• Journal of Information Technology Services
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• v.15 no.1
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• pp.97-111
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• 2016

In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

• International Journal of Advanced Culture Technology
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• v.6 no.2
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• pp.58-64
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• 2018

This main purpose of the study is to identify social network of communicators sharing information on Bokjiro for publicizing welfare policy. This study employs NodeXL pro to understand networks and their role in the social network. The data for social network analysis was collected from Twitter for a week. The result of the analysis shows that the social network of communicators on Bokjiro does not have many nodes. It also has an independent network with high possibility of information distortion. Little communicators have controlling power in information flow in one way of communication. According to the result, it is not effective for marketing strategy of welfare policy in providing online information through Bokjiro. The study suggests that the government should use the transactional approach to marketing based on agent-oriented activity focusing on the exchange relationship between information providers and demanders in an age of networked intelligence.

• Journal of Preventive Medicine and Public Health
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• v.46 no.1
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• pp.28-38
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• 2013

Objectives: This study aimed to collect information that will help enhance the social networks and improve the quality of life among elderly people by observing the relationship between their social network and health-related quality of life (HRQoL) and by analyzing social network factors affecting HRQoL. Methods: This study was based on the 2008 Community Health Survey in Yeoncheon County. Three hundred elders were included in the study population. We compared the revised Lubben Social Network Scale (LSNS-R) score and Euro quality of life-5 dimensions health status index by demographic characteristics and chronic disease prevalence. We analyzed the data using multiple regression and tobit regression by setting the HRQoL as the dependent variable and social network and other characteristics as the independent variables. We analyzed social network factors by using factor analysis. Results: The LSNS-R score differed significantly according to age and existence of a spouse. According to the results from the hierarchical multiple regression analysis, the LSNS-R explained 0.10 of the variance and LSNS-R friends factor explained 0.10 of the variance. The tobit regression indicated that the contribution of the LSNS-R family size factor to the regression coefficient of the independent variable that affected the HRQoL was $B_T$=2.96, that of the LSNS-R family frequency factor was $B_T$=3.60, and that of LSNS-R friends factor was $B_T$=5.41. Conclusions: Social networks among elderly people had a significant effect on HRQoL and their networks of friends had a relatively higher effect than those of family members.

• Health Policy and Management
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• v.29 no.2
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• pp.138-145
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• 2019

Background: The purpose of this study is supposed to figure out the keyword network from 2009 to 2018 with social network analysis and provide the research data that can help the Korea government's policy making on smoking cessation. Methods: First, frequency analysis on the keyword was performed. After, in this study, I applied three classic centrality measures (degree centrality, betweenness centrality, and eigenvector centrality) with R 3.5.1. Moreover, I visualized the results as the word cloud and keyword network. Results: As a result of network analysis, 'smoking' and 'smoking cessation' were key words with high frequency, high degree centrality, and betweenness centrality. As a result of looking at trends in keyword, many study had been done on the keyword 'secondhand smoke' and 'adolescent' from 2009 to 2013, and 'cigarette graphic warning' and 'electronic cigarette' from 2014 to 2018. Conclusion: This study contributes to understand trends on smoking cessation study and seek further study with the keyword network analysis.

• Health Policy and Management
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• v.25 no.2
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• pp.129-139
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• 2015

Background: Policy network theory was proved to be an appropriate analytic tool for the current social welfare policy making process. This study aimed to analyze policy making process related to the nurse expansion and policy output while focusing on the interactions and activities among various policy actors. Methods: In this study, we used reports related to the need for expansion of nursing personnel journals, dissertations, newspaper articles, for hearings and debate policies for securing nurse data, and interviews. We examined three components of policy network, that is, policy actors, interactions, linkage of interest. Results: For that to expand the nurse before the 2000s in expanding the supply of medical supplies have been conducted without much disagreement among policy actors under the government's initiative. However, there was lacked a close relationship between the expanding supply of nurses and inaccurate analysis of supply and demand. As the policy is applied between the various policy actors' needs and claims, conflict was intensified and many policy options had been developed. Government only took a role as a coordinator among policy actors in the 2000's. Also, it was difficult to find sufficient and clear evidence that policy-making process based on fair judgment. Conclusion: Therefore, it is urgently required to determine the policy through a social consensus to address the appropriate policy means and the process by correct analysis of the policy issues.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.261-269
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• 2012

The purpose of this study was to suggest policies that take advantage of social networking services in the field of social commerce. Presented it, in order for the concept of a social network service for the first time, were examined by four representative types of social network services, and analyzed the characteristics of each. Domestic current status and concepts presented and the addition of social commerce, and analyzed the characteristics of each type proposed six kinds. Utilizing social network services to the end, was to suggest measures that can be incorporated into the social commerce business. The results of this study suggested that the marketing implications for how social network services in the social commerce business that can be utilized in companies that will say that its worth.

