• Proceedings of the Korean Society for Information Management Conference
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• 2013.08a
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• pp.139-142
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• 2013

본 연구의 목적은 우리나라 공공도서관에서 활동하는 강사간의 연결망을 분석하여 이들의 네트워크와 도서관 운영 참여에 관한 상관관계를 분석하는 것이다. 연구 데이터는 우리나라 A시의 7개 공공 도서관에서 활동한 강사를 대상으로 설문조사하여 수집하였다. 데이터 분석은 우리나라에서 개발한 연결망 분석도구인 NetMiner4를 사용하였다. 분석결과 네트워크의 Betweenness Centrality, Eigenvector Centrality, 그리고 In status Centrality가 다른 중심분석 유형보다 상관관계가 높은 것으로 나타났다. 그러나 운영참여에 관한 모든 문항의 평균값으로 한 분석 결과는 In Degree Centrality의 관계가 가장 높은 것으로 나타났다.

• Korea Trade Review
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• v.47 no.4
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• pp.137-159
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• 2022

This study aims to analyze international trade papers published in Korea during the past 2002-2022 years. Through this study, it is possible to understand the main subject and direction of research in Korea's international trade field. As the research mythologies, this study uses the big data analysis such as the text mining and Social Network Analysis such as frequency analysis, several centrality analysis, and topic analysis. After analyzing the empirical results, the frequency of key word is very high in trade, export, tariff, market, industry, and the performance of firm. However, there has been a tendency to include logistics, e-business, value and chain, and innovation over the time. The degree and closeness centrality analyses also show that the higher frequency key words also have been higher in the degree and closeness centrality. In contrast, the order of eigenvector centrality seems to be different from those of the degree and closeness centrality. The ego network shows the density of business, sale, exchange, and integration appears to be high in order unlike the frequency analysis. The topic analysis shows that the export, trade, tariff, logstics, innovation, industry, value, and chain seem to have high the probabilities of included in several topics.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.58-72
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• 2021

In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.

• Korea Trade Review
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• v.47 no.6
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• pp.189-209
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• 2022

This study aims to analyze Latin America and the Caribbean papers published in Korea during the past 2000-2020 years. Through this study, it is possible to understand the main subject and direction of research in Korea's Latin America and the Caribbean area. As the research mythologies, this study uses the text mining and Social Network Analysis such as frequency analysis, several centrality analyses, and topic analysis. After analyzing the empirical results, there has been a tendency to change the key words and centrality coefficients between 2000-2010 and 2011-2020 years. During 2011-2020 years, the most frequent keywords were changed from Neoliberalism and culture to policy education, and economy related words. The degree and closeness centrality analyses appeared the higher frequency key words. However, the eigenvector centrality appeared very different from the order of frequency key words. The topic analysis shows that the culture, language, and Neoliberalism were the most important keywords during 2000-2010 years but economy, labor trade, industry, development became the most important keywords during 2011-2020 years in topics.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.17-28
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• 2016

This study examines the cruise course network structure in the Asian regions and the centrality of ports using social network analysis (SNA). For network analysis of Asian cruise courses, a data network of cruise courses was constructed using data on courses of cruise ships operating in Asian ports collected from the reports of the Cruise Lines International Associations.There are 249 nodes or ports of ship companies that provide cruise courses to Asia between from October 2015 to June 2016, and these nodes connect 545 ports. Density analysis based on ports where cruise ship companies operated cruise ships showed that, from October 2015 to June 2016, the density was 0.009, which was lower than the average of global port network density (2006 to 2011) and railroad network density. In addition, was calculated to be, which means that connection with all ports was possible through 2,180 steps. In the analysis of the Asian cruise course network centrality, Singapore ranked first in both out-degree and in-degree in connection centrality, followed by Hong Kong, Shanghai, Ho Chi Minh, and Keelung. Singapore also ranked first in the result betweenness centrality analysis, followed by Penang, Dubai, and Hong Kong. From October 2015 to June 2016, the port with the highest Eigenvector centrality was Hong Kong, followed by Ho Chi Minh, Singapore, Shanghai, and Danang. In the case of the domestic ports Incheon, Busan, and Jeju, connection centrality, betweenness centrality, and Eigenvector centrality all ranked lower than their competitor Chinese ports.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.121-142
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• 2014

This study aims to investigate the importance of author keyword with analysis the position of author keyword in journal. In the first stage, an analysis was carried out on the position of author keyword. We examined the importance of author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality and effective size of structural hole. In the next stage, We performed analysis on correlation between network centrality measures and the position of author keyword. The result of correlation analysis on network centrality measures and the position of author keyword shows that there are the more significant areas of the result of the correlation analysis on degree centrality, betweenness centrality and the position of keyword. In addition, These results show that we need to consider that the possible way as measuring the importance of author keyword in journal is not only a term frequency but also degree centrality and betweenness centrality.

• The Plant Pathology Journal
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• v.39 no.3
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• pp.245-254
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• 2023

The plant microbiota plays a crucial role in promoting plant health by facilitating the nutrient acquisition, abiotic stress tolerance, biotic stress resilience, and host immune regulation. Despite decades of research efforts, the precise relationship and function between plants and microorganisms remain unclear. Kiwifruit (Actinidia spp.) is a widely cultivated horticultural crop known for its high vitamin C, potassium, and phytochemical content. In this study, we investigated the microbial communities of kiwifruit across different cultivars (cvs. Deliwoong and Sweetgold) and tissues at various developmental stages. Our results showed that the microbiota community similarity was confirmed between the cultivars using principal coordinates analysis. Network analysis using both degree and eigenvector centrality indicated similar network forms between the cultivars. Furthermore, Streptomycetaceae was identified in the endosphere of cv. Deliwoong by analyzing amplicon sequence variants corresponding to tissues with an eigenvector centrality value of 0.6 or higher. Our findings provide a foundation for maintaining kiwifruit health through the analysis of its microbial community.

• Journal of Information Technology Services
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• v.18 no.4
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• pp.83-95
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• 2019

It is becoming more and more difficult to cope with new knowledge and technology required by society by the efforts of one person or organization according to the development of science and technology. As a method to overcome this, collaborative research is becoming important. This tendency is increasing in the government R&D projects as well, and the 'A' test research institute, which is the subject of this paper, is also increasing a collaborative research. The purpose of this study is to analyze the network characteristics among the participating researchers in the government R&D project conducted by the institution A, and to ascertain how the network characters of the researchers actually affect the financial performance of the team. The results of the analysis show that 'closeness centrality' and 'degree of centrality' contribute positively to the financial performance of the team. On the other hand, 'betweenness centrality' and 'eigenvector centrality' have a negative effect on the financial performance of the team because they are not directly related to financial performance.

• Journal of KIISE
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• v.43 no.10
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• pp.1124-1130
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• 2016

A controlled group is closed compared to other organizations, which hinders collection of data and accurate analysis, so that it is hard to evaluate a controlled group's power structure and predict future changes using usual analytical methods including sociological approach. Analyzing a controlled group using SNA can allow for evaluation of inner power structure by revealing the relationships between members and identifying members with central roles given limited data. In this study, in order to evaluate changes in power structure, time-sequential SNA research was conducted by analyzing eigenvector centrality, which reflects individual influence and reveals the overall power structure. The result showed an improvement in accuracy compared to other centralities that contain individual degree or closeness, and made it possible to presume structural changes such as promotion or purge of a member.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.