• Journal of Families and Better Life
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• v.9 no.1 s.17
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• pp.161-178
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• 1991

The purposes of this study are to investigate the impacts of social network support on the middle-aged housewives' crisis and to identify the importance of social network systems of modern families. The subjects of this study were unemployed housewives living in the Seoul area, whose age was from 40 to 59 and whose last child was older than 11 years old. Data were collected by structured questionnaire with the subjects(N= 404). The collected data were analyzed by Frequencies, onewy ANOVA, Scheffe-test, t-test. The major findings were as follows ; 1) Middle-aged housewives, who were the first half of 40's, university graduated, and bilieved in a religion, had lower crisis. 2) The association of social network support and middle-aged housewives' crisis, which were found to be significant were as follows ; (1) The more middle-aged housewives received total, emotional, instrumental support from husbands' families of origin, the lower their crisis was. (2) The more middle-aged housewives received total, emotional, informational, support from their families of origin, the lower their crisis was. (3) The more middle-aged housewives received total, emotional, instrumental support from their friends, the lower their crisis was. (4) The more middle-aged housewives received total, emotional, instrumental, social companionship support from their voluntary association members, the lower their crisis was.

• Annual Conference of KIPS
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• 2019.05a
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• pp.267-269
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• 2019

There are many recommendation systems offer an effort to get better preciseness the information to the users. In order to further improve more accuracy, the social network analysis method which is used to analyze data to community detection in social networks was introduced in the recommendation system and the result shows this method is improving more accuracy. In this paper, we propose a movie recommendation system using social network analysis and normalized discounted cumulative gain with the best accuracy. To estimate the performance, the collaborative filtering using the k nearest neighbor method, the social network analysis with collaborative filtering method and the proposed method are used to evaluate the MovieLens data. The performance outputs show that the proposed method get better the accuracy of the movie recommendation system than any other methods used in this experiment.

• Journal of Preventive Medicine and Public Health
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• v.44 no.5
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• pp.191-200
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• 2011

Objectives: The goal of this paper is to examine the social network effects on post-traumatic sdress disorder (PTSD) in female North Korean immigrants who entered South Korea in 2007. Specifically, it attempts to verify if the density and composition of networks make a difference after controlling for the network size. Methods: A multivariate logistic regression is used to probe the effects of social networks using the North Korean Immigrant Panel data set. Because the data set had only completed its initial survey when this paper was written, the analysis was cross-sectional. Results: The size of the support networks was systematically related to PTSD. Female North Korean immigrants with more supporting ties were less likely to develop PTSD, even after controlling for other risk factors (odds-ratio for one more tie was 0.8). However, once we control for the size of the network, neither the density nor the composition of the networks remains statistically significant. Conclusions: The prevalence of the PTSD among female North Korean immigrants is alarmingly high, and regardless of the characteristics of supporting network members, the size of the supporting networks provides substantial protection. This implies that a simple strategy that focuses on increasing the number of supporting ties will be effective among North Korean immigrants who entered South Korea in recent years.

• Journal of Information Technology Services
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• v.14 no.3
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• pp.49-65
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• 2015

As South Korean large business groups, also known as Chaebol, have broadened their influence in the domestic economy, it is important to analyze the influence of internal transactions among Chaebol affiliates on their performance. In this paper, relationship between internal transactions and efficiency of Chaebol affiliates has been analyzed. Top five Chaebol groups in South Korea are selected; they include Samsung, Hyundai Motors, LG, SK, and Lotte group. Based on internal transactions among affiliates, social networks are constructed for each Chaebol group to analyze centrality, network structures and cliques. Data Envelopment Analysis (DEA) was conducted to examine the efficiency of the Chaebol affiliates. Then, correlations between the degree centrality and the efficiency of Chaebol affiliates were analyzed, and the network structures of Chaebol groups are presented. The result shows that positive correlations between degree centrality and efficiency are observed among four Chaebol Groups. This paper shows that the Social Network Analysis (SNA) techniques can be used in the empirical research for the analysis of internal transactions of Chaebol groups.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.125-133
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• 2019

Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.125-133
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• 2019

This study aimed to investigate the political system related to the Electronic Government Law by analyzing the process of the common initiative of the law. To achieve the goal, this study applied the method of social analysis and sugessted the proper role of the assembly for realizing the electronic government and its control. The data were gathered from the bill information service of the national assembly. Netminer 4.0 was used for refining and analyzing data. The results are as follows. First, by analyzing three centrality(degree, betweenness, and eigenvector) of assembly member, the network effect of the powered party and reelected members were revealed as strong in the network. Second, through the component analysis, 5 sub-network has shown in total. The sub-networks showed two distinctive difference between two big parties. By the difference, members in two parties showed different characteristics in constituting communities and the effect of the powered party revealed as strong and clear. Based on the result, this study demonstrated the necessity of social solidarity rather than solipsism in committing common initiative. And a chronological research is need to anlayze $18^{th}$ and $19^{th}$ assembly to verify the effect of the powered party in prospect study.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.361-365
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• 2010

In recent years, social networks come into the spotlight as the important ways to find people or share information. Especially, existing social network services based on the Internet, such as Facebook.com and Cyworld.com, are now extended into the mobile environment. A mobile phone easily collects the personal information since it is carried by the user at all times, and various types of data can be gathered together with the advance of sensor technologies. These features differentiate the mobile social network services from the previous Internet-based services. In this paper, we estimate the user's mobile social contexts like closeness and relationship between the user and surrounding people using Bayesian networks. The mobile social contexts can be employed as important information for providing mobile social network services, and experimental results on real world data have verified their possibilities.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1053-1063
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• 2011

Social network analysis is the social statistical analysis of any social structure involving a stream of mutual information between observations. In this study we used the results of passes between players in a soccer game. The analysis contents are as follows. (1) Players with important or leading roles are identified. (2) Players are assessed by pass frequency and the success rate of passes. The purpose of this study is for use as basic data for future team strategy, and achieves this by evaluating the role of each individual player within a team. In this study, social network analysis without separating positions is conducted, and is also performed for defensive and attacking positions respectively. The results of this study are as follows: First, when complete team data were available, the players performing leadership roles were Jung-woo Kim, Sung-yeung Ki and Chung-young Lee, whereas Jeong-su Lee acted as a sub-leader. In case of data for defensive positions Jeong-su Lee was a leading player, and in terms of attacking positions, all of the players excelled in the game and could be evaluated as playing lead roles.

• Journal of Information Technology Applications and Management
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• v.19 no.2
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• pp.197-215
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• 2012

SNS has been recognized as a means of expanding social capital by promoting interaction and efficient communication among users. On the other hand, there are serious concerns on negative side of social network which is often called epidemics. Trust plays a critical role in controlling the spread of distorted information and vicious rumor as well as reducing uncertainties and risk from unreliable users in social network. This study focuses on what the antecedents of interpersonal trust are in social network. We performed online survey from 252 Twitter users and tested candidate antecedents which are chosen from previous literature. As a result, propensity to trust of trustor, ability and sincerity of trustee, intimacy between trustor and trustee significantly affected to the interpersonal trust in Twitter.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.52-63
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• 2008

Virtuality is a product of the information age, and as it plays a larger role in the activities of individuals, groups and organizations, the issue of how human behavior varies between virtual and physical space has become one of the most important questions facing the management environment of today. The purpose of this article is to examine how virtuality shapes individuals' social relationships within and outside their work groups. We developed a conceptual framework that explores the links between virtuality and social network based on computer-mediated communication theory and social network theory. Using data from 172 individuals of 42 project teams in 5 global business consulting firms, we tested cross-level hypotheses. The results of hierarchical linear modeling (HLM) indicate that virtuality significantly influences individual's internal tie strength as well as external bridging ties. The results also show the effects of virtual process via CMC vary along with the virtual context.