236-y
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