• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.233-240
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• 2011

Social Media is the open online tool and media platform for sharing and participation of users opinion, experience, viewpoiont, so general situation that is one-side flowing from production to consume doesn't act, and while use of two-way, user create contents use of sharing and participation. This social media include Blog, Social Network Service(SNS), Wiki, User Create Contents(UCC), Micro Blog, 5 types. In broad terms, Social Learning is self-learning that user sharing with coperation and collective intelligence through Social Media, and in few wards Social Learning is learning for Social Media. In this research, we define Social Media and Social Learning, and research of method of use of Elementary Education.

• Journal of KIISE
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• v.43 no.6
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• pp.621-626
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• 2016

Recursive query algorithm is used in many social network services, e.g., reachability queries in social networks. Recently, the size of social network data has increased as social network services evolve. As a result, it is almost impossible to use the recursive query algorithm on a single machine. In this paper, we implement recursive query on two popular in-memory distributed platforms, Spark and Twister, to solve this problem. We evaluate the performance of two implementations using 50 machines on Amazon EC2, and real-world data sets: LiveJournal and ClueWeb. The result shows that recursive query algorithm shows better performance on Spark for the Livejournal input data set with relatively high average degree, but smaller vertices. However, recursive query on Twister is superior to Spark for the ClueWeb input data set with relatively low average degree, but many vertices.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1293-1300
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• 2012

With the rapid evolution of mobile devices and the development of wireless networks, users of mobile social network service on smartphone have been increasing. Also the security of personal information as a result of real-time communication and information-sharing are becoming a serious social issue. In this paper, a framework that can be linked with a social network services platform is designed using OpenAPI. In addition, we propose an authentication and detection mechanism to enhance the level of personal information security. The authentication scheme is based on an user ID and password, while the detection scheme analyzes user-designated input patterns to verify in advance whether personal information protection guidelines are met, enhancing the level of personal information security in a social network service environment. The effectiveness and validity of this study were confirmed through performance evaluations at the end.

• Journal of Information Technology Applications and Management
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• v.28 no.5
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• pp.61-70
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• 2021

With the proliferation of smartphones and 5G networks, mobile social network service (SNS) has become an indispensable part of people's daily lives. However, with the use of SNS, fatigue and withdrawal behavior gradually emerged. Based on The Transactional Theory of Stress and Coping (TTSC), we explored the mechanism of SNS overload on users' discontinuous intention under the framework of "stressor-strain-outcome". And we also investigated the moderating effects of gender in this process. We hope that through our research, we can help SNS users to reduce unnecessary fatigue, and provide better suggestions for platform designers to adjust product design to improve user experience.

• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.82-88
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• 2012

In recent years, social awareness and concern about the SNS is getting a lot and many researches on the social impact of the SNS and variety strategies using SNS have emerged one after another. In this paper, we explain the method of interlocking between SNS and variety sensors in physical computing environment. Especially we propose that interlocking technology between sensors and twitter in Arduino platform(open source environment) can be used for the handicapped people. We design a way to send message via twitter for handicapped people using values from various sensors.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.59-66
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• 2023

Text mining (TM) is most widely used to find patterns from various text documents. Cyber-bullying is the term that is used to abuse a person online or offline platform. Nowadays cyber-bullying becomes more dangerous to people who are using social networking sites (SNS). Cyber-bullying is of many types such as text messaging, morphed images, morphed videos, etc. It is a very difficult task to prevent this type of abuse of the person in online SNS. Finding accurate text mining patterns gives better results in detecting cyber-bullying on any platform. Cyber-bullying is developed with the online SNS to send defamatory statements or orally bully other persons or by using the online platform to abuse in front of SNS users. Deep Learning (DL) is one of the significant domains which are used to extract and learn the quality features dynamically from the low-level text inclusions. In this scenario, Convolutional neural networks (CNN) are used for training the text data, images, and videos. CNN is a very powerful approach to training on these types of data and achieved better text classification. In this paper, an Ensemble model is introduced with the integration of Term Frequency (TF)-Inverse document frequency (IDF) and Deep Neural Network (DNN) with advanced feature-extracting techniques to classify the bullying text, images, and videos. The proposed approach also focused on reducing the training time and memory usage which helps the classification improvement.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.31-53
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• 2013

