Analysis of Scientific Publication Networks among Medical Schools in Korea
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참고문헌
키워드
초록
Objectives: This research was intended to analyze the special characteristics and structure of social networks among Korean medical schools for the purpose of providing knowledge regarding medical field structure, dynamics, and potential paradigm development. Methods: A collaborative 12-year data set of 35,469 published articles in the SCOPUS® database was analyzed. Among ISI subcategories, 61 having more than 20 articles were scrutinized. Following identification of correspondence and co-authorship, centralization indices and Key Player analysis were run for each subcategory. Medical schools were grouped into uniform clusters with convergence of iterated correlation (CONCOR) for structural equivalence. Finally, multidimensional scaling was used to visualize similarities. Results: All centralization indexes analyzed demonstrated a shift in the degree of centralization in the network of medical schools throughout the period examined. Betweenness centrality and eigenvector centrality in particular revealed a dramatic change indicating minimization of the role of a specific "gatekeeper". Key Player analysis confirmed Seoul National University as a constant ‘key player’ throughout the period evaluated and for the subcategories examined as well. Conclusions: This study provided insight into the scientific network among the medical schools of Korea. By understanding this network, a strategy to strengthen the basis of research may be developed.
Abstract
Objectives: This research was intended to analyze the special characteristics and structure of social networks among Korean medical schools for the purpose of providing knowledge regarding medical field structure, dynamics, and potential paradigm development. Methods: A collaborative 12-year data set of 35,469 published articles in the SCOPUS® database was analyzed. Among ISI subcategories, 61 having more than 20 articles were scrutinized. Following identification of correspondence and co-authorship, centralization indices and Key Player analysis were run for each subcategory. Medical schools were grouped into uniform clusters with convergence of iterated correlation (CONCOR) for structural equivalence. Finally, multidimensional scaling was used to visualize similarities. Results: All centralization indexes analyzed demonstrated a shift in the degree of centralization in the network of medical schools throughout the period examined. Betweenness centrality and eigenvector centrality in particular revealed a dramatic change indicating minimization of the role of a specific "gatekeeper". Key Player analysis confirmed Seoul National University as a constant ‘key player’ throughout the period evaluated and for the subcategories examined as well. Conclusions: This study provided insight into the scientific network among the medical schools of Korea. By understanding this network, a strategy to strengthen the basis of research may be developed.
참고문헌 (13)
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