• Journal of Korean Public Health Nursing
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• v.30 no.2
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• pp.311-325
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• 2016

Purpose: This study was conducted to examine the individual and community level factors associated with physical activity and to identify its relative effects using a multilevel analysis among Korean adults in certain counties. Methods: A cross-sectional data of 39,547 adults (age range of 19~64 years) living in 82 counties from the 2013 Korean Community Health Survey (KCHS) was analyzed. Individual and social correlates from KCHS and physical environmental data from the Korean Statistical Information Service were collected. A multilevel logistic regression was performed using Stata 10.0 IC. Results: Multilevel analyses showed that the effect of social and physical environmental on engaging in moderate or vigorous physical activity (MVPA) was significant in comparison to the influence of individual correlates. The individual factors that were associated with participating in MVPA included gender, marital status, education, job, and household income. In the community level, social environmental factors associated with engagement in MVPA were higher satisfaction with healthcare service (OR=3.410, 95% CI=1.109~11.269), a high level of social support (OR=5.920, 95% CI=1.459~22.657) and social network (OR=1.025, 95% CI= 1.017~1.032). Conclusion: To promote moderate or vigorous physical activity in Korean adults in some counties, social environmental factors should be considered along with individual correlates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.875-882
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• 2014

The purpose of this study is to examine the effects of social capital on the life satisfaction of the community residents. For the research, social capital was consisted of participation, network, trust and norm. To achieve the purpose of this research, data were collected from 279 citizens of S-city in Gangwon-Do. The results of this study were summarized as follows: Mean analyses showed that social capital had $3.02{\pm}.52$. According to hierarchical multiple-regression, participation(${\beta}$=.26, p<.001), network(${\beta}$=.17, p<.01) and trust(${\beta}$=.16, p<.01) among social capital showed positive influence on life satisfaction of community residents(R2=.35). This study finally discussed theoretical implications for future study and practical implications on the results.

• Korean Journal of Culture and Social Issue
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• v.15 no.4
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• pp.565-589
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• 2009

The present study explored the major components of adaptive game behavior among adolescents in Korea. Based on relevant research and a pilot testing, an Adaptive Game Use Scale (AGUS) was developed and validated. A stratified sampling procedure was used to draw a representative sample, and a total of 600 male and female students from middle schools and high schools in various regions participated in the study. Factor analyses revealed 7 facets of adaptive game behavior, including experiencing vitality, expanding life experience, making good use of leisure time, experiencing flow, exercising control, experiencing self-esteem, maintaining and expanding social network. Internal consistency and temporal stability(4 weeks) of the scale were both high. A confirmatory factor analysis indicated that a 7-factor hierarchical model fits well with the data. Moreover, additional analyses suggested that AGUS and game addiction are conceptually distinct. Correlational analyses also indicated that AGUS has good discriminant validity and concurrent validity. Implications of the findings and future directions were discussed.

• Korean Journal of Social Welfare
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• v.68 no.2
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• pp.185-211
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• 2016

This study analyzes key word networks of the papers which are published at Korean Journal of Social Welfare issued by Korean Academy of Social Welfare from 1979 to 2015. It aims at investigating the trends of social welfare researches in Korea by dividing the given period into two: 1979-2000 and 2001-2015. It shows the trends in three ways: methodologies, subjects, and intellectual structures. In order to identify intellectual structure, it calculate centrality indices basing on co-appearance frequency of key words. It also derives some values which explain relationship structure of key words by using pathfinder algorithm, and finally visualizes the intellectual structures by using the NodeXL program. Some implications of the findings of these analyses are discussed in the end.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.163-168
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• 2020

In this paper we propose a The purpose of this study was to examine the psychological characteristics of youth mobile phone use. Internally, we want to find out about self-regulation, interpersonal relationship, pleasure, and desire to achieve reality. For the research, the Korea Information Society Agency utilized 568 data based on self-control and user motivation among long-term tracking data of Internet and mobile phone addiction in 2018. The SPSS window 23 version was used for data analysis, and the data collected were analyses to identify the subject's demographic characteristics. In addition, the correlation of variables between groups was investigated by analyzing dummy variables, and the results of the study were as follows. First, the addiction was slightly higher in mobile phone game groups than in social network service (SNS) groups, but in the same period of use, social network service (SNS) groups showed a higher desire for interpersonal relationships. In the desire to avoid reality, mobile phone game groups showed a higher gap than social network service (SNS) However, there was no difference between groups in terms of pleasure and desire to achieve. The results of this study indicated that the content of mobile phone use differed in factors affecting mobile phone overuse, and suggestions for follow-up research were discussed.

