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A Study on the Network Generation Methods for Examining the Intellectual Structure of Knowledge Domains

Journal of the Korean Society for Library and Information Science / Journal of the Korean Society for Library and Information Science, (P)1225-598X; (E)2982-6292
2006, v.40 no.2, pp.333-355

Abstract

Network generation methods to visualize bibliometric data for examining the intellectual structure of knowledge domains are investigated in some detail. Among the four methods investigated in this study, pathfinder network algorithm is the most effective method in representing local details as well as global intellectual structure. The nearest neighbor graph, although never used in bibliometic analysis, also has some advantages such as its simplicity and clustering ability. The effect of input data preparation process on resulting intellectual structures are examined, and concluded that unlike MDS map with clusters, the network structure could be changed significantly by the differences in data matrix preparation process. The network generation methods investigated in this paper could be alternatives to conventional multivariate analysis methods and could facilitate our research on examining intellectual structure of knowledge domains.

keywords
지적 구조, 네트워크 분석, 패스파인더 네트워크, 정보시각화, 계량서지학Intellectual Structure, Network Analysis, Pathfinder Network, Information Visualization, Bibliometrics, 지적 구조, 네트워크 분석, 패스파인더 네트워크, 정보시각화, 계량서지학Intellectual Structure, Network Analysis, Pathfinder Network, Information Visualization, Bibliometrics

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Journal of the Korean Society for Library and Information Science