• Journal of Digital Convergence
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• v.10 no.10
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• pp.457-463
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• 2012

Social network game (SNG) literally is a game based on the relationship between social network or Relationships with people is an important element in the game you need to make full use of them is that you can smooth progress. The form of a social network game activities in the social network game applications by linking corporate products and can be induced to purchase marketing and advertising through in-game social network game on the company's Web site or by connecting the mall and shop are also available. In this study, SNG business models, Case For game development, social commerce based on the new proposed future revenue model linking scheme is proposed.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.4
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• pp.1-16
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• 2011

It is important not only to introduce the C4I(Command and Control, Communication, Computer, Intelligence) system for realizing the NCW(Network Centric Warfare) but also to evaluate the synergistic effect by the C4I system. However, the study effort for evaluating the system's synergistic effect is insufficient compared with introducing the system. Therefore, in this paper, we proposed a model that measures the synergistic effect of combat power by the warfare information system. To measure the synergistic effect of warfare information system, the network power must be considered, so we also proposed a new methodology for measurement of network power based on SNA(Social Network Analysis), not Metcalfe's law. A model we proposed is a model that measures the raised combat power by the network effectiveness. The methodology and model we proposed in this paper will be used usefully to analyze the practical effect of constructing future warfare information system.

• Knowledge Management Research
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• v.14 no.1
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• pp.21-37
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• 2013

Due to the development of social networks and smartphones, many different kinds of issues have emerged in business and society. By reflecting these trends, social network sites have appeared and they are recognized as the new concept of sites. The major feature of the social network sites is that the social relationship had been taken to the online space. Social network sites support the formation of a network and offer users the relationship between users offline as well as online. Based on the features mentioned above, users enjoy the benefits using social network sites. These social network sites in the enterprise can be used to form relationships with customers. This study identified the influencing factors as relational benefits and social influence on relationship commitment in social network sites. In addition, we analyzed that how the relationship commitment between users affects user loyalty after their using social network sites. We presented empirical results by utilizing structural equation model with 244 respondents and the significant implications for the academy and the practice with discussions.

• Knowledge Management Research
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• v.15 no.2
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• pp.1-21
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• 2014

In this study we adopted Interpersonal Process Model of Intimacy to study SNS use intention. First, we investigated the effects of personal identity, social identity and intimacy. Second, we tested the influences of self-disclosure, partner disclosure on perceived partner responsiveness. Third, we measured the relationship between perceived partner responsiveness and intimacy. Lastly, we investigated the effects of intimacy, perceived partner responsiveness and use intention. A total of 232 final respondents were collected from users of Social Network Services in 2011. The results revealed several important findings. First, we found that social identity had a significant and positive effect on intimacy. However, personal identity showed insignificant effect toward intimacy. Moreover, self-disclosure and partner disclosure had a positive effects on perceived partner responsiveness. perceived partner responsiveness showed a positive effect on both intimacy and use intention. Lastly, intimacy had significant effect on use intention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5927-5942
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• 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 Agricultural Extension & Community Development
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• v.24 no.4
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• pp.223-235
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• 2017

This study aims to identify the factors affecting the depression of elderly women in rural areas, by focusing on social network and sense of community. The questionnaires were conducted from July to September, 2016 by face-to-face interviews with the elderly women using the senior citizen center in rural areas. As a result, 302 questionnaires were collected, and of which 292 cases were utilized for the final analysis. The analysis revealed that socio-demographic characteristics, social network, and community consciousness had a significant effect on depression. The main results are summarized as follows. First, in first model, age, education, subjective health status, and subjective economic status were found to affect depression. Second, in second model, by adding the social network, the explanation power increased, and the social network of friends/neighbors were proven to be an influence on depression. Third, in third model, explanation power increased when sense of community was added, and it was proven that sense of community had an effect on depression. Finally, when the socio-demographic characteristics and the social network were controlled, the sense of community had more influence on the depression than the social network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3984-3996
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• 2014

Mobile social network can be seen as a specific application of the DTN (Delay Tolerant Network), in which the information propagation can be impacted by many social behaviors of the nodes. For a specific node, its social behaviors are various. For example, the node may not be interested in the information before receiving it and may also discard the information after getting it. On the other hand, people are more willing to forward the message to his friends. These interactive behaviors between nodes can be seen as social behaviors. It is easy to see that the impact of the social behaviors is related to the social ties, which can be manifested by the structure of the social network. State of the art works often simply assumes that the social networks can be divided into some communities. At present, some works find that the structure of some social networks is scale-free. To overcome this problem, this paper proposes a theoretical model to evaluate the impact of above social behaviors in the DTN-like scale-free network. Simulation shows the accuracy of the model. Numerical results show that both social behaviors and scale-free character have significant impact on information propagation. Moreover, the impact of social behaviors is related to the scale-free character of the networks.

• Knowledge Management Research
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• v.16 no.2
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• pp.67-89
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• 2015

Improving productivity of knowledge workers is an important issue in the 21st century referred as knowledge-based society. The core key word is knowledge sharing among constituents of an organization. The purpose of this study is to combine the social network position factors with attitude and behavior factors, and develop an integrated research model for the knowledge sharing among members of an organization. This study adopted the integrated theoretical framework based on social capital, self-efficacy, transactive memory, and knowledge sharing. Surveys were conducted to 42 organizational members from a department in a leading IT outsourcing company to empirically test the proposed research model. In order to validate the proposed research model, social network analysis tool, UCINET, a structural equation modeling tool, SmartPLS, were utilized. The empirical result showed that, first of all, organizational members' familiarity network position had significant influence on knowledge self-efficacy and transactive memory capability. Second, knowledge self-efficacy and transactive memory capability affected knowledge sharing intention. Third, knowledge sharing intention also had an impact on the job performance. However, organizational members' expertise network position had no significant influence on knowledge self-efficacy and transactive memory capability. This finding reveals the importance of the emotional approach rather than the rational approach in knowledge management. The theoretical and practical implications on the research findings were discussed along with limitations.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.576-589
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• 2023

To upgrade home style recommendations and user satisfaction, this paper proposes a personalized and optimized recommendation algorithm for interior design style based on local social network, which includes data acquisition by three-dimensional (3D) model, home-style feature definition, and style association mining. Through the analysis of user behaviors, the user interest model is established accordingly. Combined with the location-based social network of association rule mining algorithm, the association analysis of the 3D model dataset of interior design style is carried out, so as to get relevant home-style recommendations. The experimental results show that the proposed algorithm can complete effective analysis of 3D interior home style with the recommendation accuracy of 82% and the recommendation time of 1.1 minutes, which indicates excellent application effect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1168-1188
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• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.