• Journal of Gifted/Talented Education
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• v.26 no.2
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• pp.347-363
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• 2016

The purpose of this study was to analyze the trends in domestic and international gifted education in the last six years (2010-2015) by utilizing social network analysis methods. For papers of gifted education in Korea, two KCI (Korea Citation Index) rated journals, the 'Gifted/Talented Education' (The Korean Society for the Gifted) and 'Gifted and Talented Education' (The Korean Society for the Gifted and Talented Education) were selected and 457 pieces published in two journals were collected. The papers of 347 published in SSCI rated journals, 'The Gifted Child Quarterly,' 'Journal for the Education of the Gifted,' and 'High Ability Studies' were selected. English keywords were extracted from 457 papers from Korean journals and 347 papers from foreign journals and the Social Network Analysis (SNA) way was utilized for keyword frequency and central network analyses. It was appeared that the trends of paper keywords from domestic and foreign countries showed common keywords, 'academically gifted', 'science gifted', and 'gifted' as center keyword frequency, and keywords, 'achievement', 'identification', 'intelligence' appeared as the most frequent ones. For domestic papers, keywords, 'creativity', 'gifted education', and 'gifted education teacher' were the highest frequent keywords while keywords, 'foreign countries', and 'student attitudes' were most frequent ones for the foreign countries. For the analysis of papers from five journals as one group, it was found that keywords, 'identification', 'intelligence', and 'achievement' were the most important common ones and keywords, 'cognitive', 'motivation', and 'self-concept' were appeared as important keywords. The trend of gifted education in Korea seems to be different from ones of foreign countries, domestic papers of gifted education rarely included keywords of 'foreign examples', 'student attitudes', and 'gender differences.' Consequently, the trend of gifted education in Korea called for various research perspectives.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.1
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• pp.31-50
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• 2005

The purpose of this study is to analyse the role of the inter-regional knowledge network in the knowledge based economic development of regions, using regional data collected over the IMF financial crisis between 1996 and 2001. In particular, the major questions about the inter-regional knowledge network in terms of regional innovation are as follows. First, how can be distinguished the inter-regional knowledge networks among the regions? Secondly, what is the relationship between the real object economy and the inter-regional knowledge network? To answer rho questions listed above, the social network analysis is used to examine the association between the intra-regional knowledge linkage structure and the change of the real object economy. For the empirical analyses, regional labour data for 16 Metropolitan Areas(Si) and Provinces(Do) from 1996 to 2001 are used. The findings of the study suggest that there is a significant positive relationship between the concentration of the inter-regional knowledge linkage and a rate of economic growth of the real object economy and that there is a negative correlation between the density and the standard deviation of the inter-regional knowledge linkage and the rate.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.39-51
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• 2019

This study attempts to investigates big data of marital relationships of Kimhae Kim's family on their genealogy. Through the network analysis, how the relationship between families have been structured and changed longitudinally from 1500s to 1800s. Results showed that the network sizes had increased and centralizations had decreased gradually. However, the results indicated that some families were stably located in the central position on the networks. This study suggests that data on genealogy can be used for big data and social network analyses.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.109-125
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• 2013

As the number of SNS users is increasing, it has been very important how companies use SNS strategically. As a result, studies have been performed for the utilization of SNS. Most of the studies, however, focused on the overall characteristics of SNS and did not consider the characteristics of individual SNS. This study classified the main purpose of SNS use as relation-oriented purpose and information-oriented purpose, and identified the types of SNS from two viewpoints : service type and openness. Based on the classification, this study identified the characteristics of Cyworld, Facebook, and Twitter respectively, and analyzed the difference of the purpose of SNS users according to the characteristics of each service. The results showed that more users had the information-oriented purpose in the order of Twitter, Facebook, and Cyworld. There was no difference in the relation-oriented purpose among the three services. The analyses of the motive to join a group or a party made similar results. The results of additional analyses showed that the ratio of users with many acquaintances was high in the order of Facebook, Twitter, and Cyworld. In addition, more users checked their timeline or news feed more frequently in the order of Facebook, Twitter, and Cyworld.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.334-342
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• 2022

Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.