• 제목/요약/키워드: Keywords Analysis

검색결과 1,474건 처리시간 0.026초

네트워크분석을 통한 직업건강간호학회지 논문의 지식구조 분석 (Knowledge Structure of the Korean Journal of Occupational Health Nursing through Network Analysis)

  • 권선영;박은정
    • 한국직업건강간호학회지
    • /
    • 제24권2호
    • /
    • pp.76-85
    • /
    • 2015
  • Purpose: The purpose of this study was to identify knowledge structure of the Korean Journal of Occupational Health Nursing from 1991 to 2014. Methods: 400 articles between 1991 and 2014 were collected. 1,369 keywords as noun phrases were extracted from articles and standardized for analysis. Co-occurrence matrix was generated via a cosine similarity measure, then the network was analyzed and visualized using PFNet. Also NodeXL was applied to visualize intellectual interchanges among keywords. Results: According to the results of the content analysis and the cluster analysis of author keywords from the Korean Journal of Occupational Health Nursing articles, 7 most important research topics of the journal were 'Workers & Work-related Health Problem', 'Recognition & Preventive Health Behaviors', 'Health Promotion & Quality of Life', 'Occupational Health Nursing & Management', 'Clinical Nursing Environment', 'Caregivers and Social Support', and 'Job Satisfaction, Stress & Performance'. Newly emerging topics for 4-year period units were observed as research trends. Conclusion: Through this study, the knowledge structure of the Korean Journal of Occupational Health Nursing was identified. The network analysis of this study will be useful for identifying the knowledge structure as well as finding general view and current research trends. Furthermore, The results of this study could be utilized to seek the research direction in the Korean Journal of Occupational Health Nursing.

언어 네트워크 분석을 통한 화장행동 연구동향 분석 (Language network analysis of make-up behavior research)

  • 백경진
    • 복식문화연구
    • /
    • 제27권3호
    • /
    • pp.274-284
    • /
    • 2019
  • Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers' interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

키워드 네트워크 분석을 통한 리터러시 교육 연구 동향 (A Study on Research Trends in Literacy Education through a Key word Network Analysis)

  • 이우진;백혜진
    • 디지털융복합연구
    • /
    • 제20권5호
    • /
    • pp.53-59
    • /
    • 2022
  • 본 연구는 리터러시의 국내 연구동향 분석을 통해 학습과의 관련 변인을 살펴보고, 리터러시 교육방향에 시사점을 제시하고자 한다. 한국연구정보서비스(RISS)를 활용하여 1993년부터 2022년 2월까지의 연구논문을 수집하였다. 검색 키워드로 '리터러시'와 '교육'을 사용하였으며, 200편의 논문이 분석대상으로 선정되었다. 키워드 네트워크 분석을 활용하여 관련 변인을 분석한 결과, 총 810개의 키워드 중 최소 3회 이상 출현한 키워드는 118개였으며, 가장 높은 빈도를 보인 키워드는 '디지털 리터러시', '미디어 리터러시', '초등학교' 순으로 나타났다. 분석 결과를 통해 다음의 시사점을 제시했다. 첫째, 온라인 교수·학습 자원 플랫폼 구축과 교육정책 연계와의 확대성 연구가 요구된다. 둘째, 리터러시 역량 설정 및 역량 향상 방안이 모색되어야 한다. 셋째, 디지털 기반 융합 교육모델 개발이 이뤄져야 한다. 본 연구는 가장 최근까지의 리터러시 연구를 살펴보고, 이를 통해 리터러시 교육의 방향을 제시하였다는 점에서 의의가 있다고 하겠다.

