• Proceedings of the Korean Society for Information Management Conference
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• 2013.08a
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• pp.27-30
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• 2013

공동연구 네트워크의 대표적인 사례인 공저 네트워크는 오랫동안 네트워크 분석의 대상으로 다루어져 왔다. 최근에는 가중 네트워크로서 공저 네트워크에 대한 연구가 활발해지면서 연구자의 영향력을 측정하려는 몇 가지 척도가 제안되었다. 이 연구에서는 공저 네트워크에서의 중심성을 측정하기 위해서 사용된 척도인 가중페이지랭크, 공동연구 h-지수와 공동연구 hs-지수, 복합연결정도중심성, c-지수에 대해서 비교 분석해본다.

• Journal of Korean Library and Information Science Society
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• v.42 no.2
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• pp.105-125
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• 2011

This paper grasps about various features of the coauthorship network based on the co-author frequency in the Korean LIS Research Community. This issue includes many topics such as changable aspects of coauthorship network, properties of higher cooperative authors groups. This work is mostly analyzed through a bibliographic analysis of articles which is published from 2000 to 2009(10 years) in Korean Library & Information Science major four journals. The results show three major implications. 1) There is a various structural changes of coauthorship network on the change of the co-author frequency. 2) There are 21 research pairs in the higher cooperative authors groups with the co-author frequency more than five. 3) There seems that any subjective relations between the articles which is produced by 21 research pairs were not clearly presents.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.153-179
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• 2014

This study explores the characteristics of centrality measures for analyzing researchers' impact and structural positions in research collaboration networks. We investigate four binary network centrality measures (degree centrality, closeness centrality, betweenness centrality, and PageRank), and seven existing weighted network centrality measures (triangle betweenness centrality, mean association, weighted PageRank, collaboration h-index, collaboration hs-index, complex degree centrality, and c-index) for research collaboration networks. And we propose SSR, which is a new weighted centrality measure for collaboration networks. Using research collaboration data from three different research domains including architecture, library and information science, and marketing, the above twelve centrality measures are calculated and compared each other. Results indicate that the weighted network centrality measures are needed to consider collaboration strength as well as collaboration range in research collaboration networks. We also recommend that when considering both collaboration strength and range, it is appropriate to apply triangle betweenness centrality and SSR to investigate global centrality and local centrality in collaboration networks.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.323-341
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• 2021

Various research are being published in the areas of humanities, history, aviation/ports, and regional development, centering on the Incheon area which has issues such as large-scale ports and airports, archipelago, and urban regeneration. This study explored the scope of the subject and the distribution of researchers using a informetric analysis focusing on the studies of Incheon. Specifically, this study extracted authors from about 500 Incheon-related research papers listed in the Korean journal's citation index and analyzed the co-author relationship network to understand the cooperative behavior between authors' institutions. In addition, by extracting keywords from the articles and performing a weighted network (PFNET) analysis on the relationship between keywords, the intellectual structure was analyzed. As a result, it was found that Inha University and Incheon National University showed a high TBC, and Incheon Development Institute showed the high NNC. Meanwhile, the intellectual structure of Incheon-related research was found to be composed of 11 thematic clusters, and the social issues of Incheon, ports, and aviation were analyzed as representative clusters.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.57-77
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• 2014

As co-authorship has been prevalent within science communities, counting the credit of co-authors appropriately is an important consideration, particularly in the context of identifying the knowledge structure of fields with author-based analysis. The purpose of this study is to compare the characteristics of co-author credit counting methods by utilizing correlations, multidimensional scaling, and pathfinder networks. To achieve this purpose, this study analyzed a dataset of 2,014 journal articles and 3,892 cited authors from the Journal of the Architectural Institute of Korea: Planning & Design from 2003 to 2008 in the field of Architecture in Korea. In this study, six different methods of crediting co-authors are selected for comparative analyses. These methods are first-author counting (m1), straight full counting (m2), and fractional counting (m3), proportional counting with a total score of 1 (m4), proportional counting with a total score between 1 and 2 (m5), and first-author-weighted fractional counting (m6). As shown in the data analysis, m1 and m2 are found as extreme opposites, since m1 counts only first authors and m2 assigns all co-authors equally with a credit score of 1. With correlation and multidimensional scaling analyses, among five counting methods (from m2 to m6), a group of counting methods including m3, m4, and m5 are found to be relatively similar. When the knowledge structure is visualized with pathfinder network, the knowledge structure networks from different counting methods are differently presented due to the connections of individual links. In addition, the internal validity shows that first-author-weighted fractional counting (m6) might be considered a better method to author clustering. Findings demonstrate that different co-author counting methods influence the network results of knowledge structure and a better counting method is revealed for author clustering.