• 제목/요약/키워드: keyword co-occurrence analysis

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다중빈도 키워드 가시화에 관한 연구 (A Study on Multi-frequency Keyword Visualization based on Co-occurrence)

  • 이현창;신성윤
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 춘계학술대회
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    • pp.103-104
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    • 2018
  • Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

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다중빈도 키워드 가시화에 관한 연구 (A Study on Multi-frequency Keyword Visualization based on Co-occurrence)

  • 이현창;신성윤
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 춘계학술대회
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    • pp.424-425
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    • 2018
  • Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

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출현회수에 따른 키워드 가시화 연구 (Keyword Visualization based on the number of occurrences)

  • 이현창;신성윤
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2019년도 춘계학술대회
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    • pp.484-485
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    • 2019
  • Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

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키워드 빈도수에 따른 시각화 연구 (Keyword Visualization based on the Number of Occurrences)

  • 이현창;신성윤
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.565-566
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    • 2021
  • Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

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다학제 분야 학술지의 주제어 동시발생 네트워크를 활용한 기술예측 연구 (A Study on Technology Forecasting based on Co-occurrence Network of Keyword in Multidisciplinary Journals)

  • 김현욱;안상진;정우성
    • 한국경영과학회지
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    • 제40권4호
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    • pp.49-63
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    • 2015
  • Keyword indexed in multidisciplinary journals show trends about science and technology innovation. Nature and Science were selected as multidisciplinary journals for our analysis. In order to reduce the effect of plurality of keyword, stemming algorithm were implemented. After this process, we fitted growth curve of keyword (stem) following bass model, which is a well-known model in diffusion process. Bass model is useful for expressing growth pattern by assuming innovative and imitative activities in innovation spreading. In addition, we construct keyword co-occurrence network and calculate network measures such as centrality indices and local clustering coefficient. Based on network metrics and yearly frequency of keyword, time series analysis was conducted for obtaining statistical causality between these measures. For some cases, local clustering coefficient seems to Granger-cause yearly frequency of keyword. We expect that local clustering coefficient could be a supportive indicator of emerging science and technology.

기술-산업 연계구조 및 특허 분석을 통한 미래유망 아이템 발굴 (Discovery of promising business items by technology-industry concordance and keyword co-occurrence analysis of US patents.)

  • 고병열;노현숙
    • 기술혁신학회지
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    • 제8권2호
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    • pp.860-885
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    • 2005
  • This study relates to develop a quantitative method through which promising technology-based business items can be discovered and selected. For this study, we utilized patent trend analysis, technology-industry concordance analysis, and keyword co-occurrence analysis of US patents. By analyzing patent trends and technology-industry concordance, we were able to find out the emerging industry trends : prevalence of bio industry, service industry, and B2C business. From the direct and co-occurrence analysis of newly discovered patent keywords in the year, 2000, 28 promising business item candidates were extracted. Finally, the promising item candidates were prioritized using 4 business attractiveness determinants; market size, product life cycle, degree of the technological innovation, and coincidence with the industry trends. This result implicates that reliable discovery and selection of promising technology-based business items can be performed by a quantitative, objective and low- cost process using knowledge discovery method from patent database instead of peer review.

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동시 출현 기반 키워드 네트워크 기법을 이용한 이동식 사다리 추락 재해 위험 요인 연관 구조 모델링 (Correlational Structure Modelling for Fall Accident Risk Factors of Portable Ladders Using Co-occurrence Keyword Networks)

  • 황종문;신성우
    • 한국안전학회지
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    • 제36권3호
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    • pp.50-59
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    • 2021
  • The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

토픽모델링과 동시출현단어 분석을 이용한 기업가정신에 대한 연구동향 분석: 2002~2021 (Current Research Trends in Entrepreneurship Based on Topic Modeling and Keyword Co-occurrence Analysis: 2002~2021)