키워드 네트워크 분석을 활용한 과학기술동향 분석 (Analysis of Trends in Science and Technology using Keyword Network Analysis)

  • 박주섭;김나랑;한은정
    • 한국산업정보학회논문지
    • /
    • 제23권2호
    • /
    • pp.63-73
    • /
    • 2018
  • 학계나 연구소에서는 연구동향이나 과학기술동향을 파악하고 예측하기 위해 전문가들의 판단에 의존하는 정성적인 방법을 주로 활용하여 왔다. 이 기법은 많은 시간과 비용이 드는 단점이 있기에 본 논문에서는 키워드 네트워크 분석을 활용하여 과학기술 동향을 예측하였다. 이를 위해 미국 특허 중 AI(Artificial Intelligence) 특허 초록 13,618개를 대상으로 키워드 네트워크 분석을 활용하여 분석 1기(2002.1.1. ~ 2006.12.31.), 분석 2기(2007.1.1. ~ 2011.12.31.), 분석 3기(2012.1.1. ~ 2016.12.31.)로 구분하여 분석하였다. 빈도 분석 결과, 분석 1기에서 3기로 시간이 경과할수록 AI 응용 분야의 방법에 관련된 핵심어들이 부각되었다. 키워드 네트워크 분석에서도 시간이 경과함에 따라 응용 분야의 방법에 관련된 핵심어와 다른 핵심어 간의 연계성이 높아졌다. 또한 분석 전체 기간 중 상승 및 하락 추세를 보인 연계 핵심어를 분석하면 응용 분야의 방법과 관리에 대한 연계성은 강화되는 반면에 기초 분야의 연계성은 약화되었다. 키워드 연결 중심성 분석에서도 기간이 경과할수록 응용 분야에 대한 중심성 수치가 높았다. 키워드 매개 중심성 분석에서 분석 3기는 응용 분야의 방법론 관련 핵심어가 가장 높은 매개 수치를 보였다. 이는 앞으로 응용 분야의 방법들이 AI 분야의 강력한 중개자 역할을 할 것으로 예상된다. 본 논문에서 제시한 기법은 지역혁신과 관련된 과제 발굴이나 사회문제 이슈의 시각화 등 지역혁신 분야에 활용되어 질 수 있을 것이다.

그래프 이론 및 네트워크 모델을 이용한 지식경영연구 논문 트랜드 분석 (A trend analysis of the Knowledge Management Research using graph theory and network model)

  • 이동현;이 호;김정민
    • 지식경영연구
    • /
    • 제17권1호
    • /
    • pp.1-16
    • /
    • 2016
  • 본 연구에서는 국내 지식경영 분야의 연구동향들이 어떻게 전개되어 왔는지 살펴보기 위해 한국지식경영학회의 지식경영연구 학술지에 2000년 부터 2015년까지 게재된 총 352개의 논문의 1496개의 키워드를 대상으로 그래프 이론 및 네트워크 모델을 이용하여 추세를 분석하였다. 분석 결과를 통하여 최근 각광받고 키워드들, 네트워크의 중심에서 멀어진 키워드들, 그리고 키워드들 간의 단절고리에 대하여 알아보았다. 연구자들은 본 연구결과를 활용하여 향후 지식경영 분야 후속연구의 설계 및 주제선정을 위한 기초자료로 삼을 수 있을 것이다.

Contents Analysis and Synthesis Scheme for Music Album Cover Art

  • Moon, Dae-Jin;Rho, Seung-Min;Hwang, Een-Jun
    • 전기전자학회논문지
    • /
    • 제14권4호
    • /
    • pp.305-311
    • /
    • 2010
  • Most recent web search engines perform effective keyword-based multimedia contents retrieval by investigating keywords associated with multimedia contents on the Web and comparing them with query keywords. On the other hand, most music and compilation albums provide professional artwork as cover art that will be displayed when the music is played. If the cover art is not available, then the music player just displays some dummy or random images, but this has been a source of dissatisfaction. In this paper, in order to automatically create cover art that is matched with music contents, we propose a music album cover art creation scheme based on music contents analysis and result synthesis. We first (i) analyze music contents and their lyrics and extract representative keywords, (ii) expand the keywords using WordNet and generate various queries, (iii) retrieve related images from the Web using those queries, and finally (iv) synthesize them according to the user preference for album cover art. To show the effectiveness of our scheme, we developed a prototype system and reported some results.

