• The Korean Journal of Health Service Management
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• v.12 no.2
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• pp.113-123
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• 2018

Objectives : The purpose of this study was to investigate the effect of participation in social activities on the subjective health satisfaction of the elderly in groups with and without chronic diseases. Methods : Data were used from the "2014 the Korean Elderly Survey" and the subjects were 10,451 persons aged 65 years or older. Data analysis was conducted using SPSS 18.0 statistical package. Results : The results of this study were as follows. In the case of the elderly without chronic diseases, only the employment status (${\beta}=.135$, p<.01) had a significant effect on the health of the elderly. In the case of elderly people with chronic illness, participation in lifelong education (${\beta}=.183$, p<.001), participation in social group (${\beta}=.277$, p<.001), volunteer work experience (${\beta}=.060$, p<.05), and employment status (${\beta}=.342$, p<.001) had a significant effect on health. Conclusions : Policies and systems are needed to actively encourage and support the social activities of the elderly. Additionly, care and attention are needed to provide social jobs for the elderly and build a sustainable network.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.105-117
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• 2014

The change of social media market toward multimedia environment makes users select social media according to preference factor's gratification and this also causes competition among various social medias. So this study focused on competition among social media from the perspective of users' gratification while considering multimedia environment of social media market. The widely known Niche theory is used to confirm competitions among media in an environment with limited resource. According to research result, (1) Facebook and Kakao Talk mostly satisfies users' expectations; (2) Facebook and Kakao Talk form leading group and Blog, Youtube and Twitter form chasing group in this competition; (3) Kakao Talk greatly satisfies users' various expectations. The research result implies that, for social media to have competitive advantage in the market, it is better to provide convenience and real-time responsiveness in mobile environment and to improve service so that users could more easily utilize network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3836-3854
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• 2022

The student group division is benefit for universities to do the student management based on the group profile. With the widespread use of student smart cards on campus, especially where students living in campus residence halls, students' daily activities on campus are recorded with information such as smart card swiping time and location. Therefore, it is feasible to depict the students with the daily activity data and accordingly group students based on objective measuring from their campus behavior with some regular student attributions collected in the management system. However, it is challenge in feature representation due to diverse forms of the student data. To effectively and comprehensively represent students' behaviors for further student group division, we proposed to adopt activity data from student smart cards and student attributes as input data with taking account of activity and attribution relationship types from different perspective. Specially, we propose a novel student group division method based on a multi-view student attribute heterogeneous information network (MSA-HIN). The network nodes in our proposed MSA-HIN represent students with their multi-dimensional attribute information. Meanwhile, the edges are constructed to characterize student different relationships, such as co-major, co-occurrence, and co-borrowing books. Based on the MSA-HIN, embedded representations of students are learned and a deep graph cluster algorithm is applied to divide students into groups. Comparative experiments have been done on a real-life campus dataset collected from a university. The experimental results demonstrate that our method can effectively reveal the variability of student attributes and relationships and accordingly achieves the best clustering results for group division.

• 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.

• Korean Journal of Organic Agriculture
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• v.15 no.2
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• pp.131-150
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• 2007

This study explores the development process of an farmers' group in Asan City that now plays an important role in the development of organic farming of the region. While increase in income in general may be one of main purposes making farmers join or form a group, the farmers group in Asan, instead, has tried to form a cooperative of local organic farmers. In doing so, they experienced a lot of difficulties and leant by trial and error. As a result, the farmers' group has recently developed in terms of business and organisational growth. The growth is not merely due to the growth of organic food markets but also due to the strong internal ties and trust that made possible to expand into food processing as well as to do social and cultural activities fur the rural residents. It implies that trust and cooperative identity between farmers should be the most important thing to be locally embedded farmers groups in a specific region.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.538-540
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• 2013

소셜 네트워크 서비스를 이용하는 사람들이 증가하면서, 프라이버시와 관련된 보안 문제들 또한 이슈가 되고 있다. 기존의 소셜 네트워크 서비스들은 일반적으로 중앙 집중형 구조를 가지고 있다. 서비스 사용자들의 기본적인 프로필 정보들은 서비스 제공자에게 수집되어 빅데이터를 이룬다. 이러한 빅데이터가 서비스 제공자 측면에서는 상업적인 용도로 사용되지만, 사용자 개인의 입장에서는 자신의 개인정보가 악의적인 목적으로 사용되는지 전혀 알 수가 없다. 따라서 서비스 제공자의 무분별한 정보 수집 문제를 해결하기 위해 원천적으로 중앙 집중형 구조를 제거하고, 기존의 포털사이트와의 연동을 통해 오픈 아이디로 이용 가능한 오픈 소스 기반 분산형 소셜 네트워크 서비스를 제안한다.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.603-615
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• 2021

