• Journal of Digital Contents Society
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• v.19 no.1
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• pp.51-58
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• 2018

As the amount of users and data of NS explosively increased, research based on SNS Big data became active. In social mining, Latent Dirichlet Allocation(LDA), which is a typical topic model technique, is used to identify the similarity of each text from non-classified large-volume SNS text big data and to extract trends therefrom. However, LDA has the limitation that it is difficult to deduce a high-level topic due to the semantic sparsity of non-frequent word occurrence in the short sentence data. The BTM study improved the limitations of this LDA through a combination of two words. However, BTM also has a limitation that it is impossible to calculate the weight considering the relation with each subject because it is influenced more by the high frequency word among the combined words. In this paper, we propose a technique to improve the accuracy of existing BTM by reflecting semantic relation between words.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.195-200
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• 2019

Nowadays as the use of mobile communication devices such as smart phones and tablets and the use of Computer is expanded, data is being collected exponentially on the Internet. In addition, due to the development of SNS, users can freely communicate with each other and share information in various fields, so various opinions are accumulated in the from of big data. Accordingly, big data analysis techniques are being used to find out the difference between the response of the general public and the response of the media. In this paper, we analyzed the public response in SNS about child allowance and childbirth grant and analyzed the response of the media. Therefore we gathered articles and comments of users which were posted on Twitter for a certain period of time and crawling the news articles and applied sentiment analysis. From these data, we compared the opinion of the public posted on SNS with the response of the media expressed in news articles. As a result, we found that there is a different response to some national policy between the public and the media.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.137-148
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• 2024

The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.504-506
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• 2019

The text and diary data of many SNSs around the world are uploaded, but it does not go beyond sharing and recording the data. In general, social big data is used to identify taste and interests. However, there is a need for a system that analyzes and displays their status and information. Therefore, in this paper, the happiness diary system deals with the design of the system that can record the data of the SNS and its own diary, store them in the big data system, and express the happiness through their diary and SNS data using emotional analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.441-444
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• 2012

오늘날 스마트폰의 보급으로 SNS는 급속도로 성장하였고, 매일 엄청난 분량의 텍스트 데이터가 생성되고 있다. 본 연구에서는 다른 매체에 비해 개인의 의견이 좀 더 거침없이 올라오는 SNS의 특징에 주목해 SNS의 텍스트 데이터를 대상으로 하는 평판 분석 기법을 제안한다. 제안 방법은 분석하고자 하는 대상에 대한 SNS 데이터를 수집하여 DB에 저장한 다음, 광고 제거 과정과 자동 띄어쓰기 과정 및 형태소 분석을 거친 후 감성 포함 여부 확인 과정과 극성 분류 과정으로 구성된다. 평판 분석을 위해 본 연구에서는 감성 단어 사전의 쾌-불쾌 수치와 활성화 수치를 사용한다. 분석 결과 모든 문서에 대한 극성 분류 정확도는 55%였고, 감성 포함 여부 확인 과정이 올바르게 수행된 문서에 대한 극성 분류 정확도는 82%였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1211-1213
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• 2013

최근에 인터넷의 발전으로 인하여 기업의 마케팅도 변화하고 있다. 소설네트워크서비스(SNS)가 등장하고 이를 이용하는 사용자가 많아짐에 따라 기업에서는 사용자를 위한 새로운 마케팅으로 빅데이터를 활용하는 방법을 생각하고 있다. 하지만 기업에서는 SNS 이용하는 사용자의 생각과 관심을 찾기가 쉽지 않아 SNS 마케팅을 활용하기 힘들고 정보도 많이 부족하다. 따라서 빅데이터의 사용자가 선호하는 것, 좋아하는 것, 싫어하는 것과 같은 생각을 분석하기 위한 방법이 필요하다. 이처럼, 본 논문에서는 이러한 문제점을 해결하고자 빅데이터를 분석함으로써 기업에게 정확성하고 신뢰성 있는 정보를 제공하여 정보의 가치를 높여 기업의 마케팅에서 활용할 수 있는 방안에 대해 연구한다.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.75-95
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• 2012

This study focuses on examining the determinants of smartphone-based social network services(SNS) use. That is, the study explores the key factors affecting the use of smartphone-based SNS. People who have been using online-based SNS such as Cyworld and Facebook for years are now using mobile-based SNS such as KakaoStory. Under the situation. the study attempts to draw key determinants of smartphone-based SNS use from the studies of TAM, hedonic information systems, and social perspectives. To test the hypotheses, we conducted partial least squares (PLS) analysis using a total of 233 data collected on the users of smartphone-based SNS including KakaoTalk and KakaoStory. The key findings are as follows : first, it is verified that both ease of use and usefulness, two main factors in TAM, had positive effects on smartphone-based SNS use. Second, for enjoyment and escapism considered as the two main factors of hedonic IS characteristics, only the effect of enjoyment on SNS use was significant. Finally, social ties as a factor of social characteristics had the most significant effect on smartphone-based SNS use. The result implies that smartphone-based SNS can be one of the major means of maintaining existing social ties.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.1-15
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• 2017

Social Network Service (SNS) emerged to become a major platform for consumers' social activities, affecting their choice behavior. With rapid increase in SNS adoption among consumers, firms actively apply SNS into their marketing activities and use it as an important communication medium with consumers. Particularly SNS marketing become increasingly prevalent in Chinese restaurant sector as they provide promotional information to consumers through SNS. It is urgent for firms to understand the extent of SNS impact on consumers' choice behavior, and to understand consumers' response toward SNS in order to develop more effective SNS marketing strategies. The purpose of this study is to assess the effects of four SNS characteristics on brand equity and purchase intention and to determine the relative importance among these four characteristics on brand equity and purchase intention. Results show that all of the characteristics have significant influence on consumers' brand equity, and also, brand equity affects consumers' purchase intention.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.583-592
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• 2020

With the popularization of smartphones, Social Networking Service (SNS) has become the means of communication for modern people. Due to the nature of the means of communication, SNS generates a variety of archive and preservation evidence. Therefore, it is a major analysis target in terms of digital forensic investigation. An application that provides SNS stores data in a central server or database in a smartphone inside for user convenience. Some applications provide encryption for privacy, which can be anti-forensic in terms of digital forensic investigation. Therefore, the study of the encryption method should be continuously preceded. In this paper, we analyzed two applications that provide SQLite-based database encryption through SQLCipher module. Each database was decrypted and key data was identified.

• The Journal of Bigdata
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• v.2 no.1
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• pp.27-39
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• 2017

The importance of online communication is getting increased by the rapid growth of smartphone supply and Social Network Service (SNS) use. Catching up with the trend, firms are actively use SNS to improve brand image, promote products, and communicate with customer. On the one hand, SNS is the channel for firms' marketing activities, but on the other, it is also the channel where the events related to the firms propagate in real time. Firms are led to unexpected state of crisis, when events are quickly spread out on SNS. Then firms are assessed their image by the way they deal with the state of crisis. This paper proposes to figure out user response on SNS according to each crisis response strategies by analyzing event-related twitter data when crisis situations of firms arise. We classify crisis response strategies into response attitude, defensive and accommodative response, and response speed, fast and slow response. This paper suggests optimal crisis response strategy to firms regarding state of crisis propagated on SNS.