• Journal of the Korean Society for information Management
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• v.41 no.3
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• pp.511-533
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• 2024

This study aims to develop novel centrality measures applicable to networks that include both directional and weighted information, such as interlibrary loan networks and logistics transportation networks. While weighted PageRank has traditionally been used in such cases, experimental results reveal that it yields similar outcomes to neighborhood centrality, which measures local centrality. However, triangle betweenness centrality (TBC), despite assessing global centrality in weighted networks, does not consider link directions. To address these limitations, we propose two modified versions of the existing TBC measure: TBC-T for trust networks and TBC-F for flow networks. Applying these measures to two interlibrary loan networks, we find that TBC-T considers only the weights of inlinks, while TBC-F incorporates both inlink and outlink weights. These newly developed measures are expected to be useful for measuring node global centrality in weighted directed networks.

• 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.

• The Journal of Information Systems
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• v.31 no.2
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• pp.19-43
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• 2022

Purpose Due to the COVID-19 pandemic, many companies are building virtual workplaces based on virtual reality technology. Through this study, we intend to identify the trend of convergence and convergence research between virtual reality technology and work space, and suggest future promising fields based on this. Design/methodology/approach For this purpose, 12,250 bibliographic data of research papers related to Virtual Reality (VR) and Workplace were collected from Scopus from 1982 to 2021. The bibliographic data of the collected papers were analyzed using Text Mining and Pathfinder Network, Parallel Neighbor Clustering, Nearest Neighbor Centrality, and Triangle Betweenness Centrality. Through this, the relationship between keywords by period was identified, and network analysis and visualization work were performed for virtual reality-based workplace research. Findings Through this study, it is expected that the main keyword knowledge structure flow of virtual reality-based workplace convergence research can be identified, and the relationship between keywords can be identified to provide a major measure for designing directions in subsequent studies.

• Proceedings of the Korean Society for Information Management Conference
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• 2005.08a
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• pp.357-364
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• 2005

저자동시인용 자료에 대한 분석 도구로 삼각매개중심성 (triangle betweenness centrality; TBC) 척도를 비롯하여 네 가지 새로운 척도를 제안하고 정보학 분야의 지적 구조 분석에 적용해보았다. 제안한 척도는 사회네트워크 분석 분야에서 사용되고 있는 여러 중심성 척도를 참고하여 동시인용 데이터에 적합하도륵 고안되었다. 검증을 위해서 이은숙, 정영미(2002)의 연구에서 수집한 1990년부터2000년까지 11년간 Journal of America Society for Information Science에 인용된 주요 저자50명의 동시인용 네트워크를 여러 중심성 척도를 사용해서 분석하였다. 전통적인 분석 도구인 다차원척도법이나 군집분석과 달리 중심성 척도를 통해서는 저작물에 반영된 개별 저자의 입지와 영향력에 대한 구체적인 분석이 가능하였다. 특히 삼각매개중심성 척도는 측정 범위의 조절이 자유로와서 지역적 중심성과 전역적 중심성을 모두 파악할 수 있는 것으로 나타났다.

• Journal of the Korean Society for information Management
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• v.30 no.4
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• pp.241-264
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• 2013

This study compared and analyzed weighted network centrality measures supported by Opsahl's tnet and Lee's WNET, which are free softwares for weighted network analysis. Three node centrality measures including weighted degree, weighted closeness, and weighted betweenness are supported by tnet, and four node centrality measures including nearest neighbor centrality, mean association, mean profile association, triangle betweenness centrality are supported by WNET. An experimental analysis carried out on artificial network data showed tnet's high sensitiveness on linear transformations of link weights, however, WNET's centrality measures were insensitive to linear transformations. Seven centrality measures from both tools, tnet and WNET, were calculated on six real network datasets. The results showed the characteristics of weighted network centrality measures of tnet and WNET, and the relationships between them were also discussed.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.2
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• pp.149-169
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• 2021

