• Korean journal of communication and information
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• v.60
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• pp.75-103
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• 2012

The purpose of this study is to explore the meaning and the effect of communication as social capital, which needs to be evaluated empirically focusing on corporate reputation. Also, it tried to analyze consumers' communication network in the structural, substantial, and relational level, which is to verify how characteristics and meanings of communication network structure affect to a good corporate reputation. A survey toward 200 participants was conducted during 5 days from March 29 to April 3, 2012. Characteristics of communication network structure of a corporation with higher reputation is analyzed using the index such as degree, degree centrality, and density. The findings of the study show that a corporation with higher reputation has higher network degree, degree centrality, and density compared to a corporation with lower reputation. Consumers of a corporation with higher reputation get information from various overlapping sources. It allows them to share similar interpretation, which could elevate the degree, degree centrality, and density of network. It also proved that when the network density is high, a corporation with higher reputation can distribute information much faster and easier. Moreover, in the substantial level of social capital, product/service information network has high degree and density rather than corporate issue information network. Likewise, degree and density of information acquisition network was higher than those of information provision network. Also, this study verified the effect and relationship between the network structure characteristics and corporate loyalty in a relational level. In this way, the positive effect of the degree centrality on corporate loyalty was supported. In conclusion, as consumers share more information from overlapping sources, the degree of communication network gets higher. Throughout this network, the diffusion of information among consumers would be activated, and this confirmed that corporate reputation and corporate loyalty is closely related.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.675-685
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• 2011

This paper proposes a job matching function that calculates the job matching probability of a job-seeker to an employer taking the working conditions of a job-seeker and an employer into account. In addition, this study analysis the degree of centrality that means interactions of a job-seeker and an employer utilizing social network analysis. The results are follows. First, a degree of centrality is found to be severely concentrated in certain job-seekers or certain employers; in addition, there are many job-seekers and employers who have no matching results. Second, according to decision tree analysis, characteristics of a job-seeker that influences the degree of centrality are gender, age and degree of education in order of importance. The characteristics of a employer that influences the degree of centrality are proposed salary, industry classification and firm size in order of importance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.314-315
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• 2018

본 연구는 사회연결망 분석을 활용하여 2012년부터 2016년까지 부산항을 기항하는 컨테이너 정기선 항로 패턴 분석을 통해 세계 주요항만과의 중심성을 파악하여 부산항과 연결되어 있는 항만 네트워크의 구조적인 특성을 파악하였다. 부산항 컨테이너 정기선 항로 네트워크상에 연결정도 중심성, 근접중심성, 매개중심성이 높은 항만은 싱가포르항으로 분석되었으며, 실제 연도별 부산항 주요 국가 항만별 처리 물동량 순위와 부산항 컨테이너 정기선 항로 네트워크 중심성 분석 결과 간 순위 비교는 서로 상이한 것으로 나타났다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.137-146
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• 2018

The purpose of this study was to derive and analyze the hub facilities that occupy major positions in the vehicle movement networks of livestock facilities. For this purpose, this study used the KAHIS data provided by Animal and Plant Quarantine Agency. The hub facilities were derived from the degree centrality & betweenness centrality. The analysis results are summarized as follows. First, in a livestock facility's vehicle movement network, there are a small number of hub facilities with very high centrality indicator values compared to other facilities. Second, the hub facilities based on the degree centrality are the feed factory, the milk collecting center, slaughterhouse, slaughterhouse for chicken, and livestock markets. Third, the hub facilities based on the betweenness centrality are the livestock markets, the feed factory, and slaughterhouse. Fourth, hub facilities based on the degree centrality are concentrated in a particular area, but the hub facilities based on betweenness centrality are distributed relatively evenly.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.75-82
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• 2009

Air transport markets are composed of airlines' networks through their base airports. The analysis of an air transport market has been focusing on determining the efficiency or competitiveness of airports or airlines in the market using number of routes, number of passengers, transfer rates, revenues, costs, and other data. However, little work has been done in analyzing the airport network itself. Assuming the air transport markets of Korea, China, and Japan are integrated, this paper aims to analyze the characteristics of the resulting airport network. To that end, the degree of connectivity, the degree of closeness, and the betweenness of centrality are employed. The analysis shows that Incheon International Airport is better than most other airports in terms of the degree of connectivity and that of closeness. Airports in Japan, however, exhibit strong connectivity but weak closeness and betweenness of centrality. Although it has low connectivity, Shenyang Airport has a possibility of becoming an attractive point of the integrated market in the future due to its high degree of closeness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.353-362
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• 2018

