• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.127-146
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• 2013

The online social networking services (SNS) have been growing as the means of communication. In this study, we investigated word-of-mouth (WOM) effect under the SNS environment and evaluated the impact of message sender's influence on the WOM effect. Especially, this study focused on the betweenness centrality calculated through the social network analysis (SNA) of SNS network information, and proposed it as the measure of WOM message sender's influence, SNA may provide more accurate and objective measures than subjective self-reporting survey method. Fifty-one Facebook users responded to each of their four Facebook friends, who had been selected based on their betweenness centrality, Statistical analyses were performed using the responses and the betweenness centralities of the Facebook friends. The results showed that the direction (positive vs, negative) of a WOM message in SNS had an impact on the attitude of the message receiver toward the product. Moreover, the betweenness centrality of the message sender as well as his/her opinion leadership had a moderating effect on the WOM effect. Opinion leadership is a measure that has been frequently used for indicating the influence of WOM message sender in the previous studies. Considering the result that the betweenness centrality of the message sender was Significantly correlated to his/her opinion leadership, the betweenness centrality can be used for indicating the influence of WOM message sender.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.43-46
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• 2008

Centrality has been actively studied in network analysis field. In this paper we show a calculation method of closeness centrality for WSN. Since nodes in a sensor network are very scarce in energy and computation capability the calculation of the closeness is done in two tiers by dividing network into clusters. In first step closeness centrality for cluster heads is calculated. In the second step closeness of member nodes of the chosen cluster is computed in respect to that cluster itself.

• Journal of Korean Library and Information Science Society
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• v.47 no.3
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• pp.95-114
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• 2016

The purpose of this preliminary study is to collect specific examples of book reports and understand semantic characteristics of them through semantic network. The analysis was conducted with 23 book reports which classified by three groups. The keywords were selected from the of book reports. Five types of keyword network were composed based on co-occurrence relations with keywords. The result of this study is following these. First, each keyword network of book reports of groups and individuals is shown to have different structural characteristics. Second, each network has different high centrality keywords according to the result analysis of 3 types of centrality(degree centrality, closeness centrality, betweenness centrality). These characteristic means that keyword network analysis is useful in recognizing the characteristics of not only groups' and but also individual's book reports.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

• 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 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.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.479-491
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• 2008

A "task network" is a type of social network that consists of experts who exchange professional help and advice regarding executing tasks. In this study, we investigate the task network used within the IS department of a national bank in Korea. We identify how this network moderates the influence of computer-mediated communication (CMC) technology on an individual s task performance. Size, density, and centrality were measured as the characteristics of a personal task networks. Size equates to the total number of colleagues who work with a specific member for a certain project. Density is the ratio of the number of actual relationships to the total number of available relationships. Centrality defines whether an individual s position is in the exact center of whole network, and is measured by betweenness centrality, meaning the position one member holds between others in a network. Our findings conclude that the conditions - the larger the size of the task network, the smaller its density and the higher its level of centrality - lead to more benefits of using CMC media. Further, this positive effect of CMC is more noticeable when it provides synchronicity.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.35-46
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• 2011

As development of exhibition, it has been an important issue to analyze exhibition for the next success of exhibition. A lot of existing researches have focused on the exhibitor's and visitor's satisfaction problem. However, the exhibitor's satisfaction and success of exhibition come from the analysis of exhibition in the network level. Booths composing exhibition are regarded as nodes in network, so the trace of visitors visiting booths can construct the arc of networks. The purpose of this study is to analyze the booth visiting pattern and components of network through social network analysis using data collected in the $17^{th}$ International KIDS & EDU EXPO for Children. This research is the first approach of network-leveled analysis of exhibition, and the result of network analysis is helpful to support the booth arrangement in next exhibition. Our analysis results the following implications. First, Booths with high degree centrality or betweenness centrality should be deployed in the wide space or corner of the exhibition hall. Finally, booths within a block should be deployed in the same space of the exhibition hall to provide convenience to the visitors and to enhance exhibition performance.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.387-399
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• 2015

Recently collaboration network is generated to find out experts in their field as potential collaborators in health care sector. In this paper, the co-author network of a National Cancer Center researcher was generated for identifying each researcher's role and collaborative research pattern. The co-author network of 2,437 authors was extracted from 1,194 SCI(E) publications from 2000 to 2010 and author's role was analyzed by author's centrality value. Centrality reflecting only the number of papers and centrality weighted by the paper number, impact factor, and authorship contribution was evaluated. On the comparison with simple degree centrality value and the weighted degree centrality, difference of value was statistically significant(t=11.66, p=0.00). Co-author network considering various variables of the paper provides more objective figure of researcher's role. This suggests that co-author network could be more effective in identifying potential collaborators.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.25-43
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• 2022

Unlike the past, efforts must be made to interpret physical distribution from a network perspective as the service area expands spatially. In addition, logistics networks are undergoing rapid changes due to various changes in the environment. Therefore, the purpose of this study is to analyze the changes in the structure of maritime cargo and the centrality of ports using social network analysis. Using the trade data of domestic maritime at five-year intervals, we investigated changes in the network structure and identified the main factors that affect the centrality of domestic ports. Ports with the highest centrality, which is seen as a port that plays the role of an intermediary, emerged in the order of Busan and Ulsan. This study predicts patterns of domestic cargo trade over the next 20 years based on changes in port centrality and understanding of maritime cargo network, and can be used as reference materials for risk preparation.