• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.46-54
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• 2022

The existing methods for determining influence in social networks do not accurately determine the influence of users because they do not delete or update existing relationships before they stop in the face of an increasing number of inactive users on social networks. In this paper, we propose a user influence detremination method using the temporal k-shell decomposition technique based on the creation date of users of social networks. To solve the problem of increasing influence of old users in social networks, we apply k-shell decomposition and age-specific order centrality as attenuation coefficients due to aging in neighbors. The age-decaying k-shell decomposition and age-specific order centrality are searched for influential users at the present time by applying the attenuation coefficient and age-dependent weights. Various performance evaluations are performed to show the superiority of the proposed method.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.1-12
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• 2022

The purpose of this study is to identify the social perception characteristics of young children with disabilities over the past decade. For this purpose, Textom, an Internet-based big data analysis system was used to collect data related to young children with disabilities posted on social media. 50 keywords were selected in the order of high frequency through the data cleaning process. For semantic network analysis, centrality analysis and CONCOR analysis were performed with UCINET6, and the analyzed data were visualized using NetDraw. As a result, the keywords such as 'education, needs, parents, and inclusion' ranked high in frequency, degree, and eigenvector centrality. In addition, the keywords of 'parent, teacher, problem, program, and counseling' ranked high in betweenness centrality. In CONCOR analysis, four clusters were formed centered on the keywords of 'disabilities, young child, diagnosis, and programs'. Based on these research results, the topics on social perception of young children with disabilities were investigated, and implications for each topic were discussed.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.187-196
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• 2020

This study attempted to examine the structural characteristics of the social network of nursing units by dividing them into a job-related advice network and a friendship network, and to analyze the relationship between nurse organizational commitment and intent to leave. The subjects were 420 nurses working in 4 hospitals and 30 nursing units. Data were analyzed using UCINET 6.0, SPSS 20.0 and HLM 7.0. In job-related advice networks, degree centrality of head nurse contributed to organizational commitment. Network density contributed to intent to leave. In friendship networks, closeness centrality of head nurses and betweenness centrality of charge nurse contributed to organizational commitment. Density and betweenness centrality of charge nurses contributed to intent to leave. Accordingly, it is necessary to foster good relationships between nurses and to develop various types of strategies for building effective networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.295-301
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• 2018

In various disciplines, researchers, not single researchers, tend to cooperate to study the same topic. There are many studies to analyze the collaborative form of various researchers through the social network analysis method, but there are few such studies in the computer field. In this paper, we analyze the characteristics of network and various groups of researchers through the social network analysis technique of the co-authors of the Journal of Korea Institute of Information and Communication Engineering, and analyze the degree centrality, the between centrality and edge weight. As a result of the analysis, many groups were extracted from the co-author's network, but the top 20 groups accounted for more than 50% of the total, also, we could find a pair of researchers who do joint research with a very high frequency. These Co-author networks are expected to be the basis for in-depth research on the subject and direction of research through future researches.

• Journal of The Korean Association of Information Education
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• v.11 no.3
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• pp.379-387
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• 2007

The purpose of the study was to explore the correlation between in-degree and out-degree centrality Social Network Indices and cognitive and affective learning outcomes measures in an e-Learning environment. Results indicate both the out-degree and in-degree centrality indices are correlated with the cognitive learning outcome measures only. Further, results of the follow-up multiple regression analyses describe the cognitive learning outcome would be predicted by both the in-degree centrality (52%) and out-degree centrality (8%). A discussion is provided to interpret the results and limitations are specified.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1414-1423
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• 2014

This paper aims to analyze destination composition patterns included in package products and to identify the characteristics of the tourism destinations through social network analysis using data collected from tour packages distributed by major Korean travel agencies, targeting Singapore as a key destination. Such tour package data were transcribed into data matrix using Pajek, UCINET, and Cytoscape for analysis. The density and centralization scores derived from the analysis indicated clearly that each destination was almost connected to each other. The centrality scores indicated that the destinations with higher degree of centrality also has higher betweenness centrality within the network. Based on centrality scores, POI(point of interests) of tourism destinations showed concentration in southern area of the target region. Finally, through component analysis, subgroups of tourism destination networks are isolated. Practical implications were also presented for industry practitioners.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.209-217
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• 2013

This study focuses on the analysis of purchased items' relationship occurred by consumers' purchasing behavior observed in on-line shopping mall based on social network analysis. In order to find relational characteristics of each item for establishing marketing strategy, we apply three definitions of centrality in network, which are degree centrality, betweenness centrality, and closeness centrality in the purchased items' network. Thus, the research results provide the criteria for selection of market segmentation variables. Furthermore, the details of case has been introduced to validate the analyzed results in terms of marketing strategy, and supporting evidences are provided accordingly.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.390-394
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• 2009

The semantic web-based social network is highly useful in a variety of areas. In this paper we make diverse analyses of the FOAF-based social network, and propose an expert recommendation system. This system presents useful method of ontology-based social network using SparQL, RDFS inference, and visualization tools. Then we apply it to real social network in order to make various analyses of centrality, small world, scale free, etc. Moreover, our system suggests method for analysis of an expert on specific field. We expect such method to be utilized in multifarious areas - marketing, group administration, knowledge management system, and so on.

• The Journal of Information Systems
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• v.25 no.1
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• pp.135-158
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• 2016

Purpose Virtual communities change the way people communicate and share information. The purpose of this paper is to find how internet social capital and individual motivations influence the information sharing in virtual communities. This study considers the social capital theory, individual motivations, information sharing, and community promotion to construct a theoretical model. Design/methodology/approach Social capital focuses on three dimensions that include 6 factors: social interaction ties, centrality, shared language, shared vision, trust and reciprocity. Individual motivations include 2 factors: reputation and enjoy helping. To confirm the research model and the hypotheses, 426 effective questionnaires were used for the final analysis. Findings The result of data analysis demonstrates that social interaction ties, centrality, shared language, trust, and reciprocity were significant in affecting information sharing behaviors. However, reputation, enjoy helping, and shared vision does not appear to have a significant influence on information sharing behaviors. The information sharing was positively related to community promotion.

• Journal of Korean Library and Information Science Society
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• v.44 no.4
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• pp.443-463
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• 2013

Korea Institute of Science and Technology Information(KISTI) provides domestic researchers with science and technology information through NDSL Information Document Service(NIDS) network to improve research productivity in Korea. University libraries and information centers of research institutes are playing a major role in the NIDS collaboration network. In this study, we examined the relationship among the participating organizations for document delivery service using the social network analysis(SNA) method. Centrality of each organization in the NIDS network was analyzed with the indexes such as degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. The research results show that KISTI, KAIST, POSTECH, and FRIC are located at the center of the NIDS network. Based on the research results, this paper suggests several directions for improvement of document delivery service.