• 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 Information Management
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• v.41 no.2
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• pp.161-181
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• 2010

The purpose of this study is to investigate citation behavior in internet news to research papers of 10 domestic economic institutes and to suggest institutes' impact quantitatively with h-index and various modified indices. Content analysis of 878 news articles that collected from NAVER news site was performed. First, as citing behavior, cited numbers of research papers, preferred news media, speed, source entry accuracy, centrality, subject section, and length by the institutes were examined. Next, impact indices for institutes were calculated by cited numbers using h-index, g-index, $h_s$-index, and $g_s$-index, and the ranking of 10 research institutes were determined by each impact indices. As a result, institutes belonged to upper ranks showed little variation among the different indices. On the other hand, institutes belonged to middle and lower ranks showed variations in impact indices and experts' survey.

• Journal of Technology Innovation
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• v.15 no.1
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• pp.203-233
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• 2007

This study investigates how characteristics in the value-chain industrial cluster affect the R&D investment and the output of firms in each industries. For this, we try to extract the inter-industrial networking structure from the input-output table in which 17 manufacturing sectors are included. In particular, we will give shape to the "unit structure" which shows the intermediary flows of goods and services between industries in order to get an unit of final demand in a certain industry. Using this "unit structure", we can try the inter-industrial networking analysis and get some indices of centrality and centralization related to the characteristics of each industries in the value-chain industrial cluster. The results show that the centrality in the value-chain industrial cluster does not have any consequence for the R&D investment and the output in each industries. However, there is a correlation between the centralization in the value-chain industrial cluster and the R&D investment and the output of firms in each industries. These results may be very suggestive in bringing up a new frame of industrial cluster policy in a macro level.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.7-24
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• 2009

Since the Web is dynamic, it is necessary to analyze scholarly Web space with both quantitative and qualitative methods for better understanding of communication characteristics. In this study, we analyzed contents of pages and links to ascertain the characteristics of Korean scholarly Web space in terms of network structure and communication behavior. The result shows that the structure of the original network with all the external links remained is not much different from that of the network with activated external links only. However, the purposes of linking vary among scholarly institutions. The centrality measures correlate more strongly with the clustering coefficient than with the constraint index implying the similar explanatory power of the two types of structural indices.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.81-93
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• 2003

The purpose of the study was to explore the potential of the Social Network Analysis as an analytical tool for scientific investigation of learner-learner, or learner-tutor interaction within an e-Learning environment. Theoretical and methodological implication of the Social Network Analysis had been discussed. Following theoretical analysis, an exploratory empirical study was conducted to test statistical correlation between traditional performance measures such as achievement and team contribution index, and the centrality measure, one of the many quantitative measures the Social Network Analysis provides. Results indicate the centrality measure was correlated with the higher order learning performance and peer-evaluated contribution indices. An interpretation of the results and their implication to instructional design theory and practices were provided along with some suggestions for future research.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.391-407
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• 2012

The loss of connectivity and fragmentation of forest landscapes are seriously hindering dispersal of many forest-dwelling species, which may be critical for their viability and conservation by decreasing habitat area and increasing distance among habitats. For understanding their environmental impacts, numerous spatial models exist to measure landscape connectivity. However, general relationships between functional connectivity and landscape structure are lacking, there is a need to develop landscape metrics that more accurately measure landscape connectivity in whole landscape and individual patches. We reviewed functional and structural definition of landscape connectivity, explained their mathematical connotations, and applied representative 13 indices in 3 districts of Seoul having fragmented forest patches with tits, the threshold distance was applied 500m by considering the dispersal of tits. Results of correlation and principal component analysis showed that connectivity indices could be divided by measurement methods whether they contain the area attribute with distance or not. Betweenness centrality(BC), a representative index measuring distance and distribution among patches, appreciated highly stepping stone forest patches, and difference of probability of connectivity(dPC), an index measuring including area information, estimated integrated connectivity of patches. Therefore, for evaluating landscape connectivity, it is need to consider not only general information of a region and species' characteristics but also various measuring methods of landscape connectivity.

