• Management & Information Systems Review
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• v.30 no.3
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• pp.153-167
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• 2011

This study conducts to examine the effect of purchase intention on social shopping by connection density and centrality which is a structural characteristic of social network. Furthermore, this study suggests and analyses the difference of social shopping purchase intention between online community which focuses on a group and SNS(social network service) which focuses on an individual. To examine these reason, this study proposes hypotheses that reflects structural characteristic then analyses them. The result of analysis shows that the purchase intention on social shopping seems to be high when the density of connection is high and the purchase intention seems to be high when the centrality is high as well. Moreover, there is difference in the purchase intention on social shopping between online community and SNS and it is found that both cases where the connection density is high in the online community and the connection centrality is high in SNS have significant impact on the purchase intention. Based on these results, this study provides an implication on the importance on network structure in social network and social shopping and to increase the purchase intention of social shopping, this study suggests the implication on the importance and direction which understands the structure of social network type.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.567-575
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• 2020

As online social networks are used as a critical medium for modern people's information sharing and relationship, their users are increasing rapidly every year. This not only increases usage but also surpasses the existing media in terms of information credibility. Therefore, emerging marketing strategies are deliberately attacking social networks. As a result, public opinion, which should be formed naturally, is artificially formed by online attacks, and many people trust it. Therefore, many studies have been conducted to detect agents attacking online social networks. In this paper, we analyze the trends of researches attempting to detect such online social network attackers, focusing on researches using social network graph characteristics. While the existing content-based techniques may represent classification errors due to privacy infringement and changes in attack strategies, the graph-based method proposes a more robust detection method using attacker patterns.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.96-104
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• 2020

As consumers' consumption activities become more active due to the activation of online shopping malls, companies are conducting item trend analyses to boost sales. The existing item trend analysis methods are analyzed by considering only the activities of users in online shopping mall services, making it difficult to identify trends for new items without purchasing history. In this paper, we propose a trend analysis method that combines data in online shopping mall services and social network data to analyze item trends in users and potential customers in shopping malls. The proposed method uses the user's activity logs for in-service data and utilizes hot topics through word set extraction from social network data set to reflect potential users' interests. Finally, the item trend change is detected over time by utilizing the item index and the number of mentions in the social network. We show the superiority of the proposed method through performance evaluations using social network data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.914-924
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• 2020

In this study we developed artificial network generation model, which can generate on-line social network. The suggested model can represent not only scale-free and small-world properties, but also can produce networks with various values of topological characteristics through controlling two input parameters. For this purpose, two parameter K and P are introduced, K for controlling the strength of preferential attachment and P for controlling clustering coefficient. It is found out on-line social network can be generated with the combinations of K(0~10) and P(0.3~0.5) or K=0 and P=0.9. Under these combinations of P and K small-world and scale-free properties are well represented. Node degree distribution follows power-law. Clustering coefficients are between 0.130 and 0.238, and average shortest path distance between 5.641 and 5.985. It is also found that on-line social network properties are maintained as network node size increases from 5,000 to 10,000.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.404-414
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• 2017

With the development of smartphones and online social networks, users produce a lot of contents and share them with each other. Therefore, users spend time by viewing or receiving the contents they do not want. In order to solve such problems, schemes for recommending useful contents have been actively studied. In this paper, we propose a contents recommendation scheme using collaborative filtering for users on online social networks. The proposed scheme consider a user trust in order to remove user data that lower the accuracy of recommendation. The user trust is derived by analyzing the user activity of online social network. For evaluating the user trust from various points of view, we collect user activities that have not been used in conventional techniques. It is shown through performance evaluation that the proposed scheme outperforms the existing scheme.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.159-167
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• 2018

In this study, we have developed an online learning community site using Humhub social network software and promote social constructive learning through the questions and answers in subject specific learning groups. By accumulating learning contents which consist of questions and answers about specific topics, learners can acquire knowledge by searching relevant topics and questions and can create and reconstruct knowledge as well as consuming knowledge by participating in self-regulated learning community. We have developed a mathematical editor feature which enables users to enter mathematical expression such as equations and greek characters. Online learning community sites can be used for inquiry based information education.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.12
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• pp.533-540
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• 2013

Anonymity is the one of main reasons for substantial improvement of Internet. It encourages various users to express their opinion freely and helps Internet based distributed systems vitalize. But, anonymity can cause unexpected threats because personal information of an online user is hidden. Especially, distributed systems are threatened by Sybil attack, where one malicious user creates and manages multiple fake online identities. To prevent Sybil attack, the traditional solutions include increasing the complexity of identity generation and mapping online identities to real-world identities. But, even though the high complexity of identity generation increases the generation cost of Sybil identities, eventually they are generated and there is no further way to suppress their activity. Also, the mapping between online identities and real identities may cause high possibility of losing anonymity. Recently, some methods using online social network to prevent Sybil attack are researched. In this paper, a new method is proposed for extracting a user's system-wide Sybil-resistant trust value by using the properties embedded in online social network graphs. The proposed method can be categorized into 3 types based on sampling and decision strategies. By using graphs sampled from Facebook, the performance of the 3 types of the proposed method is evaluated. Moreover, the impact of Sybil attack on nodes with different characteristics is evaluated in order to understand the behavior of Sybil attack.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.129-134
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• 2015

Since automatic social engineering based spam attacks induce for users to click or receive the short message service (SMS), e-mail, site address and make a relationship with an unknown friend, it is very easy for them to active in online social networks. The previous spam detection schemes only apply manual filtering of the system managers or labeling classifications regardless of the features of social networks. In this paper, we propose the spam detection metric after reflecting on a couple of features of social networks followed by analysis of real social network data set, Twitter spam. In addition, we provide the online social networks based unsupervised scheme for automated social engineering spam with self organizing map (SOM). Through the performance evaluation, we show the detection accuracy up to 90% and the possibility of real time training for the spam detection without the manager.

• Journal of Korea Game Society
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• v.14 no.5
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• pp.193-202
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• 2014

This study is based on previous studies on the various types of games and analyse the effects of the characteristics of mobile social network games on online word-of-mouth of game users. As a result, it was revealed that commitment increased because of the features of not needing to access continuously, not interrupted by reciprocal relationship among users, a particular time and place. However, in the process of the interaction with the media, perceived individual social presence and asynchrony that did not need to continue to access, they did not affect satisfaction and respectively. In addition, this commitment had more effects on online word-of-mouth than satisfaction. Comprehensive the above, the research achievement of this study may be expected to contribute to the ongoing development of future domestic mobile social network game industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1347-1349
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• 2013

현시대 온라인 사용자들에게 각광받고 있는 형태의 웹기반 서비스의 한 형태인 소셜 네트워크 서비스는 동창모임, 지역모임 등의 다양한 현실 인간관계를 기반으로 한 사용자간의 매칭 기능을 제공하고 있다. 이러한 매칭 기능을 바탕으로 소셜 네트워크 서비스는 개인의 일상을 공유하는 용도로 사용되고 있다. 이와는 별도로 학습관리시스템은 대학이상의 고등교육 현장에서 사용되어 학습자의 학습 내용 및 그에 대한 교수자의 피드백을 주기 위한 용도로 이용되고 있다. 본 논문에서는 이러한 소셜 네트워크 서비스의 특성과 학습관리 시스템을 융합하여 학교현장 및 평생교육 관점에서 활용 가능한 소셜 네트워크 서비스기반의 사용자 협업형 학습관리시스템의 구조를 제시한다.