• Title/Summary/Keyword: Keyword Trends

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Research Trends and Tasks in the field of Public Library Programs in Korea (국내 공공도서관 프로그램 분야의 연구 동향과 과제)

  • Pan Jun, Kim
    • Journal of the Korean Society for Library and Information Science
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    • v.56 no.4
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    • pp.51-71
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    • 2022
  • Since the 1990s, the growth of the public library program field progressed rapidly at home and aborad as the proportion of programs increased as a major job for public libraries in response to social changes and user demands. However, it is difficult to find a study to grasp the overall research trend in the field of public library programs in Korea. Accordingly, intellectual structure analysis was performed based on keyword profiling to examine research trends in the domestic public library program field. In particular, keyword analysis, network analysis and cluster analysis, and period/year analysis were performed step by step based on the author keywords (uncontrolled keywords) of degree papers and academic journals retrieved from the RISS database. In addition, based on the results of this intellectual structure analysis, the research trends of public library programs were comprehensively reviewed and future research tasks were presented.

Research on Overseas Trends and Emerging Topics in Field of Library and Information Science (문헌정보학분야 해외 연구 동향 및 유망 주제 분석 연구)

  • Bon Jin Koo;Durk Hyun Chang
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.3
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    • pp.71-96
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    • 2023
  • This study aimed to investigate key research areas in the field of Library and Information Science (LIS) by analyzing trends and identifying emerging topics. To facilitate the research, a collection of 40,897 author keywords from 11,252 papers published in the past 30 years (1993-2022) in five journals was gathered. In addition, keyword analysis, as well as Principal Component Analysis (PCA) and correlation analysis were conducted, utilizing variables such as the number of articles, number of authors, ratio of co-authored papers, and cited counts. The findings of the study suggest that two topics are likely to develop as promising research areas in LIS in the future: machine learning/algorithm and research impact. Furthermore, it is anticipated that future research will focus on topics such as social media and big data, natural language processing, research trends, and research assessment, as they are expected to emerge as prominent areas of study.

Research Trends and Tasks in the field of Reading Program in Korea (국내 독서 프로그램 분야의 연구 동향과 과제)

  • Pan Jun Kim
    • Journal of the Korean Society for information Management
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    • v.41 no.2
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    • pp.47-69
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    • 2024
  • Despite many changes occurring in the objects and methods of reading, the importance of reading as the most effective means of developing human intellectual ability is consistently emphasized. However, in Korea, reading tends to be perceived as a part of tedious and rigid education or learning activities rather than an act of giving pleasure and joy while accompanied by fun and interest. In addition, compared to the high interest and emphasis on reading, discussions on reading programs to systematically implement them are relatively insufficient, and it is difficult to find a study in Korea that grasp the overall research trend in the field of reading programs. Accordingly, in order to generally examine research trends in the field of domestic reading programs, an intellectual structure analysis method based on keyword profiling was applied. In particular, basic analysis, keyword analysis, research area analysis, and analysis by period and year were performed in stages based on the keywords of theses and academic journal articles in the domestic reading program field retrieved from the RISS database. In addition, future research tasks were presented by comprehensively reviewing the research trends of domestic reading programs identified as a result of this intellectual structure analysis.

Analysis of Trend and Convergence for Science and Technology using the VOSviewer

  • Jeong, Dae-hyun;Koo, Youngduk
    • International Journal of Contents
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    • v.12 no.3
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    • pp.54-58
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    • 2016
  • In this study, articles of the science and technology field that had been monitored for the period from 2002 to 2013 using GTB (Global Trends Briefing) were analyzed. Specifically, the VOSviewer was used to analyze the annual science and technology trends by keyword and the science and technology standard-classification information indicated in the GTB articles, and the convergence trends were therefore monitored. The findings of this study show that active studies were under way in the fields of material science and new and renewable energy, and that convergence has progressed. This result indicates that the information of the articles on papers and patents is more reliable, as it can reflect the current trends more rapidly in the science and technology field than the paper information or the patent information that is traditionally used in analyses of science and technology information.

Keyword Network Analysis of Trends in Research on Climate Change Education (키워드 네트워크 분석을 활용한 기후변화 교육 관련 연구동향 분석)

  • Kim, Soon Shik;Lee, Sang Gyun
    • Journal of the Korean Society of Earth Science Education
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    • v.13 no.3
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    • pp.226-237
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    • 2020
  • The purpose of the research is to analyze research trends related to climate change education by network analysis based on keywords extracted from the research title. For this purpose, 62 papers were selected from Korean Citation Index(KCI) journals published from 2011 to 2020 using such keywords as "climate change" and "climate change education" in the Research Information Sharing Service. The analysis procedure consisted of selection of analysis papers, keyword extraction and purification, and keyword network analysis and visualization. Textom, Ucinet 6.0, and NetDraw were used to analyze the frequency, degree centrality, and betweenness centrality. The results of the research showed that, first, Early 'Energy and Climate Change Education' had the highest frequency of papers examining climate change education. Second, the keywords/phrases that appeared most frequently in research on climate change education were "program" "energy," "analysis," "elementary school," "elementary school," "elementary school students," "development," and "impact." Third, the analysis of the centrality of betweenness centrality showed that the index of 'program', 'primary students' and 'primary schools' were the highest, and the largest group was 'development and effect of teaching and learning programs'. Based on these results, it was concluded that future research on climate change education needs to be examined in further detail and expanded into more specific areas.

