Journal
NEURAL COMPUTING & APPLICATIONS
Volume -, Issue -, Pages -Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-023-08808-2
Keywords
Qualitative comparative analysis; QCA; Knowledge network structure; Social network analysis
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This paper explores the knowledge network structure of foreign research literature by applying the qualitative comparative analysis (QCA) method to the field of information science and library science (ISLS) from the perspective of the cocitation of social network actors. The study reveals that the QCA method covers a wide range within the field of ISLS, but the research topics involved in this field are not concentrated. The author cooperation network shows scale-free characteristics and the application of the QCA method is dominant in European and American countries.
This paper explores the knowledge network structure of foreign research literature by applying the qualitative comparative analysis (QCA) method to the field of information science and library science (ISLS) from the perspective of the cocitation of social network actors such as authors, institutions, countries, and literature, and it further reveals the future application trends of this method. [Method/process] Based on 86 journals in the ISLS field that were downloaded from the Web of Science using the QCA method, the social network analysis (SNA) method and the visual analysis tool Gephi are used to analyse the author cooperation network, the research institution cooperation network, the national cooperation network, the cocitation network, the cutting-edge trends, etc., of journal papers. The analysis shows that the QCA method covers a wide range within the field of ISLS, but the research topics involved in this field are not concentrated, and the author cooperation network has scale-free characteristics. The application of the QCA method is still dominant in European and American countries, and China, the USA, and Italy all play key roles in the national cooperation network. Finally, the institutional cooperation network has certain small group attributes.
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