• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.11-14
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• 2009

In this paper, we propose the method configuring social networks among users based on users' context and profile. Recently, many researchers are concerned about social networks related with collaborative systems. In case of the existing researches, however, it is difficult to configure social networks dynamically because they are based on static data types, such as log and profile of users. The proposed method uses not only user profiles but also context reflecting users' behavior dynamically. It computes the similarity among users' behavior contexts using hierarchical structure of context domain knowledge model. And it calculates relationships between contexts by given weight factors of category of context model. In order to verify usefulness of the method, we conduct an experiment on configuring social network according to change of user context. We expect that it makes dynamic analysis of relationship of users possible.

• Knowledge Management Research
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• v.13 no.4
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• pp.83-100
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• 2012

Given the prevalence of mobile social network services (SNS) such as Facebook and Kakaotalk, it has become important to understand user's continuance behavior in a mobile SNS environment. Although trust and privacy concerns play a key role in SNS users' decision-making processes, most studies on SNS have shed little light on the effects of trust and privacy concerns on SNS continuance intention. In this regard, this paper developed an integrated model to deeply understand the key antecedents of user's continuance intention to use mobile SNS by incorporating trust and privacy concerns into extended expectation-confirmation model. The proposed research model was tested by using survey data collected from 170 users who have experience with Kakaotalk. The findings of this study found that the proposed theoretical framework provides a statistically significant explanation of the variance in continuance intention of mobile SNS. The analysis results indicate that trust serves as the salient antecedent of continuance intention to use mobile SNS. However, it was found that privacy concerns negatively influence trust, whereas it is not significantly related to continuance intention of mobile SNS. The theoretical and practical implications of the findings were described.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.25-38
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• 2021

Recently the need for network surveillance to detect abnormal behavior within dynamic social networks has increased. We consider a dynamic version of the degree corrected stochastic block model (DCSBM) to simulate dynamic social networks and to monitor for a significant structural change in these networks. To apply a control charting procedure to network surveillance, in-control model parameters must be estimated from the Phase I data, that is from historical data. In network surveillance, however, there are many situations where sufficient relevant historical data are unavailable. In this paper we propose a self-starting Shewhart control charting procedure for detecting change in the dynamic networks. This procedure can be a very useful option when we have only a few initial samples for parameter estimation. Simulation results show that the proposed procedure has good in-control performance even when the number of initial samples is very small.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.137-145
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• 2016

The explosive growth of social networking services based on smart devices popularize these relationships and activities online in accordance with the far larger impact of this on the real life offline, the interest and importance for the online activity is increasing. In this study, factors affecting the SNS activity are defined by object, user, influence direction, influence distance and proposed a method to measure organic terms in effect between the SNS users. Influence Direction and Influence Strength (or Distance) are elaborated by using the existing influence measurement element such as structured data - the number of friends, the difference between the number of contacts - and the new influence measurement element such as unstructured data - gap between the former time and the latter time, preference and type of response behavior - that occur in social network service. In addition, the system for collecting and analysing data for measuring influence from social network service and the process model on the method for measuring influence is tested by using sample data on Facebook and explained the implementation probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.287-312
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• 2011

Internet chat programs and instant messaging services are becoming increasingly popular among Internet users. One of the crucial issues with Internet chat is how to manage the corresponding pairs of questions and answers in a sequence of conversations. Although many novel methodologies have been introduced to cope with this problem, most are poor in managing interruptions, organizing turn-taking, and conveying comprehension. The Internet environment is recently evolving into a 3D environment, but the problems with managing chat dialogues with the standard 2D text-based chat have remained. Therefore, we propose a more realistic communication model for chat agents in 3D virtual space in this paper. First, we propose a new method to measure the capacity of communication between chat agents and a novel visualization method to depict the hierarchical structure of chat dialogues. In addition, we are concerned with communication networks for virtual people (avatars) living in virtual worlds. In this paper we consider a microscopic aspect of a social network in a relatively short period of time. Our experiments show that our model is highly effective in a virtual chat environment, and the communication network based on our model greatly facilitates investigation of a very large and complicated communication network.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.69-87
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• 2013

Recently a large number of people have been using social networking and microblogging services such as Facebook and Twitter. These mediums play a pivotal communication channel in a business-to-customer (B2C) relationship. Given its importance in today's business, companies have invested in the strategic application of social network services to reach out to customers. This study provides a blueprint for mechanisms for successful execution of social network services in the context of developing an effective B2C relationship, such as customer participation behavior. The S-O-R(Stimulus-Organism-Response) framework lays out the foundation for developing our research model and provides a structured view for understanding customer participation behavior on brand loyalty. For the methodology, this study employed a mixed-method approach. Additionally, in order to provide empirical evidences, a total of 121 respondents have completed the survey. All the data were compiled and analyzed through structural equation modeling and were implemented in partial least square (PLS). To sum up, this study presented theoretical and practical implications by providing the effect of customer participation behavior on brand loyalty through B2C microblogging.

