• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.159-170
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• 2021

The purpose of this study was to understand the knowledge structure through keyword network analysis for the purpose of identifying research trends in the research field of multicultural education. To this end, the research trends and intellectual structure of multicultural education were identified through network analysis of words that appeared more than 6 times in the keywords of the papers registered in the KCI (Korean Journal of Citation Index) from 2002 to 2020. Study changes were analyzed by analysis. As a result of the analysis, the first period (2002-2010) focused on multicultural society and multiculturalism, while the second period (2011-2015) additionally introduced multicultural families, globalization, and teacher education, and the third period (2016-2020), multicultural receptivity, multicultural sensitivity, and multicultural efficacy were newly revealed. The research trend of multicultural education in Korean society over the past 19 years has been confirmed that the research topic has changed from theoretical research to empirical research, and the content of multicultural education has also been specified and expanded by field and subject.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.68-73
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• 2016

This study was conducted to identify trends and knowledge structures associated with recent trends in Korean tourism from 2010 to 2015 using keyword data. To accomplish this, we constructed a network using keywords extracted from KCI journals. We then made a matrix describing the relationships between rows as papers and columns as keywords. A keyword network showed the connectivity of papers that have included one or more of the same keywords. Major keywords were then extracted using the cosine similarity between co-occurring keywords and components were analyzed to understand research trends and knowledge structure. The results revealed that subjects of tourism research have changed rapidly and variously. A few topics related to 'organization-employee' were major trends for several years, but intrinsic and extrinsic factors have been further subdivided and employees of specific fields have been targeted as subjects of research. Component analysis is useful for analyzing concrete research topics and the relationships between them. The results of this study will be useful for researchers attempting to identify new topics.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.307-319
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• 2021

Although it is currently conducting slope management and research using digital technologies such as drones, big data, and artificial intelligence, it is still somewhat insufficient and is still vulnerable to slope failure. For this reason, it is inevitable to present the development direction for research on prediction and analysis of slope failure using the digital technologies to effectively deal with slope failure, which requires a preemptive understanding of prediction and analysis of slope failure. In this paper, we collected literature data based on the Web of Science for five years from January 1, 2016 to December 31, 2020 and analyzed by co-word analysis to identify the domain structure of research on prediction and analysis of slope failure. Detailed subject areas were identified through network analysis, and the domain relationships between keywords were visualized to derive global and regionally oriented keywords through relationship, centrality analysis. In addition, the clusters formed by performing cluster analysis were displayed on the multidimensional scailing map, and the domain structure according to the correlation between each keyword was presented. The results of this study reveal the domain structure of research on prediction and analysis of slope failure, and are expected to be usefully used to find future research directions.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.199-207
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• 2018

This study aims to analyze Next Production Revolution (NPR) technologies through evidence-based keyword network in order to cope with the change of production paradigm called the Fourth Industrial Revolution (4IR). For the analysis, a total of 441 papers related to NPR or 4IR were extracted and the NPR technology network was constructed based on the simultaneous appearance relationship of the author keywords of these papers. Based on the NPR technology network, we explored key technologies through analysis of centrality and keyword group. As a result, technologies such as 'digital twin' and 'modeling and simulation', discovering insights by connecting the virtual and physical world in real time and reflecting them into design and process, are analyzed as key technologies.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.25-43
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• 2019

Recently there has been a growing interest in digital preservation and digital curation with rapid increase of digital resource. This study aims to investigate the research topics and the course topics related digital preservation and digital curation. The course information is collected from the curricular of library and information science departments and archival science departments in leading countries such as US, England, Ireland, Canada and New Zealand. Title keyword profiling and network analysis were adapted to discover core research and education areas. The key topics in the abstracts of research papers and the contents of the course were also illustrated by these methods. In the research analysis, archival system is the biggest area of researches related digital preservation and digital curation. Courser analysis shows digital curation education and process is the important area of education. As a result of content analysis, plan and strategy is a notable topic of research and record management process is a major topic of courses for digital preservation and digital curation. In addition, format of digital resource is an important topic for research and courses.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.587-598
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• 2003

This paper construct two-level word similarity relation matrices about title and to scientific treatise. As guide keyword similarity relation matrices which is constructed to co-occurrence frequency base same time keeps recall rater by query expansion by tolerance relation, it is index structure to improve the precision rate by two-level contents base retrieval. Therefore, draw area knowledge through subject analysis and reasoned user's information request and area knowledge to fuzzy logic base. This research is research to improve vocabulary mismatch problem and information expression having essentially on query.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.21-37
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• 2021

