• Title/Summary/Keyword: Keyword Trends

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A Study on the Research Trends of Effectiveness of Telehealth for the Elderly through Bibliographic Analysis (계량서지 분석을 통한 노인 대상 원격보건의 효과성 연구 동향 규명)

  • Park, Sun Ha;Kim, Mi Kyeong;Park, Hae Yean
    • Therapeutic Science for Rehabilitation
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    • v.11 no.1
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    • pp.7-20
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    • 2022
  • Objective : This study aims to identify international academic trends regarding the effectiveness of telehealth for the elderly through bibliographic analysis and to secure the foundation for providing basic data and subsequent research to promote domestic research. Methods : This study collected bibliographic information on the effectiveness of telehealth for the elderly published in international academia from January 2010 to December 2020 and analyzed and visualized the relationships between information using VOS viewer software (version 1.6.16, CWTS, Netherlands, 2020). Results : First, the research trend analysis shows a 678% increase in the number of papers published over the past 10 years. Most of the research was conducted in 145 (45.89%) Health care science services, and the most papers were published in 39 Telemedicine and e-Health journals (9.11%). Second, the network analysis showed that Oxford University had a total of 168 connections in other countries and institutions in the U.K, indicating the strongest influence in international academic societies. Third, as a result of the keyword analysis, 'older adults (64 times)', 'care (62 times)', 'health (50 times)', 'technology (40 times)', and 'outcomes (41 times)' were used in the study. Conclusion : In this study, the trends and topics of international academia on the effectiveness of telehealth for the elderly were analyzed to form the basis for research activities and the institutional implementation of telehealth for the elderly in Korea.

Analysis of Research Trends in Relation to the Yellow Sea using Text Mining (텍스트 마이닝을 활용한 황해 관련 연구동향 분석연구)

  • Kyu Won Hwang;Kim Jinkyung;Kang Seung-Koo;Kang Gil Mo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.724-739
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    • 2023
  • Located in the sea area between South Korea, North Korea, and China, the Yellow Sea plays an important role from a geopolitical perspective, and recently, as the use of marine space in the Yellow Sea is expanding, its social and economic values have been increasing further. In addition, owing to rapid climate changes, the need for joint response and cooperation between Korea and China is increasing in various fields, including changes in the marine environment and marine ecosystem and generation and movement of air pollutants. Accordingly, in this study, core topics were derived from research papers with the Yellow Sea as a keyword, and research trends to date were explored through author network analysis. As a specific research method, research papers related to the Yellow Sea published between 1984 and 2021 were extracted from the Web of Science database and were classified into four periods to derive core topics using topic modeling, a type of text mining. Furthermore, the influences of major research communities, researchers, and research institutes in the appropriate fields were identified through analyzing the author network, and their implications were presented. The analysis results indicated that the core topics of research papers on the Yellow Sea had changed over time, and differences existed in the influence (centrality) of key researchers. Finally, based on the results of this study, this study aims to identify research trends related to the Yellow Sea, major researchers, and research institutes and contribute to research cooperation between Korea and China regarding the Yellow Sea in the future.

Analysis of trends in domestic research on addiction using text mining and CONCOR (텍스트마이닝과 CONCOR을 활용한 중독 관련 국내 연구 동향 분석)

  • Sol-Ji Lee;Ki-Hyok Youn
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.99-110
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    • 2023
  • This study analyzed 817 articles published in Korean professional journals over the past three years, from 2020 to 2022, using text mining techniques to identify trends in addiction research in Korea and explore development directions. The analysis results are as follows. First, as a result of the analysis of the top keywords, online addiction studies such as smartphones, games, Internet, gambling, and relationship addiction were prominent as the top keywords. Second, as a result of TF-IDF analysis, many addiction studies related to behavioral addiction such as smartphones, games, the Internet, and work addiction have been conducted over the past three years, and in particular, there are many studies on addiction problems such as smartphones, games, and the Internet that have not yet been clinically diagnosed as addiction problems. This is the same as the result of word frequency analysis, and it can be interpreted that recent studies have been remarkably conducted on more diverse addiction problems. Third, the 2-gram analysis shows that words that mainly correspond to behavioral addiction, such as smartphones, games, and the Internet, appear side by side with the keyword addiction, and among them, words paired with smartphones are mentioned a lot in research papers and are being studied. Fourth, as a result of the CONCOR analysis, there were five clusters: a study on universal addiction issues such as alcohol use disorders and the Internet, a study of recovery on drug and gambling addiction, a study on mobile devices and media addiction, a study on the latest trends related to behavioral addiction, and other addiction issues. Finally, based on the results of this study, a direction for future addiction-related research was suggested.