The national loss caused by the periodic livestock epidemic is very large. In addition, vehicle movement is the main cause of livestock epidemics in Korea. In this context, this study analyzed the relationship between the degree centrality of livestock facilities and the outbreak of infectious diseases. For this purpose, a livestock vehicle movement network was constructed using the facility entrance data provided by KAHIS. Afterwards, the centrality index was derived for each facility in the vehicle movement network and the mean centrality index of the epidemic and non-epidemic facilities were compared. The analysis results are summarized as follows. First, the degree centrality of epidemic facilities is significantly greater than non-epidemic facilities. As a result of the analysis of the entire period data and the period-based data, in most data, the degree centrality of facilities where livestock infectious diseases occurred was significantly greater than most non-occurrence facilities. Second, in the entire period data, the difference in degree centrality between the epidemic and non-epidemic facilities was smaller for HPAI than for FMD. On the other hand, no significant difference was found in the results of the analysis according to the divided period. The policy implications of the results are as follows. First, proactive management of facilities based on centrality is needed. Second, in the case of cloven-hoofed animal facilities, it is more urgent to introduce a management policy based on the degree centrality.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.369-399
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• 2012

Purpose: Health technology research & development is an important area to leading future. This study examined the current trends for 'oncogene' based on the research subject network to deduce a research front. Method: Papers were extracted from PubMed database using MeSH term for studies on 'oncogenes' and further categorized as papers published by Korean. Keywords were collected from all of articles. Research subject network was generated by keywords. Research subject network was analyzed by weighted degree centrality based social network analysis and transition of research subjects was analyzed by the time series. Results: On 'oncogenes', 'Genes, ras', 'Apoptosis', 'Signal Transduction' had a high degree centrality and currently 'Antineoplastic Agents', 'Prognosis', and 'Tumor Markers, Biological' were widely conducted. Conclusion: Consistency of research trend pattern was found by analyzing oncogene network with compromised to international vs. domestic trends. Analyzing keyword networks in various subject area, those will allow us to predict the research progress and propose evidence of research & developmental strategy.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.9-14
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• 2018

This study aims to investigate an importance of Author keyword with analysis the position of author keyword. An analysis was carried out on the position of author keyword. we examined an importance of Author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In the next stage, we performed analysis on correlation between network centrality measures and the position of keyword. As a result, degree centrality, closeness centrality, betweenness centrality, eigenvector centrality both has a high value in 4th author keyword order. eigenvector centrality was the comparatively effective method to separate of author keyword order method than other 3 centrality. Correlation analysis result shows that the network analysis value are increasing in order. This study has significance in that it was able to examine the author keyword behavior. Future research is needed to identify and supplement future situational factors, behavior, and psychology.

• Journal of the Korean Society for information Management
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• v.32 no.2
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• pp.7-23
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• 2015

While there are several measures for node centralities, such as betweenness and degree, few centrality measures for local centralities in weighted networks have been suggested. This study developed a generalized centrality measure for calculating local centralities in weighted networks. Neighbor centrality, which was suggested in this study, is the generalization of the degree centrality for binary networks and the nearest neighbor centrality for weighted networks with the parameter ${\alpha}$. The characteristics of suggested measure and the proper value of parameter ${\alpha}$ are investigated with 6 real network datasets and the results are reported.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.199-209
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• 2017

This study was carried out to confirm a convergent research pattern and researchers' role in stem cell sector by social network analysis. Articles were extracted from 1996 to 2012 in PubMed, 515 authors of 270 embryonic stem cell and induced pluripotent stem cell articles and 1,515 authors of 580 adult stem cell and mesenchymal stem cell articles. Degree(D) and betweenness(B) centrality was measured and co-author network was generated for researcher's role. As a result, Core researcher and Intermediary researcher was identified in co-author network. Core researcher had high D. centrality, otherwise high B. centrality or not. Intermediary researcher for convergent research had high B. centrality and low D. centrality. Conclusively, co-author network will be used as objective data not only to find core researchers in subject area for improving achievement but also to select experts for research project evaluation.