• Smart Media Journal
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• v.1 no.4
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• pp.72-78
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• 2012

SNS supports the formation of relationships between users in common interests and provides services allowing for clique management, sharing contents, and so on. It also has common functions such as acting as primary platforms smoothing the sharing and distribution by combination with various contents. Hence, questionnaire has been conducted to users of all of Twitter, Facebook and KakaoStory, and the factors affected by each service are presented by statistical analyses of the survey and the results are resolved by dividing them into complete and instrumental social capital. This study will be able to provide a standard for users to select SNS according to their purposes and contribute to development of new SNS or improvement of existing ones.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.27-35
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• 2013

Recently, as Social Network Services(SNS) are becoming more popular, much research has been doing on analyzing public opinions from SNS. One of the most important tasks for solving such a problem is to separate opinion(subjective) documents from others(e.g. objective documents) in SNS. In this paper, we propose a new method of retrieving the opinion documents from Twitter. The reason why it is not easy to search or classify the opinion documents in Twitter is due to a lack of publicly available Twitter documents for training. To tackle the problem, at first, we build a machine-learned model for sentiment classification using the external documents similar to Twitter, and then modify the model to separate the opinion documents from Twitter. Experimental results show that proposed method can be applied successfully in opinion classification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.438-440
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• 2014

Recently it is used commercially to actively move the data from the SNS service. Therefore, we propose a method that can accurately analyze the information related to the reputation of companies and products in real time SNS environment in this paper.Identify the relationship between words by performing morphological analysis on the text data gathered by crawling the SNS scheme. In addition, it shows the visualization to analyze statistically through a established emotional dictionary morphemes are extracted from the sentence. Here, if the extracted word is not exist in sentimental dictionary. Also, we propose the algorithm that add the word to emotional dictionary automatically.

• Korean Journal of School Psychology
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• v.17 no.3
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• pp.243-261
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• 2020

Fear of missing out (FoMO) refers to the desire to stay continually connected with what others are doing because they are afraid of missing the flow or not being included. Although FoMO has been recently proposed as a widespread phenomenon within social media, there has been few empirical research by which mechanism FoMO leads to social networking service (SNS) addiction. Therefore, this study examined whether FoMO mediated the relationship between adolescents' attachment and SNS addiction proneness. A total of 517 middle and high school students participated in the study and completed self-report questionnaires. Results showed that FoMO partially mediated the relationship between adolescents' parental attachment and SNS addiction proneness, whereas the relationship between adolescents' peer attachment and SNS addiction proneness was fully mediated by FoMO. These results suggest that unstable attachment might contribute to SNS addiction through FoMO, especially in case of peer attachment. Lastly, we discussed theoretical and practical implications of this study and suggestions for future research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1619-1637
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• 2016

With wide distribution of smart phones and development of mobile network, social network service (SNS) is displaying remarkable growth rates. Users build new social relations by sharing their interests, which brings surging growth to the SNS based on the combination between the strength of expanding the place for communication and distribution of smart phones featured with easy portability. This study is designed to understand impact factors of SNS on users in Korea and to conduct empirical research on casual relationship between the factors above and the factors affecting personal information behavior through the privacy protection and self-efficacy. In order to accomplish the objective above, the study presented a research model applied with key variables of the Health Belief Model (HBM) predicting behaviors capable of recognizing and preventing individual diseases in the field of health communication. To perform empirical verification on the research model of this study, a survey was conducted upon college students at N university located in Chungcheongnam-do and K university in rural area, who have experiences using the SNS. Through this survey, a total of 186 samples were collected, and path analysis was performed in order to analyze the relationship between the factors. Based on the findings from the survey, first, variables Perceived probability, Perceived severity, Perceived impairment of the HBM, key factors of personal information protection behavior on the SNS, were found to exhibit negative relationship with self-efficacy, and Perceived probability, Perceived benefit, Perceived impairment were found to exhibit negative relationship with privacy protection. But the above, Perceived severity showed positive relationship with privacy protection, and Perceived benefit and self-efficacy also displayed positive relationship. Second, although self-efficacy, a parameter, showed positive relationship with privacy protection, it demonstrated negative relationship with personal information protection behavior. Lastly, privacy protection exhibited positive relationship with personal information protection behavior. By presenting theoretical model reflected with characteristics of prevention based on these findings above unlike previous studies on personal information protection using technologies threatening personal information, this study is to provide theoretical and operational foundation capable of offering explanations how to predict personal information protection behavior on the SNS in the future.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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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.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1975-1976
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• 2011

