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Identifying Important Topics and Knowledge Flow Paths with Topic-Citation Fusion |
Liang Shuang1,2,Liu Xiaoping1,2(),Chai Wenyue1,2 |
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China 2Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China |
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Abstract [Objective] Understanding and exploring the internal mechanism and direction of knowledge flow, this paper provides references for science and technology innovation, scientific evaluation, and decision-making. [Methods] We established a topic-based knowledge network and constructed the topic importance indicators with their impact factors and node intersection degrees. We used the maximum path search algorithm based on these important topics to construct the knowledge inflow and outflow paths. [Results] The new method could effectively identify the important topics. We also identified the knowledge flow paths and the domains with the most significant knowledge dissemination. [Limitations] The measurement of knowledge flow intensity between nodes needs to consider citation motivations and types. [Conclusions] This paper identifies two-way knowledge flows between topics. Topic groups communicate closely with each other within each discipline. Knowledge flow paths provide valuable references for grasping the research topic developments as a whole.
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Received: 16 December 2022
Published: 28 April 2023
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Fund:Project of Literature and Information Capacity Building, Chinese Academy of Sciences(E1290423) |
Corresponding Authors:
Liu Xiaoping,ORCID:0000-0002-3342-8041,E-mail:liuxp@mail.las.ac.cn。
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