• Health Policy and Management
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• v.21 no.4
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• pp.493-510
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• 2011

Objectives : This study aims to explore how social support and social network are related with health behavior. Methods : The target population was 12,449 people in Chungcheongbuk-do. The sample was accrued for the period of 3 months in 2008 by face to face interview of direct visiting from systematic sampling method. The instruments used in this study were social support, social network and health behavior. Results : There was significant difference in the level of social support and social network by sex, age, educational level, occupation, and monthly income(p<0.05). There was significant difference in the level of social support by alcohol drinking, physical exercise. There was significant difference in the level of social network by smoking, alcohol drinking, physical exercise, obesity(p<0.05). Multivarite analysis shows significant difference in the level of social instrumental support by smoking, physical exercise. It shows significant difference in the level of social emotional support by smoking. It also shows significant difference in the level of social network by smoking, physical exercise. Conclusion : These results suggest that social support and social network may be associated with health behavior. Because this study was cross sectional research, the order was not found between social support, social network and health behavior. Through a study on monitoring, we will obtain more information for relationship.

• Journal of Digital Convergence
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• v.9 no.3
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• pp.225-233
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• 2011

To determine factors affecting social network service e-service quality, this research is to investigate factors of social network service e-service quality, and analyze how these factors influencing on social network service e-service satisfactions. As a results, three dimensions were identified namely, fulfillment, ease of use and playfulness. But two dimensions were rejected namely connectivity, security. It indicates that the qualitative aspect is becoming more important than quantitative in social network service management.

• Research in Community and Public Health Nursing
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• v.24 no.4
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• pp.438-450
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• 2013

Purpose: The purpose of this study is to identify relationships between acculturation, social network, and health-related quality of life (HRQOL) among Korean-Chinese immigrants. Methods: A cross-sectional descriptive study was conducted with 147 Korean-Chinese immigrants who were residing more than 1 year in Korea. Physical and mental dimensions of HRQOL were assessed by Short Form-12 Health Survey that consisted of a physical component summary (PCS) and a mental component summary (MCS). Data were analyzed with Pearson's correlation and multiple regression. Results: The mean PCS score was $41.14{\pm}10.72$ and the mean MCS score was $49.09{\pm}11.31$ (possible range 10-70). Depression (${\beta}$=-6.43) and Social network frequency (${\beta}$=2.44) explained 28.4% of the variance in PCS while depression (${\beta}$=-11.54) and visiting clinic/hospital (${\beta}$=-4.00) explained 34.3% of the variance in MCS. Acculturation was not significantly associated with HRQOL. Conclusion: This study confirmed that the social network frequency influences HRQOL among Korean-Chinese Immigrants. The findings suggest that social network analysis should be considered in the process of developing health intervention strategies for Korean-Chinese immigrants.

• Journal of Contemporary Eastern Asia
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• v.18 no.2
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• pp.90-117
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• 2019

How is science advice integrated in environmental policymaking? This is an increasingly pertinent question that is being raised since the nuclear catastrophe of Fukushima, Japan, in 2011. Global re-evaluation of energy policies and climate mitigation measures include discussions on how to better integrate science advice in policymaking, and at the same time keeping science independent from political influence. This paper addressed the policy discourse of setting up a national CO2 reduction target in Japanese policymaking between 2009 and 2012. The target proposed by the former DPJ government was turned down, and Japan lacked a clear strategy for long-term climate mitigation. The analysis provides explanations from a quantitative actor-network perspective. Centrality measures from social network analysis for policy actors in an environmental policy network of Japan were calculated to identify those actors that control the discourse. Data used for analysis comes from the Global Environmental Policy Actor Network 2 (GEPON 2) survey conducted in Japan (2012-13). Science advice in Japan was kept independent from political influence and was mostly excluded from policymaking. One of the two largest discourse coalitions in the environmental policy network promoted a higher CO2 reduction target for international negotiations but favored lowering the target after a new international agreement would have been set. This may explain why Japan struggled to commit to long-term mitigation strategies. Applying social network analysis to quantitatively calculate discourse coalitions was a feasible methodology for investigating "discursive power." But limited in discussing the "practice" (e.g. meetings, telephone, or email conversations) among the actors in discourse coalitions.