• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.316-321
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• 2010

웹 2.0의 기술이 보급됨에 따라 소셜 네트워크 서비스에 대한 관심이 증가하였다. 국내에서는 싸이월드, 미투데이 등과 같은 서비스가 널리 사용되고 있으며 최근 급부상한 트위터는 여러 분야에서 관심을 받고 있다. 트위터는 팔로워나 트윗 등 활동 정도에 따라 랭킹 서비스가 제공되고 있지만 랭킹은 그들 사이의 관계를 세부적으로 나타내지 못한다. 본 논문에서는 트위터의 사용자들 사이에 존재하는 관계를 시각적으로 나타내는 도구에 대해 개발한다. 국내 사용자 중 팔로워의 랭킹에 따른 사용자를 이용하고, 시각화를 위해 생물학적 데이터를 네트워크로 나타내는 Cytocape 플랫폼을 사용한다. 사용자 간의 관계를 나타내는 네트워크를 통하여 온라인상에서 영향력 있는 사용자들의 관계를 나타내고 그들의 관계를 수치로 분석한다. 또한 복잡한 네트워크로부터 선택된 노드와 관련된 연결만을 추출하는 기능을 제공하여 온라인상의 관계를 상세하게 나타낸다.

• Journal of Information Management
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• v.42 no.1
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• pp.137-156
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• 2011

In this paper, our goal is to examine the factors of user's satisfaction and information sharing in Social Network Services(SNS). Based on the theoretical framework like attachment theory and self-presentation theory, we develop and test a theoretical model, propose hypotheses and analyze the effects of emotional attachment and self-presentation on the satisfaction and information sharing of SNS users. For this research, questionnaire survey was conducted with literature study and the PLS(Partial Least Square) was used to analyze the measurement model and hypotheses testing. The PLS analysis results indicate that emotional attachment affects SNS users' satisfaction and information sharing. Further, information sharing is influenced by self-presentation of SNS users. Practical implications of these findings and future research implications are also discussed.

• Journal of KIISE
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• v.41 no.12
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• pp.1110-1116
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• 2014

Nowadays, social networking sites (SNSs), such as Twitter, LinkedIn, and Tumblr, are coming into the forefront, due to the growth in the number of users. While users voluntarily provide their information in SNSs, privacy leakages resulting from the use of SNSs is becoming a problem owing to the evolution of large data processing techniques and the raising awareness of privacy. In order to solve this problem, the studies on protecting privacy on SNSs, based on graph and machine learning, have been conducted. However, examples of privacy leakages resulting from the advent of a new SNS are consistently being uncovered. In this paper, we propose a technique enabling a user to detect privacy leakages beforehand in the case where the service provider or third-party application developer threatens the SNS user's privacy maliciously.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.111-130
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• 2013

As the number of online social networking service (SNS) users is increasing, various efforts are being deployed to take advantage of SNS from the perspective of business and management. Especially, researches in the field of marketing such as word-of-mouth (WOM) effect have been actively conducted. This paper examined the impact of the SNS messages of users' friends on the users' attitude and the moderating effect of the friends' opinion leadership on the WOM effect. Fifty-one Facebook users responded to the questions on their four friends each. Regression analyses showed that there existed WOM effect under the SNS environment and the opinion leadership of the message creators positively moderated the WOM effect. We discussed the contributions and implications of this study.

• Informatization Policy
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• v.19 no.4
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• pp.3-26
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• 2012

The purpose of this study is to provide a systematical view point of SNS research published by scholarly journals in communications vis a meta-analysis. A total of 72 articles dealing with SNS issues from 2006 to 2012 were analysed by research theme, related sub-theme, methodology, theoretic rationale, targeted media, and characteristics. Effect research get the largest portion and then user research in terms of a developmental model of media research agenda. A major methodological trend is an online survey and theoretical background is Uses and Gratification. Twitter is the most popular medium researched and SNS is mainly characterized as information provision and seeking as well as relationship forming.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.84-86
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• 2012

최근 유무선 인터넷 인프라의 보급과 스마트폰의 등장으로 인터넷 사용이 급속히 늘어나면서 많은 사람들이 커뮤니티, 블로그, 트위터, 등 기타 다양한 온라인 사이트를 통하여 자신의 견해나 의견을 공개적으로 표현하고 있다. 스마트폰과 SNS 환경이 보편화됨에 따라 사람들은 점점 더 자신들의 취향에 맞는 정보의 교환을 원하고 있으며 단순한 정보검색보다는 다른 사람들의 직접적인 경험이나 의견을 반영하는 정보추천에 대한 비중이 커지고 있는 추세이다. 본 논문에서는 이런 소셜 네트워크에 널려있는 데이터들을 이용한 추천시스템 기법을 제안한다.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.73-88
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• 2014

Online communities are getting more popular with the development of information technology. It is essential that community members participate actively and share their contents or opinions continuously for the success and growth of online communities. However, it is revealed that most of members just take the role of passive observer. They are lurking community information and contents without any contribution. In this sense, this study focuses on explore lurking behavior of online community members. This study investigates the effect of the characteristics of online community, community members, and personal traits on user's lurking intention. Member familiarity and community identity have a strong positive effect on de-lurking intention, while the perception of usefulness and ease of use for communities and member expertise have a negative effect on de-lurking intention. Interestingly, users with a low level of self-esteem have higher level of motivation of participation than those with a high level of self-esteem. Finally, this study proposes several strategies to enhance information and contents sharing in online communities.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.1-10
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• 2011

Social network service is defined as an online service or communication service based on social relations among people applied the concept of social network. Social collaborative service included in social network service is characterized by the new value of modified content or recreated content made through collaborative creation process between members of the group. It has the remarkable merits such as sharing and collaboration. But, at the same time, it has the latent problems such as content reuse or copy that is not allowed for members to use. It has been emerged that UCC which is a typical example of recreated or modified content has the copyright issues in both creation and publishing step. To resolve this matter, we don't have many appropriate methods except CCL so far. So, in this paper, we define the problem and implement the UCC metadata manager to control metadata reflecting the feature of UCC. We draw the reference metadata element to identify original content utilized re-creation process. After that we define the R.Metadata Loader module based on the use case. Finally, the proposed UCC metadata manager provides the information of referenced content and lets us to identify the relationship between reference contents. So as to implement prototype, we use Kaltura which is CMS using open source and obtain functional extensibility of metadata manager by using open API.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1380-1386
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• 2015

Recently, the importance of users' geographic location information has been highlighted with a rapid increase of online social network services. In this paper, by utilizing geo-tagged tweets that provides high-precision location information of users, we first identify both Twitter users' exact location and the corresponding timestamp when the tweet was sent. Then, we analyze a relationship between the tweet frequency and the average user velocity. Specifically, we introduce a tweet-frequency computing algorithm, and show analysis results by country and by city. As a main result, it is shown that the tweet frequency according to user velocity follows a power-law distribution (i.e., Zipf' distribution or a Pareto distribution). In addition, by performing a comparison between the United States and Japan, one can see that the exponent of the distribution in Japan is smaller than that in the United States.