• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.648-654
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• 2016

This paper investigates differences of tourism destination choices for sightseeing in Seoul between first-time visitors and repeat visitors. We constructed social network using secondary data from '2015 International Visitor Survey' and analyzed its density and centrality. Study results find that: (1) first-time and repeat visitors' tourism destinations are concentrated in areas located north of the Han river. The proximity of destinations suggests the positive effects resulting from the movement network. (2) As the result of degree centrality, closeness centrality, betweenness centrality, the highest ranking tourism destinations for both visitor groups are identical, but indexes of centralities in repeat visitors' destinations increase, including Shinchon/ Hongik University, Gangnam station, and Garosu-gil. Therefore, the roles of these destinations are becoming established as tourism hubs and are popular among younger visitors as well as attract repeat visitors. Results of this study will be a useful reference in developing and managing new tourism products.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.57-72
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• 2009

As development of information technologies, customer retention has been an important issue in the competing environment. A lot of researches focus on prediction of the churning customers and seeking their characteristics. However, relationships among customers or products have not been considered in existing researches. In this study, product networks are proposed and analyzed to investigate the differences of network characteristics of products purchased by potential churning customers and those of loyal customers. The product networks are constructed from real product purchase data collected from a Korean department store. We investigated the characteristic differences, such as the degree centrality, degree centralization, and density, of two product networks constructed by potential churning customers and the loyal customers. The results indicate that degree centrality, density and degree centralization of the product network of the loyal customers are higher than those of the potential churning customers. And the promotional products of the department store are resulted to be effective in attracting the loyal customers.

• ETRI Journal
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• v.38 no.1
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• pp.52-61
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• 2016

A microblog is a service typically offered by online social networks, such as Twitter and Facebook. From the perspective of information dissemination, we define the concept behind a spreading matrix. A new WeiboRank algorithm for identification of key nodes in microblog networks is proposed, taking into account parameters such as a user's direct appeal, a user's influence region, and a user's global influence power. To investigate how measures for ranking influential users in a network correlate, we compare the relative influence ranks of the top 20 microblog users of a university network. The proposed algorithm is compared with other algorithms - PageRank, Betweeness Centrality, Closeness Centrality, Out-degree - using a new tweets propagation model - the Ignorants-Spreaders-Rejecters model. Comparison results show that key nodes obtained from the WeiboRank algorithm have a wider transmission range and better influence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.718-727
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• 2011

This research aims to empirically investigate into the relationship between venture entrepreneurs' social network and their social competence to utilize the network, which is known to help overcome the weaknesses of small-and-medium-sized ventures. An analysis was made of SEM set up with 211 entrepreneurs' responses, and the following are the findings from the analysis. First, venture entrepreneurs' networking ability has a significant, strong and positive effect on weak tie of their social network(${\beta}$=.527, C.R.=3.626), strong tie(${\beta}$=.594, C.R.=3.969), and the network centrality(${\beta}$=.418, C.R.=4.884). Second, their social astuteness also has a significant and positive effect on weak tie(${\beta}$=.192, C.R.=1.701), strong tie(${\beta}$=.269, C.R.=2.509) and the network centrality(${\beta}$=.228, p=2.283). Third, their interpersonal influence has a significant but negative effect only on strong tie(${\beta}$=-.264, C.R.=-1.862) and the network centrality(${\beta}$=-.394, C.R.=-2.914). Lastly, their apparent sincerity has no significant effect on the subordinate factors of social network. This research has not just empirically analyzed the relationship between the entrepreneurs' social network and their social competence. But also, results of the research provide practical and detailed information to entrepreneurs of small and medium ventures. Moreover, the research is significant in that it has suggested and empirically analyzed the concept of political competence, which is a concrete substance of social competence, and that it has offered theoretical foundations for future researches, which will tackle the issue of the entrepreneurs' competence in the sphere of entrepreneurship.