This study investigated the intellectual structure of the latest trends in Korean addiction research in the social sciences. A network analysis of keywords with co-word occurrence was performed on 172 papers from the KCI database based on the data from the year of 2019, and a total of 432 keywords were extracted. The network analysis was performed using several programs: Bibexcel, COOC, WNET, and NodeXL. As a result of the study, keywords related to addiction type, study subjects, research methods, and research variables were found, and a total of 20 clusters were identified. Furthermore, to identify and measure weighted networks, the relationships between each keyword were explored and discussed in detail through a network analysis of global centralities, local centralities, and betweenness centralities. The study indicated that the latest issues were focused on smartphone addiction and provided implications for the future research and practice that fields and topics of relationship addiction, food addiction, and work addiction should be more considered. Further, the study discussed the relationship between drug addiction-crime, alcohol addiction-family, and gambling addiction-motivation and the necessity of qualitative study.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.4
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• pp.27-31
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• 2023

Purpose: This study analyzed papers identified by entering the two keywords 'unification education' and 'university' during research from 2013 to 2022 in order to identify trends and key concepts in unification education research at domestic universities. Research design, data, and methodology: The study analyzed 224 papers, excluding those on primary, middle, and high school unification education, as well as unrelated and duplicate papers. The analysis included developing a co-occurrence network of keywords, utilizing topic modeling to categorize research types, and confirming visualizations such as word clouds and sociograms. Results: In the final analysis, the research identified 1,500 keywords, with notable ones like 'Korea,' 'education,' 'unification.' Centrality analysis, measuring influence through connected keywords, revealed that 'Korea,' 'education,' 'north,' and 'unification' held significant positions. Keywords with high centrality compared to their frequency included 'learning,' 'development,' 'training,' 'peace,' and 'language,' in that order. Conclusions: This study investigated trends and structures in university-level unification education by analyzing papers identified with the keywords 'unification education' and 'university.' The use of keyword network analysis aimed to elucidate patterns and structures in university-level unification education. The significance of the study lies in offering foundational data for future research directions in the field of unification education at universities.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.411-438
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• 2024

This study aims to identify and comprehensively view health information-related research trends using a bibliometric analysis. To this end, 1,193 papers from 2002 to 2023 related to "health information" were collected through the Korea Citation Index (KCI) database and analyzed in diverse aspects: research trends by period, academic fields, intellectual structure, and keyword changes. Results indicated that the number of papers related to health information continued to increase and has been decreasing since 2021. The main academic fields of health information-related research included "biomedical engineering," "preventive medicine/occupational environmental medicine," "law," "nursing," "library and information science," and "interdisciplinary research." Moreover, a co-word analysis was performed to understand the intellectual structure of research related to health information. As a result of applying the parallel nearest neighbor clustering (PNNC) algorithm to identify the structure and cluster of the derived network, four clusters and 17 subgroups belonging to them could be identified, centering on two conglomerates: "medical engineering perspective on health information" and "social science perspective on health information." An inflection point analysis was attempted to track the timing of change in the academic field and keywords, and common changes were observed between 2010 and 2011. Finally, a strategy diagram was derived through the average publication year and word frequency, and high-frequency keywords were presented by dividing them into "promising," "growth," and "mature." Unlike previous studies that mainly focused on content analysis, this study is meaningful in that it viewed the research area related to health information from an integrated perspective using various bibliometric methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.514-523
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• 2021

Recently, the proliferation of mobile simple payment services has been increasingly affecting people's lives. In addition, the increase in research from both China and Korea shows that the continuous development of simple mobile payment services will be very important in the future. The blog posts mentioning Kakao Pay and Alipay were collected, and keyword analysis was performed to investigate differences in consumers' responses to Kakao Pay and Alipay on social media. The frequency of keywords for each part of speech and the frequency of co-occurred words mentioned in one sentence were analyzed. Specifically, common words that appear in both Kakao Pay and Alipay blogs were extracted. The cooccurred words were analyzed to examine how different reactions were made on the same subject. As a result of the analysis, there were concerns among consumers about the trust of Kakao Pay and Alipay's benefits. For a mobile payment service to become competitive, it is necessary to add various additional services or solve security problems.