Analyzing Domestic Research Trends on Disclosure of Information By Comparing Major Academic Disciplines (주요 학문분야 비교를 통한 국내 정보공개 연구동향 분석)

  • Na-yun Bae;Hyo-Jung Oh
    • Journal of the Korean Society for information Management
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    • v.41 no.2
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    • pp.295-316
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    • 2024
  • Analyzing research trends is essential for the sustainable development of a discipline and is important for understanding the value of prior research and laying the groundwork for subsequent research. This study aims to draw implications for the future direction of convergence research on the disclosure of information from various disciplines by comparing and analyzing the trends in disclosure of information research in Korea. For this purpose, we analyzed the publication frequency of information disclosure papers listed in the Korea Citation Index (KCI) from 2002 to 2023 and the publication trend by discipline as a time series. In addition, we compared the keyword relationships and specialized research topics of each discipline by applying network analysis and LDA topic modeling techniques to the names and keywords of papers in law, public administration, and library and information science. As a result of the analysis, the law focuses on legal regulations and policy improvement, public administration focuses on changing social needs and administrative operation methods, and LIS focuses on practical approaches to record management and disclosure of information. Based on this, future research directions include combining policy research in law with social change research in public administration and developing realistic policies and operational guidelines from the practical perspective of LIS. Such convergent research will enable the systematic and efficient implementation of disclosure of information systems, contributing to the guarantee of the public's right to know and the enhancement of state transparency.

Trends identification of species distribution modeling study in Korea using text-mining technique (텍스트마이닝을 활용한 종분포모형의 국내 연구 동향 파악)

  • Dong-Joo Kim;Yong Sung Kwon;Na-Yeon Han;Do-Hun Lee
    • Korean Journal of Environmental Biology
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    • v.41 no.4
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    • pp.413-426
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    • 2023
  • Species distribution model (SDM) is used to preserve biodiversity and climate change impact. To evaluate biodiversity, various studies are being conducted to utilize and apply SDM. However, there is insufficient research to provide useful information by identifying the current status and recent trends of SDM research and discussing implications for future research. This study analyzed the trends and flow of academic papers, in the use of SDM, published in academic journals in South Korea and provides basic information that can be used for related research in the future. The current state and trends of SDM research were presented using philological methods and text-mining. The papers on SDM have been published 148 times between 1998 and 2023 with 115 (77.7%) papers published since 2015. MaxEnt model was the most widely used, and plant was the main target species. Most of the publications were related to species distribution and evaluation, and climate change. In text mining, the term 'Climate change' emerged as the most frequent keyword and most studies seem to consider biodiversity changes caused by climate change as a topic. In the future, the use of SDM requires several considerations such as selecting the models that are most suitable for various conditions, ensemble models, development of quantitative input variables, and improving the collection system of field survey data. Promoting these methods could help SDM serve as valuable scientific tools for addressing national policy issues like biodiversity conservation and climate change.

Text Mining-Based Emerging Trend Analysis for the Aviation Industry (항공산업 미래유망분야 선정을 위한 텍스트 마이닝 기반의 트렌드 분석)

  • Kim, Hyun-Jung;Jo, Nam-Ok;Shin, Kyung-Shik
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.65-82
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    • 2015
  • Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

Keyword-based network analysis for contemporary fashion show affected by intermedia

  • Lee, Seulah;Shin, HyunJu;Lee, Younhee;Lee, Hyun-Jung
    • The Research Journal of the Costume Culture
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    • v.28 no.4
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    • pp.562-571
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    • 2020
  • Intermedia refers to the convergence of media. The advance of intermedia has not only facilitated the delivery of brand messages in contemporary fashion shows but also facilitated interactive communication. This study investigated the mediating roles played by various media in fashion and fashion shows, focusing on the phenomenon of intermedia in contemporary fashion shows. To investigate the impact of intermedia on contemporary fashion shows, we conducted a social network analysis-a promising approach for research into fashion trends. Analyzing 159 fashion-related articles published in the 2000s, we extracted intermedia-related words (n=253). The relation-ships between keywords made an analysis of between centrality, and cluster variables applied Clauset-Newman-Moore by using KrKwic and NodeXL programs. The results of the between centrality analysis indicated that the most important factors in contemporary fashion shows are "models" and "stages." We found that the impacts of intermedia on contemporary fashion shows can be divided into four categories: "model performance," "symbolic stage management," "new media utilization," and "convergence in arts." Our analysis thus identified considerable synergy between the characteristics of intermedia and contemporary fashion shows. These results have found intermedia-related commonalities in intermedia and fashion show, and this might increase customer interest in fashion, a positive outcome for the fashion industry.