As collaboration of research is increasing in social science, this study aims to investigate the changes in patterns of research collaboration in the field of library and information science, over the years from 2002 to 2020. The data used for this study were collected from four major journals in the field to analyze the frequency of co-authored research articles by journals and by institutions that all authors were associated with. Also, the institutions data were used to build a co-authorship network, which produced various indices including TBC (Triangle Betweenness Centrality) that showed which institutions were more central than others in the network. The result shows the number of co-authored articles were constantly increasing in all journals, and some institutions, mostly universities, showed the higher centrality scores than others and the range of collaboration were also expanded.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.133-154
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• 2016

Interdisciplinary approach has been recognized as one of key strategies to address various and complex research problems in modern science. The purpose of this study is to investigate the interdisciplinary characteristics and structure of the field of big data. Among the 1,083 journals related to the field of big data, multiple Subject Categories (SC) from the Web of Science were assigned to 420 journals (38.8%) and 239 journals (22.1%) were assigned with the SCs from different fields. These results show that the field of big data indicates the characteristics of interdisciplinarity. In addition, through bibliographic coupling network analysis of top 56 journals, 10 clusters in the network were recognized. Among the 10 clusters, 7 clusters were from computer science field focusing on technical aspects such as storing, processing and analyzing the data. The results of cluster analysis also identified multiple research works of analyzing and utilizing big data in various fields such as science & technology, engineering, communication, law, geography, bio-engineering and etc. Finally, with measuring three types of centrality (betweenness centrality, nearest centrality, triangle betweenness centrality) of journals, computer science journals appeared to have strong impact and subjective relations to other fields in the network.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.327-345
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• 2008

The main purposes of this study are to construct a Korean science network from journal contributions data of Korean researchers, and to analyze the structure and characteristics of the network. First of all, the association matrix of 140 scholarly domains are calculated based on the number of contributions in common journals, and then the Pathfinder network algorithm is applied to those matrix. The resulting network has several hubs such as 'Biology', 'Korean Language & Linguistics', 'Physics', etc. The entropy formula and several centrality measures for the weighted networks are adopted to identify the centralities and interdisciplinarity of each scholarly domain. In particular, the date hubs, which have several weak links, are successively distinguished by local and global triangle betweenness centrality measures.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.47-65
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• 2021

This study aims to identify specific topics, trends, and structural characteristics of scholarly communication research, based on 1,435 articles published from 1970 to 2018 in the Scopus database through Latent Dirichlet Allocation topic modeling, serial analysis, and network analysis. Topic modeling, time series analysis, and network analysis were used to analyze specific topics, trends, and structures, respectively. The results were summarized into three sets as follows. First, the specific topics of scholarly communication research were nineteen in number, including research resource management and research data, and their research proportion is even. Second, as a result of the time series analysis, there are three upward trending topics: Topic 6: Open Access Publishing, Topic 7: Green Open Access, Topic 19: Informal Communication, and two downward trending topics: Topic 11: Researcher Network and Topic 12: Electronic Journal. Third, the network analysis results indicated that high mean profile association topics were related to the institution, and topics with high triangle betweenness centrality, such as Topic 14: Research Resource Management, shared the citation context. Also, through cluster analysis using parallel nearest neighbor clustering, six clusters connected with different concepts were identified.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.11-39
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• 2018

The study examines the research trends of doctoral dissertations in Library Science and Information Science published in the U.S. for the last 5 years. Data collected from PQDT Global includes 1,016 doctoral dissertations containing "Library Science" or "Information Science" as subject headings, and keywords extracted from those dissertations were used for a network analysis, which helps identifying the intellectual structure of the dissertations. Also, the analysis using 103 subject heading keywords resulted in various centrality measures, including triangle betweenness centrality and nearest neighbor centrality, as well as 26 clusters of associated subject headings. The most frequently studied subjects include computer-related subjects, education-related subjects, and communication-related subjects, and a cluster with information science as the most central subject contains most of the computer-related keywords, while a cluster with library science as the most central subject contains many of the education-related keywords. Other related subjects include various user groups for user studies, and subjects related to information systems such as management, economics, geography, and biomedical engineering.