• International Commerce and Information Review
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• v.17 no.3
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• pp.29-57
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• 2015

The purpose of this study is to find the factors of Social Network Games of continuous game flow and addiction. This study analyzes the significant factors of the addiction of SNGs from three categories. It also seeks to find out what relation between continuous game flow and addiction in SNGs. The model consists of three categories (SNG characteristic, User characteristic, and Environmental characteristic). The research model was conducted through the structural equation modeling(SEM) approach, and tested using 374 questionnaires. The results indicated that SNG characteristic(accessibility, enjoyment, feedback), User characteristic(self-control), Environmental characteristic(social interaction, subjective norm) have a positive effect on continuous game flow. The findings also that continuous game flow plays a moderation role that affects addiction. Finally, we discussed the research results and offered relevant suggestions for schools, firms, and future studies

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.718-727
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• 2011

This research aims to empirically investigate into the relationship between venture entrepreneurs' social network and their social competence to utilize the network, which is known to help overcome the weaknesses of small-and-medium-sized ventures. An analysis was made of SEM set up with 211 entrepreneurs' responses, and the following are the findings from the analysis. First, venture entrepreneurs' networking ability has a significant, strong and positive effect on weak tie of their social network(${\beta}$=.527, C.R.=3.626), strong tie(${\beta}$=.594, C.R.=3.969), and the network centrality(${\beta}$=.418, C.R.=4.884). Second, their social astuteness also has a significant and positive effect on weak tie(${\beta}$=.192, C.R.=1.701), strong tie(${\beta}$=.269, C.R.=2.509) and the network centrality(${\beta}$=.228, p=2.283). Third, their interpersonal influence has a significant but negative effect only on strong tie(${\beta}$=-.264, C.R.=-1.862) and the network centrality(${\beta}$=-.394, C.R.=-2.914). Lastly, their apparent sincerity has no significant effect on the subordinate factors of social network. This research has not just empirically analyzed the relationship between the entrepreneurs' social network and their social competence. But also, results of the research provide practical and detailed information to entrepreneurs of small and medium ventures. Moreover, the research is significant in that it has suggested and empirically analyzed the concept of political competence, which is a concrete substance of social competence, and that it has offered theoretical foundations for future researches, which will tackle the issue of the entrepreneurs' competence in the sphere of entrepreneurship.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.73-86
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• 2012

This paper theoretically derives an algorithm to discover a new type of social networks from workflow models, which is termed workflow-based social network intelligence. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict from workflow models and their execution histories. So, this paper proposes an algorithm, which is termed ICN-based workflow-based social network intelligence discovery algorithm, to be classified into the type of discovery techniques, which are able to discover workflow-based social network intelligence that are formed among workflow performers through a series of workflow models and their executions, In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to generate its corresponding workflow-based social network intelligence.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.557-568
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• 2014

Recently, software projects have been increasing and getting complex. Due to the large number of submitted bug reports, developers' workload increases. Generally in bug triage process, the triagers assign the bug report to fixer (developer) in order to resolve the bug. However, bug reports have been reassigned to other developers because fixers are not suitable. This is why the triagers did not correctly check and understand the bug report and decide the appropriate developers to fix the bug. This results in increase of developers' time and efforts in software maintenance. To resolve these problems, in this paper, we propose a novel method for developer recommendation based on topic model and social network. First, we build a basis of topic(s) from bug reports. Next, when a new bug report (test data set) comes, we select the most similar topic(s) and extract the participated developers from the topic(s). Finally, by applying social network, we analyze the developers' behavior (comment and commit activity) and recommend the appropriate developers. In this paper we compare our work with related studies through performance experiments on open source projects. The results show that our approach is more effective than other studies in bug triage.