Exploration of Research Trends in The Journal of Distribution Science Using Keyword Analysis

  • YANG, Woo-Ryeong
    • The Journal of Industrial Distribution & Business
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    • v.10 no.8
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    • pp.17-24
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    • 2019
  • Purpose - The purpose of this study is to find out research directions for distribution and fusion and complex field to many domestic and foreign researchers carrying out related academic research by confirming research trends in the Journal of Distribution Science (JDS). Research Design, Data, and Methodology - To do this, I used keywords from a total of 904 papers published in the JDS excluding 19 papers that were not presented with keywords among 923. The analysis utilized word clouding, topic modeling, and weighted frequency analysis using the R program. Results - As a result of word clouding analysis, customer satisfaction was the most utilized keyword. Topic modeling results were divided into ten topics such as distribution channels, communication, supply chain, brand, business, customer, comparative study, performance, KODISA journal, and trade. It is confirmed that only the service quality part is increased in the weighted frequency analysis result of applying to the year group. Conclusion - The results of this study confirm that the JDS has developed into various convergence and integration researches from the past studies limited to the field of distribution. However, JDS's identity is based on distribution. Therefore, it is also necessary to establish identity continuously through special editions of fields related to distribution.

A Text Mining Analysis of HPV Vaccination Research Trends (텍스트마이닝을 활용한 HPV 백신 접종 관련 연구 동향 분석)

  • Son, Yedong;Kang, Hee Sun
    • Child Health Nursing Research
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    • v.25 no.4
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    • pp.458-467
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    • 2019
  • Purpose: The purpose of this study was to identify human papillomavirus (HPV) vaccination research trends by visualizing a keyword network. Methods: Articles about HPV vaccination were retrieved from the PubMed and Web of Science databases. A total of 1,448 articles published in 2006~2016 were selected. Keywords from the abstracts of these articles were extracted using the text mining program WordStat and standardized for analysis. Sixty-four keywords out of 287 were finally chosen after pruning. Social network analysis using NetMiner was applied to analyze the whole keyword network and the betweenness centrality of the network. Results: According to the results of the social network analysis, the central keywords with high betweenness centrality included "health education", "health personnel", "parents", "uptake", "knowledge", and "health promotion". Conclusion: To increase the uptake of HPV vaccination, health personnel should provide health education and vaccine promotion for parents and adolescents. Using social media, governmental organizations can offer accurate information that is easily accessible. School-based education will also be helpful.

A Study on the Current Status of Supply Chain Risks after COVID-19: Focusing on Network Analysis (코로나19 이후 공급사슬 리스크에 대한 현황연구: 네트워크 분석을 중심으로)

  • EuiBeom Jeong;Keontaek Oh
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.4
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    • pp.77-92
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    • 2023
  • In this study, keyword network analysis was performed based on global and domestic journals, and network text analysis was conducted for news and articles to examine major issues and research trends on supply chain risks after COVID-19. As a result of analyzing the supply chain risk, after COVID-19 which was relatively insufficient in previous studies, research trends and topics such as supply chain risk recovery, response and public welfare, which are different from previous previous studies, were found in global and domestic journals, news and articles and it was possible to suggest practical strategies and insights for supply chain risk strategies for firms.

Analyzing Research Trends in Forest Watersheds Using the Vosviewer Program (VOSviewer 프로그램을 이용한 산림유역 관련 연구동향 분석)

  • Ji-Eun Lee;Rhee-Hwa Yoo;Min-Jae Cho
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.6_3
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    • pp.1183-1195
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    • 2023
  • In this study, we collected and analyzed domestic and international studies related to watersheds in the forest sector. Keyword co-occurrence analysis was conducted using the VOSviewer program to identify the research areas of domestic and international studies and the network structure to compare research trends. As a result, the number of research articles in international watershed-related studies showed an overall increasing trend, and the research areas were diverse and located close to each other, indicating that many convergence studies were conducted. On the other hand, the number of papers in domestic watershed-related studies seems to have stagnated overall from the past to the present, and the research areas are mainly focused on forest disasters and hydrology, with limited interdisciplinary convergence studies. In addition, in both domestic and international studies, watersheds are currently mentioned as research sites rather than management or analysis units in the forest sector. It is important to actively promote interdisciplinary research in Korea to provide a scientific and balanced basis for watershed-level forest management planning.

Investigation of Research Trends in the D(Data)·N(Network)·A(A.I) Field Using the Dynamic Topic Model (다이나믹 토픽 모델을 활용한 D(Data)·N(Network)·A(A.I) 중심의 연구동향 분석)

  • Wo, Chang Woo;Lee, Jong Yun
    • Journal of the Korea Convergence Society
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    • v.11 no.9
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    • pp.21-29
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    • 2020
  • The Topic Modeling research, the methodology for deduction keyword within literature, has become active with the explosion of data from digital society transition. The research objective is to investigate research trends in D.N.A.(Data, Network, Artificial Intelligence) field using DTM(Dynamic Topic Model). DTM model was applied to the 1,519 of research projects with SW·A.I technology classifications among ICT(Information and Communication Technology) field projects between 6 years(2015~2020). As a result, technology keyword for D.N.A. field; Big data, Cloud, Artificial Intelligence, extended keyword; Unstructured, Edge Computing, Learning, Recognition was appeared every year, and accordingly that the above technology is being researched inclusively from other projects can be inferred. Finally, it is expected that the result from this paper become useful for future policy·R&D planning and corporation's technology·marketing strategy.