Web 2.0 has affected existing e-commerce and created a new business model of e-commerce, known as social commerce. Social commerce is a subset of e-commerce using social network services and is emerging as an important platform due to increased popularity of social networking services. This study focuses on analyzing the factors that influence the shopping value and intention to repurchase of social commerce users. Based on prior researches, we develop a research model, including individual characteristics of social commerce users (Collectivism, Price Sensitivity, Impulse Buying) and social commerce characteristics (Cost saving, Product Variety, Shopping Convenience). Furthermore, this study proposed the moderating effect of Perceived Security and the relationship between shopping value and intention to repurchase. To empirically validate, the data were collected from 220 social commerce users. The results indicated that individual characteristics (collectivism, price sensitivity, impulse buying) were positively related to hedonic shopping value. In addition, social commerce characteristics (cost saving, shopping convenience) were positively related to utilitarian value. The shopping value(hedonic and utilitarian) had a significant influence on intention to repurchase. The moderating effects of perceived security also was significant. Lastly, the implications for theory and practice are discussed.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.238-248
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• 2020

This study examines the feelings of positivity and negativity generated through upward social comparison and explores the impact of the results of the emotions on SNS users' posting behavior. In particular, this study aims to systematically identify the influence of upward social comparison on SNS followers and uploaders' SNS usage behavior and the structural principle of social network circulation in which followers become uploaders again. According to the analysis, interaction-oriented followers made negative upward social comparison and positive upward social comparison, while negative upward social comparison reduced the publication of independence tendency. However, positive upward social comparison has been shown to increase both independent and interactive postings. The results of this study are meaningful in that SNS has expanded the results of prior studies, in which social comparison theories were biased toward negative upward comparisons, to positive upward comparisons. In addition, this study suggested a practical strategy for SNS platform operators on how SNS users would not deviate from other platforms.

• Korean Security Journal
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• no.46
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• pp.7-30
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• 2016

This study found the strategies for activating the security industry to utilize social network services based on the platform business model. This research was utilized for in-depth interview and IPA analysis. And use it was to check the contents and strategic improvement projects that can actually materialize and direction of the strategy. First, run a priority need area is a private center of community policing related portal development and operation, universal social networking service(SNS) utilizing expanded, professional training, IT-based security content management and operation of IT infrastructure security guards and security professionals up educational content development, online security guards and security professionals-up refresher training program development. Second, the area over the inventory capabilities increase the effectiveness of the security guards was constructed open-type comprehensive public information system. Third, the area needed to be reviewed are the individual security industry experts workers operating information channels, dedicated customer service and expanding the event of a private security guard & security service providers up. Fourth, the effectiveness of the insufficient area are discuss system improvements, the sharing of community policing closed Cameras for proposals for the expanded utilization of social networking services, private development organizations Social Network Service(SNS).

• Asia pacific journal of information systems
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• v.26 no.3
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• pp.367-384
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• 2016

Social networking services (SNS) have become a significant platform for Internet users to obtain knowledge and information. Users can share messages mutually via this platform. This kind of sharing enables users to exchange and gain useful information. However, in recent years, the crisis of stickiness has appeared in SNS, calling attention to the social network industry. Relevant professionals explain that the interest of users in sharing knowledge on SNS websites and applications may gradually decrease, eventually leading to users giving it because the platforms utilize simple and uninteresting methods to attract active participation from users. However, factors affecting the knowledge sharing on SNS websites and applications should be identified clearly through studies. Sina Weibo is one of the largest SNS platforms in the world, and studies on the factors affecting knowledge sharing of users could be valuable in addressing this issue. This paper establishes the theoretical analysis model of knowledge sharing in SNS sites and applications, analyzes the factors affecting knowledge sharing on these sites, and proposes the corresponding strategies to address the issues. Using questionnaire surveys on Sina Weibo users, this article will discuss the factors affecting knowledge sharing, and analyze these factors on SNS as well as improve the stickiness of users to achieve the aim of SNS platforms enabling the expansion of the range of users. The study will discuss theoretical foundations and the hypotheses that arise. The method of study will also be discussed. The study concludes with theoretical implications, practical implications, limitations, and future research opportunities. The results of this study could aid researchers in understanding the underlying reasons for social network activities as well as for SNS developers in improving SNS services.