• Journal of Distribution Science
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• v.18 no.3
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• pp.25-36
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• 2020

Purpose: Based on previous researches on social factors of digital item purchase in digital contents distribution platforms such as SNS, we aim to develop the integrated model that accounts for the dynamic and interactive relationship between social structure indicators and digital item purchase. Research design, data and methodology: A PVAR model was used to capture endogenous and dynamic relationships between digital item purchase and network indicators. Results: We find that there exist considerable endogenous and dynamic relationships between digital item purchase and network structure variables. Not only lagged in-degree and out-degree but also in-closeness and out-closeness centrality have significant and positive impacts on digital item purchase. Lagged clustering has a significant and negative effect on digital item purchase. Lagged purchase has a significant and positive impact just on the present in-closeness and out-closeness centrality; but there is no significant effect of lagged purchase on the other two degree variables and clustering coefficient. We also find that both closeness centralities have much higher carryover effect on digital item purchase and that the elasticity of both closeness centralities on the purchase of digital items is even higher than that of other network structure variables. Conclusions: In-closeness and out-closeness are the most influential factors among social structure variables of this study on digital item purchase.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.163-169
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• 2016

This study is to analyze factors affecting a growth of online community with perspectives of social network. Particularly this study tries to explore structural phenomenon built by interactions between users in a certain of free board belonging to the online community, in which focuses on one's writing a comments responding on those of others. With using SNA(Social Network Analysis), the social network data calculated from users' interaction shown as their comments were collected to draw out each individual's centrality value representing the structure of the online community and also we estimated duration time and the number of each comments as a proxy variable representing growth of the online community. And then cause-and-effect relationship between individual's centrality value and the duration time and the number of each comment were analyzed. As a result of the analysis, Core-Periphery, Centralization and Reciprocity have significant effects on the duration time and the number of each comment, therefore those significant values representing online structure will give an implication to manage, to promote the online community, to forecast its evolution path and to build critical policies.

• Child Health Nursing Research
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• v.25 no.4
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• pp.458-467
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• 2019

Purpose: The purpose of this study was to identify human papillomavirus (HPV) vaccination research trends by visualizing a keyword network. Methods: Articles about HPV vaccination were retrieved from the PubMed and Web of Science databases. A total of 1,448 articles published in 2006~2016 were selected. Keywords from the abstracts of these articles were extracted using the text mining program WordStat and standardized for analysis. Sixty-four keywords out of 287 were finally chosen after pruning. Social network analysis using NetMiner was applied to analyze the whole keyword network and the betweenness centrality of the network. Results: According to the results of the social network analysis, the central keywords with high betweenness centrality included "health education", "health personnel", "parents", "uptake", "knowledge", and "health promotion". Conclusion: To increase the uptake of HPV vaccination, health personnel should provide health education and vaccine promotion for parents and adolescents. Using social media, governmental organizations can offer accurate information that is easily accessible. School-based education will also be helpful.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.101-108
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• 2019

In this research, I conducted a semantic network analysis centering on media articles on purchasing, revitalizing, and utilizing the former Busan branch of Hansung Bank, a modern architectural heritage. We sought the most efficient analysis elements for the analysis of the social arguments about preservation and utilization embedded in media articles. For this reason, Degree Centrality measures how many connections the word described in the media article has, and Betweenness Centrality measures the influence that controls the flow of information through correlation I examined. In addition, keyword that express the theme well examined the aggregation structure in each sub-network. In this research, in theoretical terms, it makes sense in that the social discussion embedded in the article of the mass media is grasped empirically through semantic network analysis of words. Methodological aspect is best when it includes nouns and adjectives and the distance between words is more than four words in the analysis of the cohesive structure of the semantic network to determine whether the influence of social discussions is best assessed through the connection between words to media articles.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.257-266
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• 2011

Over the society the trial for several systems to be connected with Network has been continued to share information and to make it various. In accordance with such a change, the concept of military warfare conduction has been changing form platform centric warfare in separate combat system based on network centric warfare in network based. We have continuously made an effort that we try to get the goal with efficient system which is linked up with network, but such a study on that one in military system analysis is still slower than the study out of military until now. So this study is searching network influence factor by using military network with application of social network analysis method which is used broadly in the society and the science as well. At this time we search co-relationships between social network and the thing that we can analyse C2 time by effectiveness measurement means. By this study it has value of network influence factor identification for the growing network composition.

• The Journal of Korean Association of Computer Education
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• v.17 no.4
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• pp.69-78
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• 2014

This study aims to investigate better predictors, among learner participation and interaction, for collective self-efficacy and achievement in a web-based collaborative learning environment. Interaction requires communication among two or more learners, while participation does not. In this study, interaction was measured by in-degree centrality and out-degree centrality based on the social network analysis perspective. Multiple regression analysis results from 53 college students who performed team project via online showed that in-degree centrality predicted collective self-efficacy and out-degree centrality predicted achievement, while participation was not a significant predictor.