• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.325-332
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• 2011

Social Network Services(SNS) such as Twitter, Facebook and Myspace have gained popularity worldwide. Especially, sentiment analysis of SNS users' sentence is very important since it is very useful in the opinion mining. In this paper, we propose a new sentiment classification method of sentences which contains formal and informal vocabulary such as emoticons, and newly coined words. Previous methods used only formal vocabulary to classify sentiments of sentences. However, these methods are not quite effective because internet users use sentences that contain informal vocabulary. In addition, we construct suggest to construct domain sentiment vocabulary because the same word may represent different sentiments in different domains. Feature vectors are extracted from the sentiment vocabulary information and classified by Support Vector Machine(SVM). Our proposed method shows good performance in classification accuracy.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.125-134
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• 2014

As the social media which was simple communication media is activated on account of twitter and facebook, it's usability and importance are growing recently. Although many companies are making full use of its the capacity of information diffusion for marketing, the adverse effects of this capacity are growing. Because social network is formed and communicates based on friendships and relationships, the spreading speed of the spam and mal-ware is very swift. In this paper, we draw parameters affecting malicious data diffusion in social network environment, and compare and analyze the diffusion capacity of each parameters by propagation experiment with XSS Worm and Koobface Worm. In addition, we discuss the structural characteristics of social network environment and then proposed malicious data propagation model based on parameters affecting information diffusion. n this paper, we made up BA and HK models based on SI model, dynamic model, to conduct the experiments, and as a result of the experiments it was proved that parameters which effect on propagation of XSS Worm and Koobface Worm are clustering coefficient and closeness centrality.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.341-347
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• 2012

In cloud computing, a enterprise or a client can use resources of computers that they are not own them. In case of Web 2.0 applications, such as Facebook, it is difficult to predict the maximum popularity of the service. But, the cloud computing may give a solution about this problem without high cost, thus becomes wildly popular. One of the advantage of cloud computing is providing a high availability. To provide the availability when the cloud computing that has shared-nothing architecture, strict consistency is not well with cloud computing. So, some consistency was proposed including the eventual consistency that was weaken the traditional consistency and has been adopted to many cloud applications. In this paper, we observe various consistency criteria that can adjust to cloud computing and discuss about some consistency that can be adapted to many applications of cloud computing.

• Journal of Korean Library and Information Science Society
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• v.51 no.1
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• pp.21-41
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• 2020

This paper aims to propose ways to promote SNS marketing at school library sites with case study analyses in school libraries. To this end, in-depth interview was conducted with 10 Teacher Librarians who had used SNS in library operation and an in analysis was made of the operation status, motives and objectives, strategies and performances of the school library's SNS marketing. According to the study, most Teacher Librarians were found to be using SNS such as Facebook, Instagram, Kakao Plus Friends and so on in an attempt to improve accessibility and utilization of the library resources first. Not only that, they used SNS for the purpose of communicating with users while increasing the number of visitors and identifying the needs of users. The messages provided through SNS are information on school libraries and their reading programs, and the target market mainly involved their students. Based on the above research results, measures to promote SNS in school libraries were discussed, including the need for marketing consultative bodies, expansion of SNS targets, and enhancement of expertise in SNS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.935-937
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• 2013

Currently, depending on the penetration of the mobile device, age of one person one mobile device is open. It is a time when mobile equipment is located to the depths of human life that much. However, equipment for new mobile devices full of, was in the existing, tend to sleeping in the house or abandoned. It is determined that you build one server in a mobile device that individuals have, to be able to break out of the framework of the existing service Twitter and blogs, such as Facebook, and to create multiple Web services with a personality of their own. In this paper, we studied a scheme that can be instead of a simple fixed server, considering the characteristics of only the mobile device and take advantage.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.23 no.6
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• pp.548-557
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• 2020

Purpose: To better understand the benefits and harms of engagement with online pediatric liver disease communities within social media. Methods: We conducted a survey of caregivers of children with liver disease participating in online pediatric liver disease communities within social media, as well as a survey of healthcare providers (e.g., physicians, surgeons, nurse coordinators) from this field to better understand the perceived benefits and harms of participation. Results: Among 138 caregivers of children with liver disease that completed the survey, 97.8% agreed social media was a good place to learn about patient experiences and 88% agreed it was a good source of general information. Among caregivers, 84.8% agreed social media helps them to better advocate for their child. While 18% agreed that the information over social media was equal to the information from their healthcare team and 19% neither agreed/disagreed, only 3% indicated they would use this information to change care without telling their provider; in contrast, among 217 healthcare providers, 55% believed social media may lead caregivers to change management without telling their team. Conclusion: Engagement with online disease-specific communities in social media yields several benefits for caregivers and, in contrast to healthcare providers' concerns, participation is unlikely to lead to problems including caregivers changing the treatment plan without first discussing these plans with their team. Openness between caregivers and medical teams about the role for social media can help to improve trust and maximize the potential benefits of engagement with these groups.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.201-208
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• 2015

With services such as SNS and facebook, Big Data popularize the use of small size such as micro blogs are increasing. However, the problem of accuracy and computational cost of the search result of big data of a small size is unresolved. In this paper, we propose a subnet selection techniques based probability to improve the browsing speed of the small size of the text information from big data environments, such as micro-blogs. The proposed method is to configure the subnets to give to the attribute information of the data increased the probability data search speed. In addition, the proposed method improves the accessibility of the data by processing a pair of the connection information between the probability of the data constituting the subnet to easily access the distributed data. Experimental results showed the proposed method is 6.8% higher detection rates than CELF algorithm, the average processing time was reduced by 8.2%.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.149-156
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• 2020

This study investigated the key factors affecting online relational intimacy in the context of SNS. Based on the use and gratification theory, self-presentation, relationship formation and information searching were identified as the main needs of SNS usage. These needs were expected to influence online relational intimacy through user satisfaction, subjective well-being, and disclosing information behaviors. The theoretical framework was validated by a longitudinal method. Hypotheses were tested by using the partial least squares to data from 199 Facebook users. Self-presentation and information searching had a significant impact on both user satisfaction and subjective well-being. However, relationship formation did not significantly affect both user satisfaction and subjective well-being. User satisfaction had a significant direct effect only on online relational intimacy. Subjective well-beings played a significant role in enhancing both disclosing information behaviors and online relational intimacy. Finally, it has been found that disclosing information behaviors are a key factor in enhancing online relational intimacy. The results of this study are expected to provide academic and practical implications for the key antecedents of online relational intimacy.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.3
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• pp.157-180
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• 2013

With increasing interest in content marketing, SNS (social networking services) has become more popular as a method of library marketing, both at home and abroad. Accordingly, this study analyzed the operational status and problems of library SNS marketing, in an attempt to find ways to optimize its use. Results show that librarians' opinions of library marketing and library SNS marketing were very high, but the problems they faced included a lack of human resources dedicated to marketing, lack of marketing education, a lack of content to upload each week, and low numbers of contacts on social networking sites. To further develop and optimize library SNS marketing, five solutions were suggested based on the survey results: first, composing an intensive managing team for effective SNS operation; second, providing different levels of marketing training to decrease the librarians' mistakes; third, updating data continuously; fourth, providing information and services users need; and lastly, clearly identifying each channel's active operation goals.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.