• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.453-459
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• 2022

This study attempted to explore the realization and research direction of a successful metaverse environment in the future by analyzing international research trends of the metaverse using topic modeling. A total of 208 papers among WoS and ScienceDirect papers using metaverse as keywords were selected, and quantitative frequency analysis and topic modeling were performed. As a result, it was confirmed that research has rapidly increased after 2022. The main keywords of the research topics were 'second', 'life', 'learning', 'reality', 'metaverse', 'virtual', 'blockchain', 'nft', 'medical', 'avatar', etc. The topic keywords 'Second life & Education' and 'Virtual Reality & Medical' accounted for a large proportion of 57%, followed by 'Blockchain & Cryptocurrency', 'Avatar & Interaction', and 'Sensing and Device'. As a result of semantic analysis, current metaverse research is focused on application and utilization, and research on underlying technologies and devices is also active. Therefore, it is necessary to identify the commonalities and differences between domestic and foreign studies, and to study the application method considering the domestic environment. In addition, new jurisprudence research is more necessary along with predicting new problems. It is expected that the results of study will provide the right research direction for domestic researchers in the era of digital transformation and contribute to the realization of a digital society.

• 패션비즈니스
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• 제27권4호
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• pp.50-66
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• 2023

The purpose of this study was to examine the word distribution and topic distribution of slow fashion appearing on YouTube in detail and identify the characteristics and aspects related to fashion design through big data analysis and content analysis methods. The specific research results were as follows. First, in the results of the word distribution analysis, "item" appeared the most, 203 times. Also, "one-piece" was a point to pay attention to, as the item had the highest frequency. Second, a total of 5 topics were defined in the topic distribution analysis: topic 1 was "vintage products," topic 2 was "fashion items," topic 3 was "eco-friendly," topic 4 was "life quality emphasis," and topic 5 was "prudent consumption." Third, looking at the relationship between word distribution and topic distribution above, Korean slow fashion on YouTube was actively selecting related design elements that express vintage images in clothing life regardless of trends. In addition, there was a tendency to pursue various basic and high-quality items. Other than those findings, basic items tended to be reinterpreted in various ways through styling methods matched to the vintage image. Lastly, the tendency of slow and small-volume production appeared to emphasize handicrafts and the cultural values of fashion products.

• 한국정보시스템학회지:정보시스템연구
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• 제30권4호
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• pp.303-327
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• 2021

Purpose The online comments on news content have become social information and are understood based on deliberative democracy. Although the related research has focused on the relationship between online comments and their deliberative quality, the social information provided by online comments consists of not only direct information such as comments themselves but also indirect information such as 'likes' and 'dislikes'. Therefore, the research on online comments and deliberative quality should study this direct and indirect information together, and the direction and the degree of the indirect information should be also considered with them. Design/methodology/approach This study distinguishes comments by the attached 'likes' and 'dislikes', identifies highly supported and highly unsupported comments by the intensity of 'likes' and 'dislikes', and investigates the relationship between their existence and the deliberative quality measured as the topic diversity. Then, we applied topic modeling to the 2,390 news articles and their 74,385 comments collected from five news sites. Findings The topic diversities of the supported and unsupported comments are related to the topic diversity of all comments but the degree of the relationship is higher in the case of supported comments. Furthermore, the existence of highly supported and unsupported comments is led to less diversity of all comments compared to the case where those comments are absent. Particularly, when only highly supported comments are present, topic diversity was lower than in the opposite case.

• 한국콘텐츠학회논문지
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• 제22권7호
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• pp.73-80
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• 2022