소셜네트워크의 등장은 기업 환경에도 많은 변화를 가져오고 있다. 초기의 기업 소셜네트워크서비스(SNS)는 자사 고객들과의 커뮤니케이션 채널로 활용되었지만, 최근의 기업 SNS는 자사내의 조직강화 수단으로 인식되기 시작하고 있다. 직원들의 수평적인 아이디어 뱅크와 인맥 형성(Human networks)을 위해서 많은 기업들이 SNS 활용을 시도하고 있다. 기업 SNS의 활용도가 높아지기 위해서는 Anywhere, Anytime 접근 환경이 지원되어야 한다. 기존 SNS 활용도를 폭발적으로 증가시킨 스마트폰과 같은 모바일 단말 지원도 기업 SNS에서도 이루어져야 한다. 그러나, 모바일 단말은 PC와 같은 기존 사용자 환경에 비해서 보안적으로 많은 취약점을 갖고 있다. 이 논문에서는 기업 SNS에모바일 단말 활용 시 대두될 수 있는 보안 취약성을 점검하고, 그에 대한 대응책을 제시한다.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.223-224
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• 2014

최근 빅데이터 시대에 다가와서 소셜 네트워크 서비스(Social Network Service)가 중요한 정보 공유의 수단으로 발전함에 따라 그에 따른 예측분석, 동향분석, 이슈탐지 등이 증가하고 있으며, 콘텐츠 분야에서 빅데이터 기법 사례가 증가하는 추세이다. 모바일기기 보급이 빠르게 확산되면서 SNS 활성화와 함께 많은 양의 데이터가 증가하고 있으며, 인스타그램과 같은 해시태그 사용 가능 SNS 서비스에서 해시태그의 동시출현은 해시태그만의 연관성이 있음을 의미한다. 본 논문에서는 대상 SNS의 동시출현 해시태그를 분석하기 위해 발생되는 데이터를 가지고 현재 트렌드에 맞게 분석하여 정보를 제공하는 방법을 제시한다.

• Journal of Information Technology Applications and Management
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• v.20 no.3
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• pp.31-42
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• 2013

With a focus on Facebook, the most popular social network service (SNS), this research tried to find out which type of motivation makes users to spend more time on the SNS and in the same vein, which type of motivation makes users to believe that they will continue to use the SNS. The result shows that the need for play (entertaining) and image as social reputation affect the current amount of use, while the needs for information search, building relationship, and entertainment would make them continue to use.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.111-114
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• 2019

최근 봇넷(Botnet)은 PC 뿐만 아니라 IoT 기기를 대상으로 확대되어 구축되고 있으며, 최신 기술들이 적용되면서 탐지와 방어가 어렵도록 구축되고 있다. 특히, 해커와 테러범 사이에서 많이 활용되는 정보 은닉 기술인 스테가노그래피(Steganography)가 적용된 Botnet(Stego-botnet)이 출현하였는데, 기존의 Botnet 형태와는 달리 SNS 환경을 Botnet 개체 사이의 통신 기반으로 활용하며 Steganography 기술로 통신 내용을 숨겨 탐지가 어렵기 때문에 그 위험성과 피해가 심각할 수 있다. 본 논문에서는 SNS 환경에서의 Steganography 기반 Botnet 구축 가능성을 조사하고, 실제로 카카오톡을 활용한 Steganography 기반 Botnet 통신 가능성을 실험한 후 결과를 제시하며, Steganography 기반 Botnet에 대한 탐지 및 역추적 방안을 간략히 제안한다.