• Journal of Digital Convergence
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• v.18 no.9
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• pp.363-371
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• 2020

This study based on the digital innovation of the fashion industry has researched digital-based face design that already has many users all over the world through social media and has influenced the fashion industry. The purpose of this study is to present the future vision of the direction of the fashion industry by classifying representative cases of augmented reality-based digital face design and deriving the oriented value that penetrates them. It was needed to analyzing 3D designer's works that provide digital filter-based face design to the public through Instagram and Facebook. As a result of observing the oriented value of digital face design from the point of view of modern fashion through case exploration, three trends were drawn: experimental formativeness orientation, playful experience orientation, and future technology orientation. This study limited the scope to digital-based face design, but the conclusions presented through these are applicable to all areas of fashion. Therefore, it is supposed to expect to study new phenomena related to fashion design and fashion communication based on digital augmented reality beyond the scope of face design in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.631-637
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• 2014

Recently, SNS is widely used for various purposes such as fast decision making or effective business process in educational institutions or enterprise as well as general services for social networking. Unfortunately, all of existing general SNS platforms do not provide user groups with workspaces for sharing information in a hierarchical way, nor support the functionality of workspace backup for migrations. In this paper, we present a collaborative workspace environment named ElggSpace which extends the Elgg SNS platform with the C3ware collaborative middleware. With the help of C3ware, ElggSpace systematically supports collaborative workspaces that enable user groups to share massive resource in cloud storages. In addition, ElggSpace allows high-level access controls for resources management and the functionality of resource backup, supporting effective collaboration.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.69-74
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• 2012

Many internet users attempt to focus on the issues which have posted on social network services in a very short time. When some social big issue or event occurred, it will affect the number of comments and retweet on that day in twitter. In this paper, we propose the method of extracting core events based on timeline analysis, sentiment feature and retweet information in twitter data. To validate our method, we have compared the methods using only the frequency of words, word frequency with sentiment analysis, using only chi-square method and using sentiment analysis with chi-square method. For justification of the proposed approach, we have evaluated accuracy of correct answers in top 10 results. The proposed method achieved 94.9% performance. The experimental results show that the proposed method is effective for extracting core events in twitter corpus.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.3
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• pp.67-91
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• 2021

The purposes of this study is to identify the perception of students' use of university libraries' public relations activities using Instagram and propose ways to improve the operation of university libraries' Instagram. To this end, the status of Instagram operations of domestic and foreign university libraries was investigated, and a survey was conducted on 292 students who used the library Instagram of their universities. Based on the research results, first, it is necessary to promote the use of libraries by using 'Library Events' information closely related to the use of Instagram by students, but planning ways to participate that can lead to practical use of libraries. Second, it is necessary to promote the role of librarians through Instagram and utilize daily communication information in order to positively affect library image recognition. Third, it is necessary to guide users on how to inquire on library Instagram and actively respond to communication with users through periodic post uploads and monitoring.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.480-493
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• 2021

In this paper, we attempt to empirically explain the process by which fandom performs social participation using digital media. To do this, we utilize the concept of identification and the Situational Theory of Publics in a theoretical framework, and study ARMY, BTS fandom. We confirmed a positive association between communication behavior and social participation, and verified a mediating effect of the identification as well. Interestingly, horizontal identification, a fan-to-star friendly relationship, had a greater effect on moving toward social participation than did vertical identification, a fan's blind worship of a star. This study has significance in that it has figured out the relationship of personal feelings to public participation by mobilizing achievements in various research fields.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.215-224
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• 2021

Business stakeholders have shown huge interests on the way how to increase business value by integrating real world businesses with a rising metaverse concept. To understanding the utility of metaverse regarding digital transformation, this study conducted a qualitative study based on a metaverse framework from 2006 Metaverse Roadmap and reference theories on business models. Specifically, a multiple comparative case approach was adopted to investigate three metaverse application cases from 2000 to 2020. From findings, it was revealed that different metaverse features were tried to leverage traditional simulation games, social communities, and virtual communication activities to build business models. Secondly, the use of metaverse features were likely to be helpful in getting competitive advantages. However, we are also aware that stakeholder credibility should be carefully managed to sustain businesses.

• Information Systems Review
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• v.25 no.3
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• pp.1-26
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• 2023

A theoretical model of information overload (Jackson and Farzaneh, 2012) with its three influential components (i.e., time, technology, and social networks) was empirically tested in the context of news consumption behavior considered as a communicative outcome. Using a national sample of South Korean adults (N = 1166), data analyses identified perceived information overload and large/diverse social networks positively associated with active and passive news consumption. Findings may imply the existence of individually varying cognitive threshold (i.e., tipping point), if crossed individuals cannot process information any further. News consumers may keep searching and receiving information to verify factuality of news even when they feel overloaded.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Food Hygiene and Safety
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• v.31 no.3
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• pp.153-166
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• 2016

The purpose of this study was to investigate consumers' perceptions on monosodium L-glutamate (MSG) in social media. Data were collected from Naver blogs and Naver web communities (Korean representative portal web-site), and media reports including comment sections on a Yonhap news website (Korean largest news agency). The results from Naver blogs and Naver web communities showed that it was primarily mentioned MSG-use restaurant reviews, 'MSG-no added' products, its safety, and methods of reducing MSG in food. When TV shows on current affairs, newspaper, or TV news reported uses and side effects of MSG, search volume for MSG has increased in both PC and mobile search engines. Search volume has increased especially when TV shows on current affairs reported it. There are more periods with increased search volume for Mobile than PC. Also, it was mainly commented about safety of MSG, criticism of low-quality foods, abuse of MSG, and distrust of government below the news on the Yonhap news site. The label of MSG-no added products in market emphasized "MSG-free" even though it is allocated as an acceptable daily intake (ADI) not-specified by the Joint FAO/WHO Expert Committee on Food Additives (JECFA). When consumers search for MSG (monosodium L-glutamate) or purchase food on market, they might perceive that 'MSG-no added' products are better. Competent authorities, offices of education and local government provide guidelines based on no added MSG principle and these policies might affect consumers' perceptions. TV program or news program could be a powerful and effective consumer communication channel about MSG through Mobile rather than PC. Therefore media including TV should report item on monosodium L-glutamate with responsibility and information based on scientific background for consumers to get reliable information.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.581-592
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• 2016

WebRTC has quickly grown to be the world's advanced real-time communication in several platforms such as web and mobile. In spite of the advantage, the current technology in WebRTC does not handle a big-streaming efficiently between peers and a large amount request of users on the Signaling server. Therefore, in this paper, we put our work to handle the problem by delivering the flow of data with dynamical load balancing algorithms. We analyze the request source users and direct those streaming requests to a load balancing component. More specifically, the component determines an amount of the requested resource and available resource on the response server, then it delivers streaming data to the requesting user parallel or alternately. To show how the method works, we firstly demonstrate the load-balancing algorithm by using a network simulation tool OPNET, then, we seek to implement the method into an Ubuntu server. In addition, we compare the result of our work and the original implementation of WebRTC, it shows that the method performs efficiently and dynamically than the origin.