• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.68-79
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• 2021

On the Social Internet of Things (SIoT), social activities occur through which the vehicle generates a variety of data, shares them with other vehicles, and sends and receives feedbacks. In order to share reliable information between vehicles, it is important to determine the reliability of a vehicle. In this paper, we propose a vehicle trust evaluation scheme to share reliable information among vehicles. The proposed scheme calculates vehicle trust by considering user reputation and network trust based on inter-vehicle social behaviors. The vehicle may choose to scoring, ignoring, redistributing, etc. in the social activities inter vehicles. Thereby, calculating the user's reputation. To calculate network trust, distance from other vehicles and packet transmission rate are used. Using user reputation and network trust, local trust is calculated. It also prevents redundant distribution of data delivered during social activities. Data from the Road Side Unit (RSU) can be used to overcome local data limitations and global data can be used to calculate a vehicle trust more accurately. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.185-196
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• 2018

This study investigates the social network among authors to improve the quality of Panel researches. Korea Health Panel (KHP), implemented by the collaborative work between KIHASA (Korea Institute for Health and Social Affairs) and NHIC (National Health Insurance Service) since 2008, provides a critical infrastructure for policy making and management for insurance system and healthcare service. Using bibliographic data extracted from academic databases, eighty articles were extracted in domestic and international journals from 2008 to 2014, April. Data were analyzed by NetMiner 4.0, social network analysis software, to identify the extent to which authors are involved in healthcare use research and the patterns of collaboration between them. Analysis reveals that most authors publish a very small number of articles and collaborate within tightly knit circles. Centrality measures confirm these findings by revealing that only a small percentage of the authors are structurally dominant, and influence the flow of communication among others. It leads to the discovery of dependencies between the elements of the co-author network such as affiliates in health panel communities. Based on these findings, we recommend that Korea Health Panel could benefit from cultivating a wider base of influential authors and promoting broader collaborations.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.31-40
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• 2023

Objectives: This study investigated the effect of cognitive impairment on the association between social network properties and mortality among older Korean adults. Methods: This study used data from the Korean Social Life, Health, and Aging Project. It obtained 814 older adults' complete network maps across an entire village in 2011-2012. Participants' deaths until December 31, 2020 were confirmed by cause-of-death statistics. A Cox proportional hazards model was used to assess the risks of poor social network properties (low degree centrality, perceived loneliness, social non-participation, group-level segregation, and lack of support) on mortality according to cognitive impairment. Results: In total, 675 participants (5510.4 person-years) were analyzed, excluding those with missing data and those whose deaths could not be verified. Along with cognitive impairment, all social network properties except loneliness were independently associated with mortality. When stratified by cognitive function, some variables indicating poor social relations had higher risks among older adults with cognitive impairment, with adjusted hazard ratios (HRs) of 2.12 (95% confidence interval [CI], 1.34 to 3.35) for social nonparticipation, 1.58 (95% CI, 0.94 to 2.65) for group-level segregation, and 3.44 (95% CI, 1.55 to 7.60) for lack of support. On the contrary, these effects were not observed among those with normal cognition, with adjusted HRs of 0.73 (95% CI, 0.31 to 1.71), 0.96 (95% CI, 0.42 to 2.21), and 0.95 (95% CI, 0.23 to 3.96), respectively. Conclusions: The effect of social network properties was more critical among the elderly with cognitive impairment. Older adults with poor cognitive function are particularly encouraged to participate in social activities to reduce the risk of mortality.

• Journal of Families and Better Life
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• v.11 no.1
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• pp.176-190
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• 1993

This study intended to analyze the size and composition of social network and to identify their related variables in urban nuclear families. Data were collected through the questionnaires by wives living in Seoul area. The methods of statistical analysis used in the study were the frequency mean percentile and one-way ANOVA. The findings were as follows; 1) The size of social network in urban nuclear families was 10.0 in average and 2-33 in range. 2) The composition of social network were 45.5% in relatives 20.6% in neighbors. 21.8% in friends. 4,7% in coworkers, 4.1% religious group members 2.1% in associational members. and 1.4% in formal supporters. 3) The birth order of husbands was related to the size of social network. The composition of social network was influenced by SES family life cycle husband's birth order housing type residence duration age education employment religion and familism.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.1-21
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• 2015

This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watching network) as a useful information source for personalized recommendations. In this paper, we recommend scientific articles of interests by using the shared interests between target users and their watching connections. Our recommendations are based on one typical social bookmarking system, CiteULike. The watching network-based recommendations, which use a much smaller size of user data, produces suggestions that are as good as the conventional Collaborative Filtering technique. The results demonstrate that the watching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filtering recommendations. This study shows the expandability of social network-based recommendations to the new type of online social networks.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.139-146
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• 2016

This study proposes a methodology to analyse social networks among participating design engineers during product development projects. The proposed methodology enables product development managers or the participating design engineers to make a proper decision on product development considering the performance of participating design engineers. It considers a product development environment where an integrated product data management (PDM) system manages the product development data and associated product development processes consistently in its database, and all the design engineers share the product development data in the PDM database for their activities in the product development project. It provides a novel approach to build social networks among design engineers from an operational product development data in the PDM database without surveys or monitoring participating engineers. It automatically generates social networks among the design engineers from the product data and relationships specified by the participants during the design activities. It allows analysts to gather operational data for their analysis without additional efforts for understanding complex and unstructured product development processes. This study also provides a set of measures to evaluate the social networks. It will show the role and efficiency of each design engineers in the social network. To show the feasibility of the approach, it suggests an architecture of social network analysis (SNA) system and implemented it with a research-purpose PDM system and R, a statistical software system. A product configuration management process with synthetical example data is applied to the SNA system and it shows that the approach enables analysts to evaluate current position of design engineers in their social networks.

• Korean Journal of Child Studies
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• v.27 no.4
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• pp.165-184
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• 2006

This ethnography explored the construction of a social network and its function in a classroom of toddlers in a day-care center located in Vermont. The classroom activities of 9 two-year-old toddlers were observed for about two months, compiled and categorized. Then, the themes of psychological functions were reconstructed in data analysis. Results showed that toddlers constructed multiple relations with all peers beyond the dyadic. They also transmitted information to teachers as well as peers in indirect ways. These direct-multiple interactions as well as indirect interactions reflect the social network of Lewis' (2005) theory. In the construction of social networks, the toddlers developed communication skills, turn-taking skills, leadership, and imitation.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.1-7
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• 2014

We consider a human contact social network that has connections through cellphone addresses. To construct such a social network, we use real call records provided by a large carrier, and connect to each other if there exists a call record between any two cellphone users. Due to its huge amount of data, we down-sample it in a way that the smallest-degree nodes are removed, in turn, from the network. For a moderate size of the networks we show that the degree distribution of the network follows a power-law distribution via linear regression analysis, implying the so-called scale-free property. We finally suggest some alternative measures to analyze a social network.

• Journal of the HCI Society of Korea
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• v.12 no.2
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• pp.13-19
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• 2017

Various life-logging based on cloud service have developed social network according to the advanced technology of smartphone and wearable device. Daily digital life on social networks has been shared information and emotion and developed new social relationships. Recent life-logging has required social relationships beyond extension of personal memory and anonymity for privacy protection. This study is to determine social network group by using life-logging data obtained in daily lives and to categorize emotion behavior with anonymity guarantee. Social network group was defined by grouping similar representative emotional behavior. The public's patterns and trends was able to be inferred by analyzing representative emotion and behavior of the social groups network.