IoT Based Distributed Intelligence Technology for Hyper-Connected Space (IoT기반 초연결 공간 분산지능 기술)

  • Park, J.H.;Son, Y.S.;Park, D.H.;Cho, J.M.;Bae, M.N.;Han, M.K.;Lee, H.K.;Choi, J.C.;Kim, H.;Hwang, S.K.
    • Electronics and Telecommunications Trends
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    • v.33 no.1
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    • pp.11-19
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    • 2018
  • IoT is used not only as a technical terminology but also as a paradigm representation. As the number of IoT devices spread tremendously throughout the world, they are able to be located anywhere,recognize their environment, and achieve adaptable reactions. All market investigation agencies expect the number of IoT devices to reach tens to hundreds of billions in number. They also expect various technical problems owing to the huge number of connected things and data that will emerge during the AI era. The decentralization of centralized computing for AI is the one of the technical solutions to such problems, and the computing roles for AI will be soon distributed into the things, which can be located anywhere. In this article, the traditional distributed intelligence and its current research activities are introduced, and the next distributed intelligence target for the IoT 2.0 era is briefly touched upon using the keyword Socio-Things.

A Literature Review on Effect of Massage Based on Developmental Stage in Children in Korea (아동 발달단계에 따른 마사지 중재효과에 대한 국내연구 고찰)

  • Lee, Jae Young;Park, So Yeon
    • Journal of East-West Nursing Research
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    • v.22 no.1
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    • pp.1-9
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    • 2016
  • Purpose: We conducted a literature review for analyzing the effect of massage on children according to their developmental stage in Korea. Methods: Various academic databases were utilized for a bibliographic search, and the keyword, 'massage', was used to identify relevant references without limits on years to determine the overall research trends. Finally, 38 references cited from 1998 to 2014 were selected in Korea. Results: Only two studies adapted a randomized controlled trial design. With regard to children's developmental stage, half studies were conducted for neonates. Moreover, the percentage of application of a sensory stimulation protocol in newborn infants was 47.3%. Eighty four point one percent of studies measured physiological characteristics as outcome variables and the rate of growth was the most common (46.5%) physiological characteristic. On the contrary, only one study (4%) was conducted to evaluate the effect of massage on psychological characteristics in school aged and the adolescents. Conclusion: This study provides fundamental data on the development and direction for future studies by analyzing studies on pediatric massage in Korea.

Trends of Nursing Research in the Journal of Oncology Nursing (종양간호학회지 논문 내용과 경향 분석;창간호에서 2007년까지)

  • Chung, Bok-Yae;Yi, Myung-Sun;Choi, Eun-Hee
    • Asian Oncology Nursing
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    • v.8 no.1
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    • pp.61-66
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    • 2008
  • Purpose: Purpose of study was to analyze the research articles in the Journal of Korean Oncology Nursing in order to provide an direction for the future research, Methods: This study analyzed 93 studies published in the Journal of Korean Oncology Nursing, from its beginning year to the year 2007, according to the research objectives. The frame of evaluation included years and types of publication, the theoretical frameworks, research design, subject, data collection method, keyword analysis by MeSH. Results: 45.2% of studies was non-degree based studies. 95.7% of studies was not described theoretical framework in the articles. 71.0% was utilized a non-experimental design. 57% of subjects in researches was patients. 76.3% of studies were used the questionnaire for data collection. Concepts as human, nursing, and health were consistently appeared in research. But concepts of environment has been insufficiently conducted. Conclusion: Researches in the Journal of Korean Oncology Nursing has been changed in methodology and the topics of research for the last 7 yr. It progresses in both quantity and quality. But, it is necessary to conduct research founded on theoretical background, various research design, variability of study subjects and topics as supported by scientifically and empirically.

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