  • 장성희
    • 벤처창업연구
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    • 제17권3호
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    • pp.245-256
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    • 2022
  • 본 연구는 토픽모델링과 동시출현단어 분석을 이용하여 기업가정신에 대한 연구 동향을 제공하는 것이 목적이다. 이를 위해 Web of Science 데이터베이스에서 'entrepreneurship'을 기본검색어로 설정하고, 2002년부터 2021년까지 발표한 14,953편의 기업가정신 논문의 데이터를 확보하였다. 본 연구에서는 VOSviewer 프로그램을 이용하여 동시출현단어 분석을 하였고, R 프로그램을 이용하여 토픽모델링 분석을 하였다. 본 연구의 분석결과는 다음과 같다. 첫째, 동시출현단어 분석 결과, 기업가정신과 혁신 클러스터, 기업가정신 교육 클러스터, 사회적 기업가정신과 지속가능성 클러스터, 기업성과 클러스터, 그리고 지식 및 기술이전 클러스터 등 5개의 클러스터로 구분되었다. 둘째, 토픽모델링 분석 결과, 창업환경 및 경제발전, 국제 기업가정신, 다양한 기업가정신, 벤처기업과 자본조달, 정부정책 및 지원, 사회적 기업가정신, 경영관련 이슈, 지역도시계획 및 개발, 기업가정신 교육, 기업가의 혁신과 성과, 기업가정신 연구, 기업가의 창업의도 등 12개의 토픽으로 분석되었다. 마지막으로, 시기별 토픽변화 추이 분석결과, 벤처기업과 자본조달과 기업가의 창업의도에 대한 토픽은 상승토픽으로 나타났고, 국제 기업가정신은 하강토픽으로 나타났다. 본 연구의 결과는 기업가정신 연구에 대한 전반적인 연구동향을 파악할 뿐만 아니라, 기업가정신 연구에 대한 통찰력을 제공하는데 유용할 것으로 기대된다.

국내 통합의학 저널의 연구 동향에 대한 계량서지학적 분석 : Integrative Medicine Research를 중심으로 (A Bibliometric Analysis of Research Trends in Domestic Integrative Medicine Journals : Focused on Integrative Medicine Research)

  • 김대진;윤태형;이종록;최병희
    • 대한통합의학회지
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    • 제12권2호
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    • pp.197-210
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    • 2024
  • Purpose : This study aimed to analyze research trends in the field of integrative medicine through a bibliometric analysis of articles published in Integrative Medicine Research (IMR) journal from 2017 to 2022. Methods : Articles published in IMR journal between 2017 and 2022 were searched using the Web of Science database on August 22, 2023. The analysis was performed using the Bibliometrix and Biblioshiny tools in R (version 4.3.1) and VOSviewer (version 1.6.19). Results : The key findings were as follows: average citations per article (9.41), total authors (1,142), single-authored articles (12), average articles per author (0.27), average co-authors per article (5.27), and rate of international co-authorships (15.69 %). The most-cited article was on the cryopreservation of cells or tissues and their clinical applications. The top keyword analysis by author keywords showed that "acupuncture" was the most frequently used keyword (33 times). Co-occurrence network analysis showed 85 high-frequency keywords that appeared five or more times, and the top five keywords by total link strength were "acupuncture," "herbal medicine," "prevalence," "alternative medicine," and "complementary." The study found that, contrary to the trend in complementary and alternative medicine research in Korea, the IMR journal actively conducts intervention studies to provide clinical evidence. Conclusion : In the IMR journal, "acupuncture" was the most frequent of author keywords. The analysis of keyword trend topics over time showed that the keyword "systematic review" continued to appear from 2020 to 2022, and the keyword "clinical practice guideline" appeared for the first time in 2021. In particular, the co-occurrence network analysis highlighted keywords related to intervention research, in contrast to domestic research trends. While this study analyzed only one journal, future studies expanding the category of integrative medicine and increasing the number of journals analyzed may provide further insights.

Trends in Leopard Cat (Prionailurus bengalensis) Research through Co-word Analysis

  • Park, Heebok;Lim, Anya;Choi, Taeyoung;Han, Changwook;Park, Yungchul
    • Journal of Forest and Environmental Science
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    • 제34권1호
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    • pp.46-49
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    • 2018
  • This study aims to explore the knowledge structure of the leopard cat (Prionailurus bengalensis) research during the period of 1952-2017. Data was collected from Google Scholar and Research Information Service System (RISS), and a total of 482 author keywords from 125 papers from peer-reviewed scholarly journals were retrieved. Co-word analysis was applied to examine patterns and trends in the leopard cat research by measuring the association strengths of the author keywords along with the descriptive analysis of the keywords. The result shows that the most commonly used keywords in leopard cat research were Felidae, Iriomte cat, and camera trap except for its English and scientific name, and camera traps became a frequent keyword since 2005. Co-word analysis also reveals that leopard cat research has been actively conducted in Southeast Asia in conjugation with studying other carnivores using the camera traps. Through the understanding of the patterns and trends, the finding of this study could provide an opportunity for the exploration of neglected areas in the leopard cat research and conservation.