The aim of this study was to analyze the semantic network structure of keywords and the visual composition of images extracted from Instagram in relation to the multi-persona phenomenon with in fashion imagery, which has recently been attracting attention. To this end, the concept of a 'secondary character', which forms a separate identity from a 'main character' on various social media platforms as well as on the airwaves, was considered as the spread of multi-persona and #SecondaryCharacter on Instagram was investigated. 3,801 keywords were collected after crawling the data using Python and morphological analysis was undertaken using KoNLP. The semantic network structure was then examined by conducting a CONCOR analysis using UCINET and Netdraw to determine the top 50 keywords. The results were then classified into a total of 6 clusters. In accordance with the meaning and context of the keywords included in each cluster, group names were assigned : virtual characters, relationship with the main character, hobbies, daily record, N-job person, media and marketing. Image analysis considered the technical, compositional, and social styles of the media based on Gillian Rose's visual analysis method. The results determined that Instagram uses fashion images that virtualize one's face to produce multi-persona representation s that show various occupations, describe different types of hobbies, and depict situations pertaining to various social roles.

• Information Systems Review
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• v.17 no.2
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• pp.179-192
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• 2015

Collaborative research has been actively done on the basis of academic relationships among various study area. The importance of collaboration has also been increased. Collaborative researchers can reduce time, cost, and research risk to maximize research productivity. This study aims to develop a framework for understanding the behavior of professional groups through network characteristics. To achieve the goal, we collected data of the co-authored network and that of the reviewer network from from 2006 to 2012. Total 230 submitted papers were analyzed on the views of research performance and productivity. Various analytical methods such as centrality analysis, sub-group analysis, correlation, and regression were conducted for assuring the reliability and validity of our research. The results shows that the productivity of the co-authored network was increased and the efficiency of the reviewer network was also identified through several network indexes.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.587-595
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• 2014

As the number of users of SNS (Social Network Service) and smart devices increases sharply nowadays, many studies on various teaching models and methodologies have been made in order to utilize SNS in education. However, there are not so sufficient studies that explore social media as a learning environment and analyze empirically its relation with the academic achievement. Since various kinds of learning experiences are required in order to foster creative talents, it is necessary to have information sharing, debate and information exchange utilizing SNS. If utilizing SNS for general computer education in a university, it will be possible to collect learners' various thoughts and opinions more effectively. Because real-time feedback can be possible in each individual space through SNS by sharing the information related to the interactions between learner and teacher or between leaner and learner and exchanging opinions each other, the learner's ability to utilize a computer can be improved. Especially SNS can provide a real-time help to solve problems for underachieved students and provide an opportunity to improve the academic achievement.

• The Journal of Information Systems
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• v.30 no.1
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• pp.123-149
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• 2021

Purpose The purpose of this study is to define the anti-ESG activities of companies recognized by media by reflecting ESG recently attracted attention. This study extracts keywords for ESG controversies through association rule mining. Design/methodology/approach A research framework is designed to extract keywords for ESG controversies as follows: 1) From DeepSearch DB, we collect 23,837 articles on anti-ESG activities exposed to 130 media from 2013 to 2018 of 294 listed companies with ESG ratings 2) We set keywords related to environment, social, and governance, and delete or merge them with other keywords based on the support, confidence, and lift derived from association rule mining. 3) We illustrate the importance of keywords and the relevance between keywords through density, degree centrality, and closeness centrality on network analysis. Findings We identify a total of 26 keywords for ESG controversies. 'Gapjil' records the highest frequency, followed by 'corruption', 'bribery', and 'collusion'. Out of the 26 keywords, 16 are related to governance, 8 to social, and 2 to environment. The keywords ranked high are mostly related to the responsibility of shareholders within corporate governance. ESG controversies associated with social issues are often related to unfair trade. As a result of confidence analysis, the keywords related to social and governance are clustered and the probability of mutual occurrence between keywords is high within each group. In particular, in the case of "owner's arrest", it is caused by "bribery" and "misappropriation" with an 80% confidence level. The result of network analysis shows that 'corruption' is located in the center, which is the most likely to occur alone, and is highly related to 'breach of duty', 'embezzlement', and 'bribery'.