• Knowledge Management Research
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• v.18 no.4
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• pp.137-157
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• 2017

With the rapid growth of the internet, Social Network Services (SNSs) have played an important role. As the use of SNSs increases, users experience a sense of responsibility to respond to other people's messages or requests, and consequently experience an social overload, feeling too much social support for other users. In this study, we examined the effects of social overload on loneliness and SNS discontinuous usage intention. To verify the research model, data were collected from 83 SNS users and analyzed using SmartPLS, a structural equation modeling tool. The results of this study showed that the communal orientation and the degree of use of SNS influenced the social overload, and the social overload had a significant effect on loneliness and SNS discontinuous usage intention. The findings of this study are expected to help understand the social overload and loneliness in the use of SNS, and may also provide a strategic direction for SNS service providers.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.89-107
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• 2013

Recently, the majority of leading companies has a strong interest in SNS advertisement. Therefore, the purpose of this study was to classify lifestyle of SNS adopters in order to support establishing companies' SNS advertising strategy. According to the analysis, (1) SNS advertisement's attributes (Entertainment, Irritation and Credibility) are affecting the Advertising Value, similar to a Mobile advertisement, and (2) Major SNS advertisement's Advertising Value depends on the lifestyle. The results show that : (1) self-express lifestyle is affected by Irritation, and that (2) information collected lifestyle is affected by Entertainment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.2
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• pp.75-85
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• 2014

Recently, mobile SNS traffic has increased tremendously due to the deployment of smart devices such as smart phones and smart tablets. In this paper, mobile integrated SNS gateway is proposed to cope with massive SNS traffic. Most of mobile SNS applications update the information with individual connection to the corresponding servers. The proposed gateway integrates these applications. It is for reducing SNS traffic caused by continuous data request and improving the mobile communication performance. The key elements of the mobile integrated SNS gateway are the synchronization, cache and integrated certification. The proposed protocol and gateway system have implemented on the testbed which deployed on the real network to evaluate the performance of the proposed gateway. Finally, we present the caching performance of gateway system implementation.

• Korean Management Science Review
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• v.32 no.4
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• pp.135-153
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• 2015

In this paper, we intend to understand distinguishable SNS technology contributions for B2C commerce. In order to theorize this, we draw upon Technology-to-Performance chain (TPC) theory to develop the model that could explain how the technology value of the SNS could be realizable. For the purpose of capturing SNS technology effect to B2C channel effectiveness, on the basis of TPC theory, personal productivity is selected as a performance variable instead of satisfaction from SNS usage. Accordingly, as the antecedents of personal productivity, two variables of locatability and timeliness are extracted to reflect Task-technology-fit (TTF) dimension of performance precursors. For the utilization dimension of TPC framework, convenience and recreation tendency of the personal traits in shopping are included as the precursors of SNS utilization in the sense of reflecting utilitarian and hedonic value of SNS adoption. Empirical validation is conducted with reference to promotion and sales event on Facebook, which is chosen as the typical SNS based B2C commerce scenario. The data analysis result provide useful insights to further investigate the firm's SNS usage potentials for business applications.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.195-201
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• 2018

Smartphones and PCs have become essential components of our daily life. People are expressing their opinions freely in SNS by using these devices. We are able to predict public opinions on specific subject by analyzing the related big data in SNS. In this paper, we have collected opinion data in SNS and analyzed reputation by text mining in order to make a prediction for the will of the people before 19th presidential election in South Korea. The result shows that our method makes more accurate estimate than other election polls.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.99-101
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• 2013

본 논문에서는 사춘기 여고생들의 기능성 화장품의 신상품 개발과 성능 향상을 위한 효율적인 정보의 분석과 생산 정책을 위한 SNS 분석시스템을 제안한다. 제안하는 시스템은 여고생들의 기능성 화장품에 관한 SNS 내용을 분석하기 위한 효율적 알고리즘과 방법론을 제안하여 시스템의 처리량을 최대화하고, 각 작업의 수행시간을 최소화한다. 또한 여고생들의 기능성 화장품에 대한 기호 상태를 파악하여, 그 분석 결과를 제품의 개발 및 생산에 반영하기 위한 비주얼 방법론을 함께 제안한다. 따라서 본 논문에서 제안하는 시스템은 단지 화장품에 대한 분석뿐만 아니라 이와 비슷한 소비자의 기호가 빠르게 변화하는 제조업 분야에서 다양하게 응용이 가능하다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.321-324
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• 2015

본 논문에서는 SNS에 존재하는 특정 제품과 브랜드 또는 기업에 대한 평가, 의견, 느낌, 사용 후기 등의 소비자 생각을 수집하여 기업에서 향후 신제품 개발이나 시장 진출 및 확대 등의 경영활동에 활용할 수 있도록 SNS 빅데이터를 문석하고, 이를 활용하여 보다 소집단화 되고 개인화 되어가는 Micro-Trend 중심의 마케팅 활동을 할 수 있는 Micro-Targeting 관련 분석 정보를 제공 모델링하는 것을 제안한다. 본 연구에서는 SNS 데이터의 수집, 저장, 분석에 대한 내용을 다루고 있으며, 특히 마이크로타겟팅을 위한 정보를 머하웃(Mahout)의 유클리드 거리 기반의 유사도와 K-평균 군집 알고리즘을 활용하여 구현하고자 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.435-436
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• 2015

In order to analyze and maximize efficiency of advertise, business put more importance on SNS. Especially, keyword extraction analyses based on Hadoop receive attention. The existing keyword extraction analyses have mostly MapReduce processes. Due to that, it causes problems data base would not update in real time like SNS system. In this study, we indicate limitations of the existing model and suggest new model using Storm technique to analyze data in real time.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.1-10
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• 2012

Recently, Social Network services(SNS) is gaining popularity as Facebook and Twitter. Popularity of SNS leads to active service and social data is to be increased. Thus, social search is remarkable that provide more meaningful information to users. but previous studies using social network structure, network distance is calculated using only familiarity. It is familiar as distance on network, has been demonstrated through several experiments. If taking advantage of social context data that users are using SNS to produce, then familiarity will be helpful to evaluate further. In this paper, reflect user's attention through comments and tags, Facebook context is determined using familiarity between friends in SNS. Facebook context is advantageous finding a friend who has a similar propensity users in context of profiles and interests. As a result, we provide a blog post that interest with a close friend. We also assist in the retrieval facilities using Near Field Communication(NFC) technology. By the experiment, we show the proposed soicial search method is more effective than only tag.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.137-139
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• 2017

During the last decade, the most competitive field may be smartphone industry. Among various smartphone brands, iphone of Apple and Galaxy series of Samsung have continue to keep the hot race of competition. In this point, this study attempts to analyze big data on two the two brands in SNS and to compare the major characteristics and preference of users.