• Journal of Korea Society of Industrial Information Systems
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• 제17권5호
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• pp.61-73
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• 2012

Social Network Service is a web-based service that allows the people to construct relationship among users with same interest and supports various activities such as managing personal relations and sharing information or contents. Based on the IS Success Model and UTAUT model, this study examines factors influencing the satisfaction of SNS use. Questionnaires are collected from 473 students who are using the SNS. The results are followings: first, the performance expectancy, effort expectancy and social influence have positive effect on the use intention. Second, the facilitation conditions and use intention have positive effect on the use. Third, the system quality, information quality and use have positive effect on the satisfaction. Fourth, the performance expectancy is the strongest predictor of the use intention, the use intention is the strongest predictor of the use and information quality is the strongest predictor of the satisfaction.

• The Journal of Society for e-Business Studies
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• 제17권2호
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• pp.73-85
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• 2012

Recently, as Social Network Services(SNS), such as Twitter, Facebook, are becoming more popular, much research has been doing actively. However, since SNS has been launched recently, related researches are also infant level. Especially, search engines serviced in web potals simply show the postings in order of upload time. Searching the postings in Twitter should be different from web search, which is based on traditional TF-IDF. In this paper, we present the new method of searching and ranking the interesting postings in Twitter. In proposed method, we utilize the frequency of retweets as a major factor for estimating the quality of postings. It can be an important criteria since users tend to retweet the valuable postings. Experimental results show that proposed method can be applied successfully in Twitter search system.

• KIPS Transactions on Software and Data Engineering
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• 제6권6호
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• KIPS Transactions on Computer and Communication Systems
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• 제5권10호
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• pp.339-346
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• 2016

1 person media is becoming the leading trend among several media in the Internet era exploiting the individual desire of showing off. But, the vast accessibility of Internet produces the worry about privacy risk, which concludes in the increasement of closed SNS. In this paper, we propose a system based on PWW (Person Wide Web) where a person is producing a media and share it with other persons. PWW is an information system which consists of a smart-phone, mobile anchors, a standard web document, and his own cloud storage. An information consumer gets the link using his smart-phone from the mobile anchors attached on the objects in the field. The web browser in the smart-phone obtains the web documents designated by the link and presents it. We also explains the 1 person media system based on PWW and presents the example utilized in the field. We compared and analyzed the security factor of the system based on between WWW and PWW, and concluded that PWW is better than WWW in the aspect of security.

• Journal of Information Technology Services
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• 제15권3호
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• pp.147-155
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• 2016

According to rapid development of technology, web text is growing explosively and attracting many fields as substitution for survey. The user of Facebook is reaching up to 113 million people per month, Twitter is used in various institution or company as a behavioral analysis tool. However, many research has focused on meaning of the text itself. And there is a lack of study for text's creation subject. Therefore, this research consists of sex/age text classification with by using 20,187 Facebook users' posts that reveal the sex and age of the writer. This research utilized Convolution Neural Networks, a type of deep learning algorithms which came into the spotlight as a recent image classifier in web text analyzing. The following result assured with 92% of accuracy for possibility as a text classifier. Also, this research was minimizing the Korean morpheme analysis and it was conducted using a Korean web text to Authorship Attribution. Based on these feature, this study can develop users' multiple capacity such as web text management information resource for worker, non-grammatical analyzing system for researchers. Thus, this study proposes a new method for web text analysis.