Knowledge Evolution in Construction Automation Research

  • Mun, Seong-Hwan;Kim, Taehoon;Lee, Ung-Kyun;Cho, Kyuman;Lim, Hyunsu
    • 한국건축시공학회지
    • /
    • 제20권6호
    • /
    • pp.577-584
    • /
    • 2020
  • Construction automation and robotics have been widely adopted in the construction industry as a promising solution to such issues like a shortage of skilled labor and the difficulties workers face in harsh working environments. The analysis of the knowledge structure and its evolution from the existing articles helps identify essential knowledge elements and possible future research directions. This study attempts to (1) construct keyword networks from the papers published in the International Symposium on Automation and Robotics in Construction (ISARC), (2) investigate how keywords and keyword communities are associated with each other, and (3) examine the changes in the crucial keywords over time. Through cluster analysis, 79 keywords were categorized into four groups (BIM, Building construction, Sensing, and GPS as representative keywords) with similar structural positions. Research trends show that research themes related to Infrastructure, Construction equipment, and 3D have consistently received a large amount of attention, regardless of geographical region. Research on as-built status model utilization through BIM and Laser scanning and improving Energy performance is taking place more frequently. In contrast, research studies related to problem-solving based on Neural networks are not as common as previously. This study provides useful insights into the construction automation field, at both the macro and micro levels.

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

  • YANG, Woo-Ryeong
    • 산경연구논집
    • /
    • 제10권8호
    • /
    • pp.17-24
    • /
    • 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.

Research trends in the Korean Journal of Women Health Nursing from 2011 to 2021: a quantitative content analysis

  • Ju-Hee Nho;Sookkyoung Park
    • 여성건강간호학회지
    • /
    • 제29권2호
    • /
    • pp.128-136
    • /
    • 2023
  • Purpose: Topic modeling is a text mining technique that extracts concepts from textual data and uncovers semantic structures and potential knowledge frameworks within context. This study aimed to identify major keywords and network structures for each major topic to discern research trends in women's health nursing published in the Korean Journal of Women Health Nursing (KJWHN) using text network analysis and topic modeling. Methods: The study targeted papers with English abstracts among 373 articles published in KJWHN from January 2011 to December 2021. Text network analysis and topic modeling were employed, and the analysis consisted of five steps: (1) data collection, (2) word extraction and refinement, (3) extraction of keywords and creation of networks, (4) network centrality analysis and key topic selection, and (5) topic modeling. Results: Six major keywords, each corresponding to a topic, were extracted through topic modeling analysis: "gynecologic neoplasms," "menopausal health," "health behavior," "infertility," "women's health in transition," and "nursing education for women." Conclusion: The latent topics from the target studies primarily focused on the health of women across all age groups. Research related to women's health is evolving with changing times and warrants further progress in the future. Future research on women's health nursing should explore various topics that reflect changes in social trends, and research methods should be diversified accordingly.

키워드 네트워크 분석을 통한 『한국초등수학교육학회지』 연구의 동향 분석 (A Study on the Research Trends of 『Journal of Elementary Mathematics Education in Korea』 through a Keyword Network Analysis)

  • 문소영;조진석
    • 한국초등수학교육학회지
    • /
    • 제23권4호
    • /
    • pp.459-479
    • /
    • 2019
  • 본 연구에서는 키워드 네트워크를 통해 국내 초등수학교육 분야의 대표적인 학술지인 『한국초등수학교육학회지』에 수록된 논문의 키워드를 대상으로 본 학술지의 연구 동향을 살펴보았다. 자료수집은 창간호부터 2018년까지 총 378편의 논문을 대상으로 하였으며, 논문에 포함된 총 1140개의 키워드들에 대하여 Krkwic 프로그램과 NodeXL 프로그램을 활용하여 빈도 분석 및 키워드 네트워크 분석을 실시하였다. 연구 결과 첫째, 빈도분석 결과 최소 5회 이상 출현하여 나타난 키워드는 48개로 수학과교육과정, 수학교과서, 학교수학, 수학문제해결, 수학영재 등이 있었다. 둘째, 키워드 네트워크 분석 결과에서 중요성이 높게 나타난 키워드는 수학교과서, 학교수학, 수학과교육과정, 수학문제해결, 수학적의사소통 등이 나타났다. 이러한 연구 결과를 바탕으로 본 학술지의 연구의 주요한 연구 주제어를 파악하고 연구 동향을 논의하였으며 연구의 제한점을 바탕으로 제언을 할 수 있었다.

  • PDF