본 연구는 지난 20여 년간의 국내 소상공인 선행연구 280편을 주제어 네트워크와 LDA 토픽 모델링 분석을 통해 종합적으로 분석하고, 학계에서의 전반적인 시각과 동향을 살펴보았다. 핵심 주제어는 서로 상충 되지만 안정적이고 지속적인 성장을 위해서 필수적인 요소인 '영업'과 '보호'를 선정하였고, 7개의 토픽(토픽 1: 창업, 토픽 2: 디지털, 토픽 3: 세제, 토픽 4: 역량, 토픽 5: 상생, 토픽 6: 규제, 토픽 7: 자금)을 도출하였다. 분석 결과를 토대로, 소상공인들의 지속적인 성장과 발전을 위한 디지털 성숙도 향상의 필요성을 제기하였고, 소상공인들의 직면한 경제적 타격 문제 해결을 위해 범부처 차원의 대응과 새로운 정권 이후에도 존속될 수 있는 기능 수행 조직의 안정성을 제시하였다. 또한, 장기적, 신속성, 세밀성, 새로운 방식으로의 정부 지원 방향에 대한 주목과 선 허용 후, 규제를 하는 네거티브 방식으로의 유연한 접근을 제언하였다.

• 웰빙융합연구
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• 제5권4호
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• pp.33-37
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• 2022

Purpose: This study aims to understand the trend and central concept of domestic researches on laughter therapy. For the analysis, this study used total 72 theses verified by inputting the keyword 'laughter therapy' from 2007 to 2021. Research design, data and methodology: This study performed the development and analysis of keyword co-occurrence network, analyzed the types of researches through topic modeling, and verified the visualized word cloud and sociogram. The keyword data that was cleaned through preprocessing, was analyzed in the method of centrality analysis and topic modeling through the 1-mode matrix conversion process by using the NetMiner (version 4.4) Program. Results: The keywords that most appeared for last 14 years were laughter therapy, depression, the elderly, and stress. The five topics analyzed in thesis data from 2007 to 2021 were therapy, cognitive behavior, quality of life, stress, and the elderly. Conclusions: This study understood the flow and trend of research topics of domestic laughter therapy for last 14 years, and there should be continuous researches on laughter therapy, which reflects the flow of time in the future.

• 한국도서관정보학회지
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• 제50권4호
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• pp.339-358
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• 2019

본 연구의 목적은 광의의 측면에서 지식정보제공이라는 공동의 임무를 수행하는 도서관, 기록관, 박물관간의 협력 플랫폼 구축에 관한 연구의 동향을 토픽 모델링을 통하여 파악하기 위한 것이다. 연구의 목적을 달성하기 위하여 Scopus로부터 이들 세 기관을 동시에 다루는 논문 637편의 서지정보를 수집하였다. 수집된 서지정보 중에서 초록을 대상으로 NetMiner V.4를 통하여 총 5,218개의 단어를 추출한 후 토픽모델링 분석하였으며, 그 결과는 다음과 같다. 첫째, tf-idf의 가중치에 따른 단어출현 빈도를 분석한 결과 '보존(Preservation)'이 가장 높게 나타났으며, 둘째, LDA(Latent Dirichlet Allocation) 알고리즘을 통한 토픽모델링 분석결과 13개의 주제 영역이 도출되었다. 셋째, 13개의 주제 영역을 네트워크로 표현한 결과 '리포지터리 구축(Repository Construction)'을 중심으로 기관간의 협력, 정보자원 보존을 위한 환경 구축, 정부차원에서의 제도와 정책 발굴, 정보자원의 생애주기, 정보자원의 전시, 정보자원의 검색 등이 서로 밀접한 관련성을 가진 것으로 나타났다. 넷째, 13개의 주제 영역의 연도별 동향을 살펴보면, 1998년 이전의 연구는 제도와 정책 발굴, 정보자원의 검색, 정보자원의 생애주기 등과 같이 특정 주제에 한정된 반면, 그 이후의 연구는 보다 다양한 주제를 다룬 것으로 분석되었다.

• 대한산업공학회지
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• 제42권6호
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• pp.421-431
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• 2016

Over the last four decades, industrial engineering (IE) research in Korea has continued to evolve and expand to respond to social needs. This paper aims to identify research topics in IE research and explore their dynamic changes over time. The topic modeling approach, which automatically discovers topics that pervade a large and unstructured collection of documents, is adopted to identify research topics in domestic IE research. 1,242 articles published from 2001 to 2015 in two IE journals issued by the Korean Institute of Industrial Engineers were collected and their English abstracts were analyzed. Applying the Latent Dirichlet Allocation model led us to uncover 50 topics of domestic IE research. The top 10 most popular topics are revealed, and topic trends are explored by examining the dynamic changes over time. The four topics, technology management, financial engineering, data mining (supervised learning), efficiency analysis, are selected as hot topics while several traditional topics related with manufacturing are revealed as cold topics. The findings are expected to provide fruitful implications for IE researchers.

