• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.656-661
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• 2008

There are many sociological methodology for the study on cyber community. Especially for the online social network which is constructed by the notion of the social network, the social network analysis can be a superior methodology for the understanding of the general phenomenon and the solutions for the problematic issues. As pointed by Manuel Castells, the problem of the unification and the fragmentation, which is came after the participation and the openness, is prevailed in cyber community by its characteristics. However, computational properties that exceed the limitation of the time and space can bestow other alternatives. The Open API in the social network services that is more popular in these days is the one of those alternatives. Therefore, the purpose of this study is to investigate the problematic phenomenon of online social network and to search the solutions for those problems with the acceptance of Open API technology.

• Journal of Korean Academy of Nursing
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• v.38 no.3
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• pp.372-382
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• 2008

Purpose: The purpose of this study was to develop a multidimensional suicide prevention program for Korean elders by utilizing a community network and to evaluate its effect. Methods: A non-equivalent control group pretest-posttest design was used. The subjects were recruited from two different elderly institutions located in D city and K province, Korea. Nineteen subjects in the control group received no intervention and 20 subjects in the experimental group received a multidimensional suicide prevention program. Results: There were more significant decreases in depression, suicide ideation, and increases in life satisfaction in the experimental group compared to the control group. Conclusion: According to the above results, the multidimensional suicide prevention program for Korean elders decreased stressful events like depression, and suicide ideation and increased life satisfaction through the community network. These findings suggest that this program can be used as an efficient intervention for elders in a critical situation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2142-2161
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• 2018

Distance dynamics model is an excellent model for uncovering the community structure of a complex network. However, the model has poor robustness. To improve the robustness, we design an enhanced distance dynamics model based on Ego-Leader and propose a corresponding community detection algorithm, called E-Attractor. The main contributions of E-Attractor are as follows. First, to get rid of sensitive parameter ${\lambda}$, Ego-Leader is introduced into the distance dynamics model to determine the influence of an exclusive neighbor on the distance. Second, based on top-k Ego-Leader, we design an enhanced distance dynamics model. In contrast to the traditional model, enhanced model has better robustness for all networks. Extensive experiments show that E-Attractor has good performance relative to several state-of-the-art algorithms.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.

• Journal of Korean Society of Rural Planning
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• v.26 no.1
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• pp.39-49
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• 2020

The study analyzed the frequency of simultaneous occurrence of keywords presented in a total of 805 papers published in domestic journals from 1995 to 2019 by social network analysis(SNS) method, and examined core keywords of each period(5 years), in order to understand the research trends of the rural residential environment. The main results are as follows. First, as a result of the analysis of centrality, 'Community', 'Tourism' and 'Comprehensive Rural Village Development Project' were the top 3 keywords. Second, examined by each period, the top keywords are 'Eco Friendly' in 2000~2004, 'Tourism' in 2005~2009 and 2010~2014, 'Community' in 2015~2019. Third, comparing the structural characteristics of core keywords 2nd, 3rd, and 4th period, a network centering on 'Tourism' was clearly formed in the 2nd period. 'Tourism' was divided into 'Community' and a movement to form a separate group appeared in the 3rd period. In the 4th period, 'Community' was found to form a network without direct connection with 'Tourism'. The results of this study suggest the trend change of viewpoint for the rural area in the domestic research on rural residential environment. It has been confirmed that while the research had been carried out with the viewpoint of rural area as a 'tourist attraction' or 'sightseeing spot' for the urban citizens until the mid-2010s, in the research of late 2010s the viewpoint has settled down as a 'residential space' or 'space for new economic activities' of a variety of rural residents.

• The Journal of Information Systems
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• v.33 no.1
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• pp.45-68
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• 2024

Purpose This paper examines the role of local market-based communities in driving regional revitalization, using detailed analysis of online networks. We aim to dissect a local community's communication network, highlighting members with high engagement levels and exploring their characteristics. Our goal is to identify the conditions that allow local community networks to grow independently and to demonstrate how the activation of these networks contributes to regional revitalization. Design/methodology/approach We employ a mixed-methods approach, combining social network analysis with statistical techniques to investigate the structure of online communication networks. Specifically, we use ANOVA to determine the statistical significance of our findings, ensuring their reliability. To complement our quantitative data, we include qualitative insights from interviews, adding depth and context to our analysis. Findings Our results show that individuals with high centrality in the online network are crucial for maintaining active local communities. We find that leveraging local resources to create a supportive and adaptable environment is essential for the communities' sustainability and expansion. Importantly, our research draws a direct connection between the vitality of local community networks and the broader process of regional revitalization. We argue that energizing local communities is an effective way to address the risk of regional decline. By integrating quantitative analysis with qualitative feedback, this study contributes to the understanding of local market-based communities as key drivers of regional development. It emphasizes the importance of building vibrant, resourceful community networks to revitalize areas experiencing socio-economic challenges.