• Journal of Nutrition and Health
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• v.23 no.4
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• pp.257-269
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• 1990

We designed this study to compare the total body fat content and its distribution of diabetics with those of normal subjects. Skinfold thicknesses at eight sites(subscapular, subcostal, abdomen, suprailiac, triceps, forearm, thigh and calf) and body circumferences at five sites(waist, hip, arm, thigh and calf) were measured on 220 diabetics(82 male, 138 female) and on 160 nondiabetic subjects(male 57, female 103). We matched 92 pairs with diabetics and nondiabetic control subjects by sex, age, body weight and height, and made comparisons between two groups(case-control study). The results were as follows: 1) There was no significant difference in total body fat content of diabetics and control (male ; 20.40$\pm$2.12%, 19.20$\pm$3.52%, female ; 26.46$\pm$2.53%, 27.01$\pm$2.92%, respectively). However, body muscle mass(%) in diabetic men(33.37$\pm$4.19%) was significantly lower than in nondiabetic men(38.16$\pm$7.11%). 2) Diabetics, especially women, were characterized by more central body fat than control. That is, indices of centrality of body fat distribution(subscapular/triceps skinfold : STR, central/peripheral fat : CPR) of diabetics were higher than those of control. 3) Body weight, body mass index and %IBW(current body weight$\times$100/ideal body weight) had negative correlations with duration of diabetes(r=-0.23~-0.33), but total body fat content(%) and indices of body fat distribution, such as STR, CPR, waist/hip girth ratio(WHR), and waist/thigh girth ratio(WTR), were not related to duration of diabetes.

• Korean Journal of Social Welfare
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• v.68 no.2
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• pp.185-211
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• 2016

This study analyzes key word networks of the papers which are published at Korean Journal of Social Welfare issued by Korean Academy of Social Welfare from 1979 to 2015. It aims at investigating the trends of social welfare researches in Korea by dividing the given period into two: 1979-2000 and 2001-2015. It shows the trends in three ways: methodologies, subjects, and intellectual structures. In order to identify intellectual structure, it calculate centrality indices basing on co-appearance frequency of key words. It also derives some values which explain relationship structure of key words by using pathfinder algorithm, and finally visualizes the intellectual structures by using the NodeXL program. Some implications of the findings of these analyses are discussed in the end.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.17-29
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• 2005

The purpose of the study was to explore the potential of the Social Network Analysis as an analytical tool for scientific investigation of learner-learner, or learner-tutor interaction within a Computer Supported Corporative Learning (CSCL) environment. Theoretical and methodological implication of the Social Network Analysis had been discussed. Following theoretical analysis, an exploratory empirical study was conducted to test statistical correlation between traditional performance measures such as achievement and team contribution index, and the centrality measure, one of the many quantitative measures the Social Network Analysis provides. Results indicate the centrality measure was correlated with the higher order teaming performance and the peer-evaluated contribution indices. An interpretation of the results and their implication to instructional design theory and practices were provided along with some suggestions for future research.

• Convergence Security Journal
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• v.22 no.4
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• pp.169-178
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• 2022

In general, organizations operating multi-domain networks find it difficult to represent and manage multiple domain net works on a single screen space. Instead, most of them are managed with multiple screens visualizing network topology by domain or partitioning one screen area into multiple domains. We propose an efficient method to visualize the topology using only minimal connection information between domain-agnostic nodes in this work. This method visualizes the topology by utilizing centrality indices representing the influence of nodes in the network. Furthermore, the method dynamically segments the entire node's display area using virtual Root nodes to auto-separate domains and weights of child nodes and placing nodes in 3D space. Thus, although it is a straightforward method, the multi-domain network topology can be visualized with only minimal connection information between nodes.