• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• Journal of the HCI Society of Korea
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• v.7 no.1
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• pp.11-17
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• 2012

A number of context information is shared through social network service(SNS). Among them, we focused on the information which is rarely shared for various reasons. The result indicated that users prefer to avoid certain types of context information because of： 1)containing socially unacceptable content, 2)laking of desire for disclosure, and 3)potential risk of privacy. Concerning privacy concern, it was found that users developed their own management strategy to control context information rather than employing existing system features. Drawing on Communication Privacy Management(CPM) theory, we analyzed findings and suggested guidelines for system design.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.693-704
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• 2013

The purpose of this study was to analyze the effects of social network service on the collaborative skills, collaborative satisfaction, and interaction within groups in collaborative learning. The group that used KakaoTalk, one of social network service for working on the collaborative task in the course exhibited higher collaborative skills and collaborative satisfaction (p<.05) than the group that did not use KakaoTalk. When analyzing the amount and the content of the messages produced by the group that used KakaoTalk, the amount of messages did not have an impact on the collaborative skills and collaborative satisfaction.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.135-148
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• 2012

This work is intended to investigate how the factors of enterprise mobile SNS affect user satisfaction and continuous use intention through technology acceptance model proposed by Davis. To achieve the purpose, this researcher explored Information Systems Success model proposed by DeLone & McLean, Technology Acceptance Model proposed by Davis, and Model after Acceptance, and on the basis of the investigation, performed a study. For the data of this work, 9 enterprises, each of which has more than 100 employees and is located in Seoul, were chosen, and a questionnaire survey was conducted on their 276 employees who experienced enterprise mobile SNS. As a data collection tool, a structured self-administered questionnaire was used. For data analysis, SPSS 18.0 and AMOS 18.0 were used for applying Structural Equation modelling. According to the results of this work, three factors of enterprise mobile SNS-systematic factor (system quality, information quality, and service quality), user factor (personal innovation and personal familiarity), social factor (social effects and social interaction)-affected user satisfaction and continuous use intention through perceived availability, perceived easiness, and perceived enjoyment. Also, it was found that the direction of effects matched a theoretical prediction. And, it was revealed that the decision variables and mediating variables significantly affected user satisfaction and continuous use intention. Theoretical and practical meanings were discussed for the study result, and some suggestions were made for the issues of this work and future studies.

• The Journal of Society for e-Business Studies
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• v.18 no.1
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• pp.191-211
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• 2013

The deployment of social network service(SNS) makes the social network game(SNG) as the new value added service of SNS be popular. But, a few study had identified the reason of this popularity and the elements of SNG. Based on the social presence theory and media richness theory, we had tried to identify three community artifacts (i.e. persistent labeling, self presentation and deep profiling) and two media characteristics(i.e. vividness and interactivity) as the SNG elements in this research. Then we had empirically validated the effect of these elements on the SNGexperience (i.e. social presence, perceived enjoyment) and behavioral intentions (i.e. Continuous usage intention, willingness to pay and loyalty) of the users. We conducted a survey to the actual SNG users. 243 data were collected and analyzed by PLS algorism. The results indicated that the community artifacts mediated by the social presence and media characteristics could significantly affect on the experiences and behavioral intentions. These findings could contribute to identify what element could be the reason of social network game popularity and could also contribute to design more attractive social network game in practice.

• Journal of Digital Convergence
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• v.9 no.1
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• pp.189-200
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• 2011

Social media environment has had a significant effect on 'power shift' over the world. Such change was due to the choice of smart people. Accordingly, the Smart Citizens Party PR strategies of $S^6M^2AR^3T^4$ should be formulated in accordance with times. Now, politicians or parties can gain a Specific, Simplicity, Sharing and Strong Synergy effect through Social Network Service (SNS). In addition, in order to embody Mighty, Measurable, and Achievable policies, policy-makers should formulate policies based on a Realistic basis, which can gain people's Reliability in every field Relevant to people's way of a happy life by giving them Time of equal opportunity and making them share the same vision and Target with Target segmentation for all sorts of people, Together. In this sense, twelve kinds of alternative words in The Smart Citizens Party PH strategies are suggested. The study suggests desirable direction of development and alternatives in regard to the trends of The Smart Citizens Party PR strategies. Alternatives that are given in this research paper will receive the people's choice because they are a dynamic force to execute 'mighty and powerful Korea'.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.233-240
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• 2011

In this paper, we design and implement an L-SNS system to reduce ever-increasing adverse effects of the Internet through the strengths of social network service system based on media literacy, including critical comprehension, creative expression, participation, communication ability, etc. The L-SNS system we proposed here was used the Smartphone as a medium of communication for learners, and to let them have indirect experience and real-time interaction. In addition, it provides the environment to make objective decisions through the process examining an in-depth discussion among other learners in the aspect of a third party.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.670-674
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• 2018

Social network service (SNS) related data including comments/text, images, videos, blogs, and user experiences contain a wealth of information which can be used to build recommendation systems for various clients' and provide insightful data/results to business analysts. Multimedia data, especially visual data like image and videos are the richest source of SNS data which can reflect particular region, and cultures values/interests, form a gigantic portion of the overall data. Mining such huge amounts of data for extracting actionable intelligence require efficient and smart data analysis methods. The purpose of this paper is to focus on this particular modality for devising ways to model, index, and retrieve data as and when desired.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.355-373
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• 2015

Social networking services (SNSs) serve to strengthen people's social relationships by providing ways for people to utilize such relationships especially like workplace. With the development of the internet worldwide, the number of SNS users is rapidly growing and a wider range of service types have become available. In this study, we designed a research model with a focus on what makes people use SNSs at workplace and how it is associated with changes in relationship quality and their intention to continue using the services and analyzed data collected for the research model. Theoretically, intrinsic and extrinsic motivation was invoked and measured, in terms of hedonic and utilitarian values, and satisfaction and trust were adopted as variables of relationship quality. Data were collected from Facebook users using workplace, and a partial least squares (PLS) analysis was made on 188 data points. The analysis results showed that two forms of motivation-hedonic and utilitarian-are separated from each other in their influence and that utilitarian value is more important than hedonic value, especially when it comes to users' satisfaction. In addition, the analysis found a weak relationship between satisfaction and trust in SNS environments; this was a little different from the results of previous studies.

• Culinary science and hospitality research
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• v.23 no.7
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• pp.1-10
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• 2017

This study proposed SNS big data analysis method of food service industry in the 4th industrial revolution. This study analyzed the keyword of the fourth industrial revolution by using Google trend. Based on the data posted on the SNS from January 1, 2016 to September 5, 2017 (1 year and 8 months) utilizing the "Social Metrics". Through the social insights, the related words related to cooking were analyzed and visualized about attributes, products, hobbies and leisure. As a result of the analysis, keywords were found such as cooking, entrepreneurship, franchise, restaurant, job search, Twitter, family, friends, menu, reaction, video, etc. As a theoretical implication of this study, we proposed how to utilize big data produced from various online materials for research on restaurant business, interpret atypical data as meaningful data and suggest the basic direction of field application. In order to utilize positioning of customers of restaurant companies in the future, this study suggests more detailed and in-depth consumer sentiment as a basic resource for marketing data development through various menu development and customers' perception change. In addition, this study provides marketing implications for the foodservice industry and how to use big data for the cooking industry in preparation for the fourth industrial revolution.