• Knowledge Management Research
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• v.1 no.1
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• pp.47-64
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• 2000

As the Knowledge Economy grows bigger, studies and practices of knowledge management flourish in almost every organizations. Yet, the studies of fundamental relationships between knowledge and organization have not been sufficiently developed. It is partly because current knowledge management mainly focus on the technical aspects of the theme. This paper tries to find the possible organizing principles and theoretical foundations of knowledge-intensive organizations through the perspective of knowledge market and knowledge community. Based on the differentiation of "knowledge" and "knowing", the author draws several propositions about knowledge creation and knowledge use. Then, the author relates these propositions to the design and implementation of two theoretical models of organizations, i. e. knowledge market and knowledge community. Major claims are: 1) Knowledge use and knowledge creation process are conceptually separable, so that different conceptual models (market & community) need to be applied. 2) Since knowledge use and creation should be integrated, organizations in the Knowledge Economy should be the efficient knowledge market and, at the same time, knowledge community with care and cooperations. 3) The network of independent small KIFs(knowledge-intensive firms) could be considered as the possible organizational model of the future.

• Journal of Information Technology Applications and Management
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• v.23 no.2
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• pp.97-112
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• 2016

Many studies have pointed out that trust is the most important component of social capital. Although there have been lots of attempts to measure level of trust between members of community, it is hard to find studies which examine trust from the standpoint of structural aspects. Because of the recent rapid growth of SNS and openness trend on members and their friendship information, it became possible to understand the structure of trust relationships among users in SNS. This study aims to facilitate interpersonal trust by comparing the structure of the trust network among social network users. For this purpose, it proposes a method to explore the structure of trust network and strategies to evolve toward more open structure. In experiments to distinguish structure of trust network with three social network communities, it is discovered that ADVOGATO has characteristics of open and collective network together whereas EPINION and FILMTRUST have collective and open characteristics respectively.

• Korean Journal of Health Education and Promotion
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• v.29 no.1
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• pp.39-57
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• 2012

Objectives: This study was to measure community capacity using individual-level and organizational-level capacity indicators and illuminated the relationship of community capacity and self-rated health status in two regions in Seoul, Korea. Methods: The data from individual surveys were obtained by quota sampling the residents of two autonomous gu in Seoul (N=1,000). The data from organizational surveys were obtained by snowball sampling lists of organizations in the possession of gu offices with a sampling frame (N=153). The survey tools were 6 indicators regarding residents' social capital and a sense of community and 5 indicators regarding community-based organizations and their networks. The analysis methods consisted of the effect of the components of capacity on health status and social network analysis. Results: As for capacity on individual levels, while D-gu was mainly developed inn individual capacity in terms of social interaction, Y-gu was stronger in a sense of community and cohesion among residents. As for capacity on organizational levels, Y-gu was more developed than was D-gu in associational networks. Conclusion: It is necessary to develop health promotion program per community and to strengthen partnerships with and among grassroots organizations based in local communities through the measurement of community capacity.

• Journal of Korean Society of Rural Planning
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• v.23 no.1
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• pp.1-10
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• 2017

The community bridge node finder, based on the stochastic method of network analysis, can compute hubs spot, which would enable the use of network structures with limited information. However, applying this node finder to heterogeneity networks, which are efficient to analyze the main farm complex in fields and the spread of infectious disease, is difficult. These problems, The most connected point that is called hub is often a major role in the heterogeneity network. In this study, we therefore improved the community bridge node finder to enable it to be applied to heterogeneity networks. We attempted to calculate the bridge node quantitatively by using the modularity of cohesion analysis method and the community bridge node finder. Application of the improved method to the HPAI(Highly Pathogenic Avian Influenza) spread in Korea 2008 produced a quarantine coefficient that was 4 - 37% higher than the quarantine coefficient obtained with the centrality method for the first 14 days after the HPAI outbreak. We concluded that the improved method has the ability to successfully calculate the bridge node in heterogeneity networks based on network structures with scant information, such as those describing the spread of infectious disease in domestic animals. And Our method should be capable to find main farm complex in fields.