• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.1
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• pp.43-48
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• 2023

This study analyzed research trends in the field of ecological research. Data were collected based on a keyword search of the SCI, SSCI, and A&HCI databases from January 2002 to September 2022. The seven keywords, including biodiversity, ecology, ecotourism, species, climate change, ecosystem, restoration, wildlife, were recommended by ecological research experts. Word clouds were created for each of the searched keywords, and topic map analysis was performed. Topic map analysis using biodiversity, climate change, ecology, ecosystem, and restoration each generated 10 topics; topic maps analysis using the ecotourism keyword generated 5 topics; and topic map analysis using the wildlife keyword generated 4 topics. Each topic contained six keywords.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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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.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.4
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• pp.19-27
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• 2023

In this study, a total of 2,584 domestic research papers with the keywords "Aviation Safety" and "Aviation Accidents" were subjected to Text Mining analysis. Various text mining techniques, including keyword frequency analysis, word correlation analysis, network analysis, and topic modeling, were applied to examine the research trends in the field of aviation safety. The results revealed a significant increase in research using the keyword "Aviation Safety" since 2015, with over 300 papers published annually. Through keyword frequency analysis, it was observed that "Aircraft" was the most frequently mentioned term, followed by "Drones" and "Unmanned Aircraft." Phi coefficients were calculated for words closely related to "Aircraft," "Aviation," "Drones," and "Safety." Furthermore, topic modeling was employed to identify 12 distinct topics in the field of aviation safety and aviation accidents, allowing for an in-depth exploration of research trends.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.511-518
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• 2012

In this study, the trend in green technology was observed and the domain of the green technology area that will be actively studied in the future was found by establishing knowledge map in green technology area and comparing and analyzing green technology information in Korea and overseas in time series. For the purpose of this study, network analysis was conducted for the keyword of green technology information provided by green technology information portal site (www.gtnet.go.kr) operated by Korea Institute of Science and Technology Information. Network analysis was conducted using keyword, and change of study subject was found by dividing the analysis result into periods. In the result of network analysis on top 100 keywords from total English keyword, it was found that renewable energy related areas such as solar energy and biomass had high centrality. When the main keyword trend by year was studied, centrality of solar cell, nanotechnology, smart grid, and fuel cell were found to increase, showing that research and development in generation and use of renewable energy are actively made.

• MALSORI
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• no.43
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• pp.151-161
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• 2002

This study presents performance analysis results of speaker adaptation for keyword spotting system. In this paper, we implemented MLLR (Maximum Likelihood Linear Regression) method on our middle size vocabulary keyword spotting system. This system was developed for directory services of universities and colleges. The experimental results show that speaker adaptation reduces the false alarm rate to 1/3 with the preservation of the mis-detection ratio. This improvement is achieved when speaker adaptation is applied to not only keyword models but also non-keyword models.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.13-18
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• 2019

In this study, we investigate important keywords and their relationships among the keywords for social issues, and analyze topics to find subjects of the social issues. In particular, we collected twitter data with the keyword 'metoo' which has attracted much attention in these days, and perform keyword analysis and topic modeling. First, we preprocess the twitter data, identified important keywords, and analyzed the relatedness of the keywords. After then, topic modeling is performed to find subjects related to 'metoo'. Our experimental results showed that relatedness of keywords and subjects on social issues in twitter are well identified based on keyword analysis and topic modeling.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.151-158
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• 2019

This study aimed to analyze the research trend related on obesity in physical education in Korea through the keyword network analysis and to establish a basic database for effective design of prospective studies. To achieve it the study crawled co-occured keywords with 'obesity' and 'physical education' from RISS and analyzed the list from 1990 to 2018. They include 25 journal papers and 38 dissertations. The results are as follows. First, recent 30 years 63 papers published in Korea with 'Obesity' and 'Physical Education', and there were 144 related keywords. Second, analyzing journals which have 'Obesity' and 'Physical Education', co-occured keywords in 4 centrality were 24 keywords(student, Korea, prevention, effect, level, body, activation, actual condition, lesson, child, investigation, participation, book, cause, activity, normal, degree, nutrition, physical strength, weight, elementary, light, inquiry, health), and 37 keyword occurred in top 30. Lastly, by CONCOR analysis the result could be divided into 2 clusters. One consists of the object of obesity and its invervention, and the other consists of negative keywords of obesity and its preliminery dimenstion. Through the result, this study showed the research trend which involves the concept of obesity in physical education in Korea. Through the result, prospective obesity research in physical education in Korea would be promoted.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.89-103
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• 2022

The purpose of this study is to explore professors' perception of blended learning. For this purpose, the reflective journals written by 56 university professors was analyzed using the keyword network analysis method. The results of this study are as follows: First, as a result of keyword frequency analysis for the blended learning, the keywords showed the highest frequency in the order of (1) 'instructional design', 'student', 'instructional method', 'learning objective' in the area of learning, (2) 'importance', 'instruction', 'feeling', 'student' in the area of feeling, and (3) 'semester', 'plan', 'weekly', and 'instruction' in the area of action plan. Second, the results of analyzing the degree, closeness centrality, and betweenness centrality of network connection are as follows. (1) The keywords 'instruction', 'instructional method', 'instructional design', and 'learning objective' in the area of learning, (2) the keywords 'instruction', 'importance', and 'necessity' in the area of feeling, and (3) 'instruction', 'plan', and 'semester' in the area of action plan showed high values in degree, closeness centrality, and betweenness centrality. Based on the research results, implications for blended learning and professors' perception were discussed.

• Journal of the Korea Fashion and Costume Design Association
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• v.24 no.4
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• pp.73-85
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• 2022

The purpose of this study is to conduct more practical subsequent research by identifying research areas through a systematic analysis of sustainable fashion design research trends. For this study, 117 journals domestic journals published between 2010 and 2020 were selected using the keyword, 'sustainable fashion'. With the research materials, six top keywords, 'zero waste', 'sustainability', 'eco-friendly', 'upcycling', 'recycling', and 'ethical', were derived. The research status was examined by year, keyword, keyword and year, and research topic. The analysis results are as follows. First, looking into the studies by year, it was found that research on sustainable fashion increased in general. Compared to 2010, the research tripled in 2020, and it was found to have increased steadily from 2018. Second, regarding the research by keyword, eco-friendly was the most common. It can be seen that research tended to focus on recycling or eco-friendliness before, but in later material design development was heading towards upcycling. Third, concerning the research by topic, case studies were found the most before, but research on design development tended to increase recently. Based on that, it is expected that the areas of sustainable fashion design that need more research will be investigated further.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.309-330
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• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.