• Journal of Intelligence and Information Systems
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• 제20권2호
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Information Systems Review
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• 제18권3호
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• pp.209-233
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• 2016

Internet companies that utilize social network have increased in number. The introduction of diverse social media services facilitated innovative changes in e-business. Social network service (SNS), which is a domain of social media, is a web-based service designed to strengthen human relations in the Internet and build new social relations. The remarkable growth of social network services and the profit generation and perception of this service are the new growth engines of this digital age. Given this development, many global IT companies views SNS as the most powerful form of social media. Thus, they invest efforts to develop business models using SNS.2) This study verifies the impact of privacy exposure in SNS as a result of privacy invasion. This study examines the purpose of using the SNS and user's awareness of the significance of personal information, which are key factors that affect self-disclosure of personal information. This study utilizes theory of reasoned action (TRA) to provide a theoretical platform that describes the specific behavior and emotional response of individuals. This study presents a research model that considers negative attitude (negatude). In this model, self-disclosure in SNS is considered a TRA. TRA is a subjective norm, a behavioral intention, and a key variable of exposure behavior. A survey was conducted on college students at Y university in Seoul to empirically verify the research model. The students have experiences in using SNS. A total of 198 samples were collected. Path analysis was applied to analyze the relations of factors. The results of path analysis show the statistically insignificant impact of privacy invasion on negatude, subjective norm, behavioral intention, and exposure behavior. The impact of unrecognized privacy invasion was also considered insignificant. The impacts of intention to use SNS on negatude, subjective norm, behavioral intention, and exposure behavior was significant. A significant impact was also found for the significance of personal information on subjective norm, behavioral intention, and exposure behavior, whereas the impact on negatude was insignificant. The impact of subjective norm on behavioral intention was significant. Lastly, the impact of behavioral intention on exposure behavior was insignificant. These findings are significant because the study examined the process of self-disclosure by integrating psychological and social factors based on theoretical discussion.

• Korean Management Science Review
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• 제28권3호
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• pp.83-94
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• 2011

Microblogging is a Web2.0 technology that is used to manage online interpersonal relationship in SNS. Microblogging service allows the users to publish online brief text updates, usually less than 140~200 characters, sometimes images too. Recently, it becomes more and more popular. There are many reasons, the major one of which is that it can be perfectly combined with mobile. Based on technology acceptance model (TAM) and according to mobile service and microblogging service, this research adds four attributes : Perceived enjoyment, Habit, Mobility, Social Influence. It studies the factors that will impact on the way in which people use rapid developing Mobile Microblogging Service. This research will compare the influence factors and intension to use with the results from other studies with SNS and Mobile Microblogging Service, and then conclude the differences that can be generated in Microblogging.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2013년도 추계학술발표대회
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• pp.433-436
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• 2013

폐쇄형 SNS란 카페 블로그 등 온라인 상의 커뮤니티 서비스를 모바일로 옮겨 놓은 것이다. 이메일 주소나 전화번호로 연결된 모든 지인을 일괄적으로 친구로 등록하는 개방형 SNS와 달리, 친밀도에 따라 지인을 따로 관리할 수 있다. 개방형 SNS에 비해 가입자 폭은 넓지 않지만 이용자 충성도가 높다는 게 큰 장점으로 꼽힌다. 이에 본 논문에서는 폐쇄형 SNS를 통하여 학교에서 리더를 맡고있는 회장, 학회장 등에게 효과적으로 학생회를 운영 할 수 있는 어플리 케이션을 제공한다. 이를 통해 사용자들은 효과적인 학과 운영과 질높은 행사, 투명한 학회비 관리 등을 제공받을 수 있다.

• Journal of Korea Multimedia Society
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• 제19권9호
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• pp.1698-1709
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• 2016

These days, anyone can easily product and share their own content through a web service such as blogs and SNS. However, contents are being operated separately because of the space limitation in individual SNS. Therefore, it is hard to search contents efficiently in individual SNS. To solve this problem, this paper propose a "Private Contents Management and Sharing Service with Voluntary Sharing Economy System." The system is in part [Input], [Save] and it provides a way to collect the content that are scattered on the Internet based on the creation of personal index. It also proposes a more systematic content management and sharing by creating and updating the website standard index by introducing an index Coordinator concept. Furthermore in [Use] section, by providing a portion of the index as the primary search results, it avoid unclassified content list which was simply collected by users. In conclusion, unlike previous studies, this system will contribute to the acquisition and management of interspersed content and ultimately contribute to the shared activation by preventing secondary processing and unauthorized processing to the original article.