• ETRI Journal
• /
• v.43 no.5
• /
• pp.812-824
• /
• 2021

Recently, with an increase in Internet usage, users of online social networks (OSNs) have increased. Consequently, privacy leakage has become more serious. However, few studies have investigated the difference between privacy and actual behaviors. In particular, users' desire to change their privacy status is not supported by their privacy literacy. Presenting an accurate measurement of users' privacy status can cultivate the privacy literacy of users. However, the highly interactive nature of interpersonal communication on OSNs has promoted privacy to be viewed as a communal issue. As a large number of redundant users on social networks are unrelated to the user's privacy, existing algorithms are no longer applicable. To solve this problem, we propose a structural similarity measurement method suitable for the characteristics of social networks. The proposed method excludes redundant users and combines the attribute information to measure the privacy status of users. Using this approach, users can intuitively recognize their privacy status on OSNs. Experiments using real data show that our method can effectively and accurately help users improve their privacy disclosures.

• Knowledge Management Research
• /
• v.12 no.2
• /
• pp.69-80
• /
• 2011

This paper reports on a structural view of a knowledge network comprised of clubs and organisationsexpressly concerned with cultural activities in a regional Australian city. Social network analysis showed an uneven distribution of power, influence, and prominence in the network. The network structure consisted of two modules of vertices clustered around particular categories of creative arts and these modules were linked most frequently by several organisations acting as communication hubs and boundary spanners. The implications of the findings include 'network weaving' for improving the network structure and developing a systemic approach for exploring the structures of social action that form community-based knowledge networks.

• Korean Journal of Human Ecology
• /
• v.21 no.3
• /
• pp.469-488
• /
• 2012

International marriage is composed over 10% among total marriage in Korea. Korea is changing rapidly to the multi-cultural society. The researches need to inquire into what the state of 'ethnic communities of the immigrant wives as the minorities' is and how the immigrant wives build and develop the ethnic networks longitudinally. At the beginning, this study tried to know what kinds of social networks the immigrant wives use for the process of being married and for the adjusting to marriage and Korean culture. For the purposes of this study FGI and the interviews were applied for the immigrant wives and the specialist groups in metropolitan city DaeGu. 18 interviewees from Vietnam, China, Philippine, etc.. were collected by the snow-ball sampling. The social networks of the immigrant wives in DaeGu were mainly private, but were deterritorialized and reterritorialized actively. They managed the close relationship with their family members of motherland, and had the networks sticky with relatives, friends, and other immigrant wives from the same countries. Even though they acquired the Korean nationality, they have the transnational identities. But the internet environment of Korea can contribute to activate the social networks for the ethnic communities of the immigrant wives.

• Journal of Preventive Medicine and Public Health
• /
• v.44 no.5
• /
• pp.191-200
• /
• 2011

Objectives: The goal of this paper is to examine the social network effects on post-traumatic sdress disorder (PTSD) in female North Korean immigrants who entered South Korea in 2007. Specifically, it attempts to verify if the density and composition of networks make a difference after controlling for the network size. Methods: A multivariate logistic regression is used to probe the effects of social networks using the North Korean Immigrant Panel data set. Because the data set had only completed its initial survey when this paper was written, the analysis was cross-sectional. Results: The size of the support networks was systematically related to PTSD. Female North Korean immigrants with more supporting ties were less likely to develop PTSD, even after controlling for other risk factors (odds-ratio for one more tie was 0.8). However, once we control for the size of the network, neither the density nor the composition of the networks remains statistically significant. Conclusions: The prevalence of the PTSD among female North Korean immigrants is alarmingly high, and regardless of the characteristics of supporting network members, the size of the supporting networks provides substantial protection. This implies that a simple strategy that focuses on increasing the number of supporting ties will be effective among North Korean immigrants who entered South Korea in recent years.

• Korean Journal of Social Welfare
• /
• v.49
• /
• pp.7-33
• /
• 2002

This study analyse interorganizational networks of the self-supporting service organizations using data on the 31 organizations in Chanju area. Interorganizational networks are operationalized in two ways: conference network and referral network. First, this study attempt to examine the characteristics of interorganizational networks of the self-supporting service organizations. Using block model, I can capture some of the structural features of interorganizational networks. Major findings of block modeling are as follows: (1) Public organizations are more inactive to make a connect with other organizations. (2) Most of organizations incline to make a connect with same kind organizations. Namely, employment service organizations incline to flock together, and social welfare organizations are also much the same. Second, this study attempt to examine the determinants of interorganizational networks of the self-supporting service organizations. Relations between pairs of organizations are modeled as a function of dyadic level covariates in accordance with resource dependence, transaction cost, and organizational domain theory. Measure of informal ties between organizations are also included as covariates. Applying logit and tobit regression methods, this study reveals that most variables have effects on the dyadic relations of organizations. Through this empirical analysis, I can suggest policy implications for the self-supporting programs in Korea.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.05a
• /
• pp.544-547
• /
• 2004

Current increasingly information systems log historic information in a systematic way. Not only workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called 'event log'. Unfortunately, the information in these event logs is rarely used to analyze the underlying processes. Process mining aims at improving this problem by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs. This paper focuses on the mining social networks. This is possible because event logs typically record information about the users executing the activities recorded in the log. To do this we combine concepts from workflow management and social network analysis. This paper introduces the approach and presents a tool to mine social networks from event logs.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.12
• /
• pp.5927-5942
• /
• 2017

Many real networks exhibit overlapping community structures. Recent studies have been performed that analyze the impact of overlapping community structure on information propagation, but few of them concerned with individual behaviors. From this point of view, we propose a Markov process model to evaluate the performance of information propagation in social networks with overlapping community structures. In addition, many individual social behaviors are combined in the model. For example, individuals may exhibit selfish behaviors, such as individual and social selfishness, and people may discard the information after they have used it. The accuracy of the model is verified by simulation. Furthermore, the numerical results show that both overlapping community structure of the network and individual behaviors have a significant impact on the outbreak size and propagation speed of the information. Additionally, the overlapping community structure of the social network can reduce the impact of selfishness on information propagation.

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

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.4
• /
• pp.1643-1660
• /
• 2016

Connectivity and trust in social networks have been exploited to propose applications on top of these networks, including routing, Sybil defenses, and anonymous communication systems. In these networks, and for such applications, connectivity ensures good performance of applications while trust is assumed to always hold, so as collaboration and good behavior are always guaranteed. In this paper, we study the impact of differential behavior of users on performance in typical social network-enabled routing applications. We classify users into either collaborative or rational (probabilistically collaborative) and study the impact of this classification and the associated behavior of users on the performance of such applications, including random walk-based routing, shortest path based routing, breadth-first-search based routing, and Dijkstra routing. By experimenting with real-world social network traces, we make several interesting observations. First, we show that some of the existing social graphs have high routing costs, demonstrating poor structure that prevents their use in such applications. Second, we study the factors that make probabilistically collaborative nodes important for the performance of the routing protocol within the entire network and demonstrate that the importance of these nodes stems from their topological features rather than their percentage of all the nodes within the network.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.5
• /
• pp.1168-1173
• /
• 2013

This paper proposes a new visualization method based on cloud technique which uses internal relationship of user correlation and external relation of social network to visualize user relationship hierarchy. The visualization method of this paper can well represent user-focused relationship hierarchy on social networks by a correlation matrix. The importance of a access node reflects into user relationship hierarchy by exploiting external relation of social network. Users of the method can well understand user relationships on account of representing user relationship hierarchy from social networks. In addition, the method use hadoop and hive for distribution storing and parallel processing which the result of calculation visualizes hierarchy graph using D3.