• Journal of Digital Contents Society
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• v.14 no.1
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• pp.41-50
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• 2013

Social network analysis use the n nodes with l connections. About dozens or hundreds number of nodes are reasonable for social network analysis to the entire data. Beyond such number of nodes it will be difficult to analyze entire data. Therefore, it is necessary to separate the whole social networks, a method that can be used at this time is Clustering. You will be able to easily perform the analysis of the features of social networks and the relationships between nodes, if sub-group consists of all the nodes by Clustering. Clustering algorithm needs the interaction with the user and computer because it is need to pre-set the number of sub-groups. Sub-groups generated like this can not be guaranteed optimal results. In this paper, we propose dynamic sub-groups creating method using the external community association. We compared with previous studies by the number of sub-groups and sub-groups purity standards. Experimental results show the excellence of the proposed method.

• Journal of Family Resource Management and Policy Review
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• v.28 no.1
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• pp.13-25
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• 2024

The rate of single-person households has been increasing all over the world, and there has been a particularly rapid increase in them in Korea. Single-person households show unique and various characteristics related to the reasons for becoming a single-person household, gender, life cycle, and so on. Thus, research needs to focus on the specific groups of single-person households in order to provide tailored policies and programs. This study segmented single-person households in three groups based on life cycle: young, middle-aged, and older adults. Differences in the level of healthy lifestyle, as well as factors affecting that, were investigated according to the groups. The data were collected in 2022, with 237 respondents from single-person households in Kimpo. Descriptive statistics, t-test, ANOVA, and multiple regression analysis were conducted. The overall level of healthy lifestyle was found to be significantly higher for young adults compared to older adults. Results from multiple regression show that significant factors related to the healthy lifestyle of single-person households were gender, educational attainment, whether becoming a single-person household was voluntary, and whether the respondents had experienced discrimination as a single-person household. Significant factors differed by the sub-categories of the healthy lifestyle scale. This study has implications related to discovering differences in the level of healthy lifestyles of single-person households through examining the factors affecting it according to life cycle.