• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.1087-1094
• /
• 2009

As online community was revitalized, the internet became the second space for people's everyday life. People enter into a connection with other on-line members and they maintain and extend their relationships. Such relationships can be analyzed and visualized with social network analysis. The method oftentimes envisions the structural elements of complex social life. The study aims at visualizing the relationships among the Cyworld users and designs an application "Blow Blow Your Pinwheel", the main purpose of this application is visualizing social relationships between ego and '1chons' which is a concept of friendship in Cyworld. Designing such an application, the study focuses on closeness of relationships which we think is composed of 1)proximity 2)similarity, 3)familiarity, and 4)reciprocity. The study used these concepts in measuring the strength of relationship between ego and other 1chons(friends). Specifically, we devised survey questionnaires which asked users to evaluate the importance of the above factors of closeness, and implemented the result in calculating the strength of the relationship between ego and other by giving weights for each factor. These measurements then were applied in visualizing the relationships in the application, we designed. Through the application, we can compare on-line relationships with off-line relationships and attempt for the new approach of Social Networks.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.30 no.2
• /
• pp.182-191
• /
• 2024

Purpose: The purpose of this study was to explore the characteristics of social networks among registered nurses in acute nursing care units. Methods: This study used a survey design. Four nursing units from two acute hospitals were selected using a convenience method, and 83 nurses from those nursing units participated in the study in July 2022. The positive influences among nurses included friendship, collaboration, advice, and referent networks, and the negative influences included avoidance and bullying networks. Using the NetMiner program, the k-means clustering technique was applied to create groups of nodes with similar characteristics. The general characteristics of the participants were analyzed by mean, standard deviation, frequency, and ANOVA or chi-squared test. Results: As a result of dividing the 83 nurse participants into four clusters, positive influencers, silent peers, unwelcome peers, and active bullies were identified. Positive influence group nurses were frequently mentioned in the friendship, collaboration, advice, and referent networks. On the other hand, nurses in the unwelcome group and the active bullying group were frequently mentioned in the avoidance and bullying networks. Conclusion: Social networks that have a positive or negative impact on nursing performance are created through different relationships between nurses. Nurse managers can use the findings to create a more supportive and collaborative environment. Further research is needed to develop intervention programs to improve interactions and relationships between fellow nurses.

• Journal of Communications and Networks
• /
• v.17 no.2
• /
• pp.126-132
• /
• 2015

In mobile computing research area, it is highly desirable to understand the characteristics of user movement so that the user friendly location aware services could be rendered effectively. Location based social networks (LBSNs) have flourished recently and are of great potential for movement behavior exploration and datadriven application design. While there have been some efforts on user check-in movement behavior in LBSNs, they lack comprehensive analysis of social influence on them. To this end, the social-spatial influence and social-temporal influence are analyzed synthetically in this paper based on the related information exposed in LBSNs. The check-in movement behaviors of users are found to be affected by their social friendships both from spatial and temporal dimensions. Furthermore, a probabilistic model of user mobile behavior is proposed, incorporating the comprehensive social influence model with extent personal preference model. The experimental results validate that our proposed model can improve prediction accuracy compared to the state-of-the-art social historical model considering temporal information (SHM+T), which mainly studies the temporal cyclic patterns and uses them to model user mobility, while being with affordable complexity.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.22 no.3
• /
• pp.505-514
• /
• 2012

Because people usually establish their online social network based on their offline relationship, the social networks (i.e., the graph of friendship relationships) are often used to share contents. Mobile devices let it easier in these days, but it also increases the privacy risk such as access control of shared data and relationship exposure to untrusted server. To control the access on encrypted data and protect relationship from the server, M. Atallah et al. proposed a hop-based scheme in 2009. Their scheme assumed a distributed environment such as p2p, and each user in it shares encrypted data on their social network. On the other hand, it is very inefficient to keep their relationship private, so we propose an improved scheme. In this paper, among encrypted contents and relationships, some authenticated users can only access the data in distributed way. For this, we adopt 'circular-secure symmetric encryption' first. Proposed scheme guarantees the improved security and efficiency compared to the previous work.

• Korean Journal of School Psychology
• /
• v.17 no.1
• /
• pp.1-16
• /
• 2020

This study aims to investigate peer socialization processes on early adolescents' prosocial behaviors in friendship networks. A longitudinal social network model (SIENA) was used to disentangle socialization process in prosocial behavior. Participants were fourth and fifth graders in South Korea from 39 elementary school classrooms (N=1,040, 48% girls). According to results, students select friends based on similarity in prosocial behavior (peer selection) was found in both prosocial behaviors. Peer influence effects were also observed in prosocial behaviors. Also, moderating effect of social relatedness was significant. In classes with high social relatedness, influence effect of prosocial behavior was significant. As a contrast, prosocial behavior was not socialized in classes with the low social relatedness. Results suggest that peernetwork play a critical role in the co-evolution of friendships, and prosocial behaviors. Findings yielded the importance of the socialization process and promoting healthy peer socialization environment.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.3
• /
• pp.178-188
• /
• 2009