• Journal of Multimedia Information System
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• 제1권1호
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• pp.55-67
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• 2014

Image topic and emotion analysis is an important component of online image retrieval, which nowadays has become very popular in the widely growing social media community. However, due to the gaps between images and texts, there is very limited work in literature to detect one image's Topics and Emotions in a unified framework, although topics and emotions are two levels of semantics that often work together to comprehensively describe one image. In this work, a unified model, Joint Topic/Emotion Multi-Modal Hierarchical Latent Dirichlet Allocation (JTE-MMHLDA) model, which extends previous LDA, mmLDA, and JST model to capture topic and emotion information at the same time from heterogeneous data, is proposed. Specifically, a two level graphical structured model is built to realize sharing topics and emotions among the whole document collection. The experimental results on a Flickr dataset indicate that the proposed model efficiently discovers images' topics and emotions, and significantly outperform the text-only system by 4.4%, vision-only system by 18.1% in topic detection, and outperforms the text-only system by 7.1%, vision-only system by 39.7% in emotion detection.

• 한국정보시스템학회지:정보시스템연구
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• 제27권4호
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• pp.1-33
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• 2018

Purpose The purpose of this study is to review topic and survey methodological trends in 'The Journal of Information Systems' in order to present the practical guidelines for the future IS research. By attempting to conduct a meta-analysis on both topic and survey methodological trends, this study could provide researchers wishing to pursue this line of work further with what can be done to improve IS disciplines. Design/methodology/approach In this study, we have reviewed 185 papers that were published in 'The Journal of Information Systems' from 2010 to 2018 and classified them based on topics studied and survey methodologies used. The classification guidelines, which was developed by Palvia et al.(2015), has been used to capture the topic trends. We have also employed Struab et al.(2004)s' guidelines for securing rigor of validation issues. By using two guidelines, this study could also present topic and rigor trends in 'The Journal of Information Systems' and compare them to those trends in International Journals. Findings Our findings have identified dominant research topics in 'The Journal of Information Systems'; 1) social media and social computing, 2) IS usage and adoption, 3) mobile computing, 4) electronic commerce/business, 5) security and privacy, 6) supply chain management, 7) innovation, 8) knowledge management, and 9) IS management and planning. This study also could offer researchers who pursue this line of work further practical guidelines on mandatory (convergent and discriminant validity, reliability, and statistical conclusion validity), highly recommended (common method bias testing), and optional validations (measurement invariance testing for subgroup analysis, bootstrapping methods for testing mediating effects).

• 한국융합학회논문지
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• 제11권7호
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• pp.9-18
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• 2020

본 논문의 연구목표는 LDA(Latent Dirichlet Allocation) 모델을 적용하여 국가연구개발사업을 통해 수행되고 있는 ICT(Information and Communication Technology) 분야의 연구과제에 대한 주요 연구 토픽과 동향을 탐색하는데 있다. 연구방법에는 NTIS(National Science and Technology Information Service)로부터 최근 5년간 국가연구개발사업의 전체 연구과제 정보를 다운로드받고 이를 정보통신기획평가원(IITP)의 EZone 시스템과 매칭하여 ICT 분야 연구과제 5,200건을 확보하고, 토픽모델링 기법중 하나인 LDA 모델을 적용하여 연구토픽과 연구동향을 조사하였다. 실험결과로, ICT분야 연구과제에 대한 연구토픽은 인공지능, 빅데이터, 사물인터넷(Internet of Things)과 같은 지능정보기술로 확인되었고 연구동향에는 초실감미디어에 관한 연구가 활발히 진행되고 있음을 확인하였다. 끝으로 본 논문에서 진행된 국가연구개발사업에 대한 토픽모델링 결과는 향후 ICT분야 연구개발 계획 및 전략수립, 정책, 과제기획 등 중요한 정보로 활용될 수 있을 것이다.