A blog is a personal website where its owner publishes his/her articles for others. A blog can have relationships with other blogs. In this paper, we define a network that is composed of blogs connected together with such relationships as a blog network. Blog networks can have two different propensities characterized by the articles published in the blogs: information-valued propensity and friendship-valued propensity. The degree of each propensity of a blog network plays an important role in deciding business policies for blog networks. In this paper, we address the problem of determining the degrees of two propensities of a given blog network. First, we determine the degree of the propensity of every relationship, a basic unit of a blog network, by using classification that is one of data mining functionalities. Then, by utilizing the result thus obtained, we compute the degrees of two propensities of the whole blog network. Also, we propose a method to solve the problem that the degree of propensities depends on the size of blog networks. To verify the superiority of the proposed approach, we perform extensive experiments using a huge volume of real-world blog data. The results show that our approach provides high accuracy of around 93% in determining the degrees of both propensities of relationships between arbitrary two blogs. We also verify the applicability of the proposed approach by showing that if determines the degrees of the information-valued and friendship-valued propensities correctly in real-world blog networks.

• The Journal of Information Systems
• /
• v.23 no.1
• /
• pp.53-71
• /
• 2014

The center of networking is moving toward mobile from PC based computing environment. The number of smartphone users are increasing rapidly today. One of the most popular smart phone applications is mobile SNS such as Kakao Story, Facebook, Twitter, Mobile Cyworld, etc. Mobile SNS means social network services based on mobile communication technology. This research focused on mobile SNS usage of married women who have not enough time for face-to-face communication with their friends to enhance their friendship. Married women in their 30s and 40s have lots of things to do like housework and caring their children. Mobile SNS would help their communication in aspect such of free of space and time. Through Mobile SNS married women can reinforce their personal relationship and self-esteem. Social Information Processing Theory (SIP) is an interpersonal communication theory developed by Walther(1992). Once established, online personal relationships may demonstrate the same relational dimensions and qualities as face-to-face relationships. The theory explains how people get to know one another online, without nonverbal cues, and how they develop and manage relationships in the computer-mediated environment. The result of empirical analysis indicates that marred women's Mobile SNS activities reinforce their personal relationship and self-esteem.

• Journal of Digital Contents Society
• /
• v.12 no.3
• /
• pp.383-390
• /
• 2011

The purpose of this study was to examine major motivations for using SNSs and the effect of them on SNS participation. In order to address the research questions, 253 undergraduate and graduate students participated. Results of the study were summarized as follows. First, Cyworld was mainly used followed by Facebook and Twitter. Most of the respondents had access to SNSs via smart devices. The average frequency of SNS use was 1-3 times a day and they used them less than 30 minutes a time. The reasons why they started to use SNSs were mainly to follow current trends, maintain friendship, and accept acquaintances recommendations. Second, the result of component analysis derived four primarily underlying dimensions related to SNS use; self-satisfaction, social interaction, recreation, and information seeking. Third, both self-satisfaction and social interaction motivation had significant correlation with SNS participation. The results of multiple regression analysis showed that self motivation was more influential on active participation than social interaction and information seeking motivation.

• Korean Journal of Social Welfare
• /
• v.38
• /
• pp.234-254
• /
• 1999

Volunteering has been defined as a form of altruistic helping behavior directed at improving other's welfare. Volunteering is, however, also identified as a type of collective action for community welfare. In this regard, this study tests whether neighborhood member's network and collective identity are more important determinants to explain participation in volunteer work than altruistic or normative motivation. This study estimates a model in which volunteering is determined by empathy, normative beliefs, neighborhood networks(friendship, contacts, and integration), and identity as a neighborhood member. This study shows that empathy, normative beliefs, and collective identity as a neighborhood member have significant impacts on participation in volunteer work. In addition, this study reveals that neighborhood member's network has an indirect impact on volunteering through identity as a neighborhood member. These results suggest that neighbor-hood community member's ties and collective identity are important sources for community welfare and collective volunteer work.

• Korean Journal of School Psychology
• /
• v.18 no.1
• /
• pp.31-48
• /
• 2021

The purpose of this study was to determine whether the retention of university freshmen could be predicted using their peer relationships in a specific department. In this study, retention was defined as a student staying enrolled in their university for a certain period of time. Social relationships are formed through interaction between people, so both students' self-perceptions and others' perceptions of them must be accounted for, so we used a social network analysis that did so. We examined social networks visualizations that allowed for a rich interpretation of numerical information. Participants in this study were freshmen who enrolled in an undergraduate program in 2017, 2018, or 2019. We used the name generator method to determine how quantitative friendship network variables predicted the academic retention up to the first semester of 2020. Cox proportional hazard model analysis showed that the weighted indegree centrality with intimacy positively predicted retention. The results of this study can be used to identify and conduct interventions for students who may be likely to disenroll. However all of the students did not participate in the department, it was difficult to examine their entire peer networks. Thus, this study's results cannot be generalized because the participants are students of a specific major, so further research is needed to produce more generalizable results.