• Title/Summary/Keyword: 키워드네트워크 분석

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An Investigation on Digital Humanities Research Trend by Analyzing the Papers of Digital Humanities Conferences (디지털 인문학 연구 동향 분석 - Digital Humanities 학술대회 논문을 중심으로 -)

  • Chung, EunKyung
    • Journal of the Korean Society for Library and Information Science
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    • v.55 no.1
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    • pp.393-413
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    • 2021
  • Digital humanities, which creates new and innovative knowledge through the combination of digital information technology and humanities research problems, can be seen as a representative multidisciplinary field of study. To investigate the intellectual structure of the digital humanities field, a network analysis of authors and keywords co-word was performed on a total of 441 papers in the last two years (2019, 2020) at the Digital Humanities Conference. As the results of the author and keyword analysis show, we can find out the active activities of Europe, North America, and Japanese and Chinese authors in East Asia. Through the co-author network, 11 dis-connected sub-networks are identified, which can be seen as a result of closed co-authoring activities. Through keyword analysis, 16 sub-subject areas are identified, which are machine learning, pedagogy, metadata, topic modeling, stylometry, cultural heritage, network, digital archive, natural language processing, digital library, twitter, drama, big data, neural network, virtual reality, and ethics. This results imply that a diver variety of digital information technologies are playing a major role in the digital humanities. In addition, keywords with high frequency can be classified into humanities-based keywords, digital information technology-based keywords, and convergence keywords. The dynamics of the growth and development of digital humanities can represented in these combinations of keywords.

A Knowledge Map Based on a Keyword-Relation Network by Using a Research Paper Database in the Computer Engineering Field (컴퓨터공학 분야 학술 논문 데이터베이스를 이용한 키워드 연관 네트워크 기반 지식지도)

  • Jung, Bo-Seok;Kwon, Yung-Keun;Kwak, Seung-Jin
    • The KIPS Transactions:PartD
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    • v.18D no.6
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    • pp.501-508
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    • 2011
  • A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

기업가정신 교육 프로그램의 효과성 검증: 메타분석과 키워드 네트워크 분석을 중심으로

  • 강다영;이은진;이우진
    • 한국벤처창업학회:학술대회논문집
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    • 2023.11a
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    • pp.61-67
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    • 2023
  • 기업가정신의 중요성이 전 세계적으로 확산하며, 국내에서도 기업가정신 함양을 위한 다양한 형태의 교육들이 '창업교육', '기업가정신 교육', '앙트러프러너십 교육' 등 저마다의 이름과 형태로 실시되고 있다. 기업가정신 교육이 확산됨에 따라 관련 연구 또한 활발히 진행되고 있으나, 개별적인 연구결과가 일관된 결론을 도출하고 있는지는 확인되지 않았다. 아직까지 관련 연구들을 종합하여 교육 성과에 대한 통일된 결과를 제시하는 연구는 미비한 수준이다. 이에 본 연구에서는 최근 10년 동안 국내 학술지에 게재된 다수의 논문을 대상으로 메타분석과 키워드 네트워크 분석을 실시하여 기업가정신 교육 프로그램의 성과를 체계적이고 종합적으로 제시하고 관련 연구 동향을 검토하고자 한다. 본 연구를 통해 국내 기업가정신 교육의 효과성에 대한 타당하고 통일된 결론이 제시되어 기업가정신 교육 프로그램의 개선과 발전을 위한 유의미한 시사점을 제공할 수 있기를 기대한다.

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

  • Lee, Dong Hyun;Lee, Ho;Kim, Jungmin
    • Knowledge Management Research
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    • v.17 no.1
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    • pp.1-16
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    • 2016
  • The purpose of this study is to analyze 352 scholarly journals and 1496 keywords in Knowledge Management Research from 2000 to 2015 and provide systematical view point of research trend in the area of knowledge management using graph theory and network model. The relational patterns among keywords as well as keywords which recently received noticeable attention and keywords which receded from the spotlight in recent years in the knowledge management literature were identified. The result of this study can be used as a foundation of future research ideas in knowledge management.

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

  • Lee, Woo-Jin;Baek, Hye-Jin
    • Journal of Digital Convergence
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    • v.20 no.5
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    • pp.53-59
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    • 2022
  • The purpose of this study is to examine the factors related to learning through analysis of domestic research trends in literacy and to present the direction of literacy education. Research papers from 1993 to February 2022 were collected using RISS. 'Literacy' and 'Education' were used as search keywords, and 200 papers were selected for analysis. As a result of analysis using keyword network analysis, 118 keywords appeared at least three times out of a total of 810 keywords. The order of the keywords with the highest frequency is 'digital literacy', 'media literacy', and 'elementary school'. The following direction was suggested through the analysis results. First, it is required to establish an online teaching and learning resource platform and link it with education policy. Second, it is necessary to set literacy competencies and seek ways to improve competencies. Third, a digital-based convergence education model should be developed. This study is meaningful in that it analyzed the most recent literacy studies and suggested the direction of literacy education.

A Bibliometric Analysis of the Major Korean Journals Indexed in 2020 Google Scholar Metrics (2020 구글 스칼라 매트릭스에 색인된 국내 주요 학술지에 대한 계량서지학적 분석)

  • Kim, Donghun;Kim, Kyuli;Zhu, Yongjun
    • Journal of the Korean Society for information Management
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    • v.38 no.1
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    • pp.53-69
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    • 2021
  • This study aims to understand the research landscape of South Korea using the data of 2020 Google Scholar Metrics. To achieve the goal, we constructed and analyzed four types of networks including the university collaboration network, the keyword co-occurrence network, the journal citation network, and the discipline citation network. Through the analysis of the university collaboration network, we found major universities such as Seoul National University, Keimyung University, and Sungkyunkwan University that have led collaborative research. Job related keywords such as job change intention and job satisfaction have been frequently studied with other keywords. Through the analysis of the journal citation network, we found multiple journals such as The Journal of the Korea Contents Association, Korean Journal of Sociology, and Korean Journal of Culture and Social Issues that have been widely cited by the other journals and influenced them. Finally, Education, Business administration, and Social welfare were identified as the top influential disciplines that have influenced other disciplines through the knowledge diffusion. The study is the first of its kind to use the data of Google Scholar Metrics and conduct a stepwise network analysis (e.g., keyword, journal, and discipline) to broadly understand the research landscape of South Korea. Our results can be used by government agencies and universities to develop effective strategies of promoting university collaboration and interdisciplinary research.

Research Trends on Defects of Apartment Building by Keyword Network Analysis (키워드 네트워크 분석을 이용한 공동주택 하자 연구 동향 분석)

  • Jang, Ho-myun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.9
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    • pp.403-410
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    • 2017
  • Apartment housing has rapidly increased since the housing supply policy implemented in the late 1980s. However, various defects have occurred because the policy focused only on quantity supply, while neglected quality control. In addition, disputes related to various defects are increasing. ; accordingly, studies defects of apartment houses have been continuously conducted to solve various problems. In this study, I analyzed the research trends regarding long-term accumulated defects of apartment buildings by keyword network analysis, and suggest implications. As ananalysis method, I collected journal articles using the portal of the Korea Educational and Scientific Information Agency and constructed data analysis by filtering collected academic papers and keyword refinement. Ialso performed visualization modeling for keyword network relationships, connection degree centrality analysis, and mediation centrality analysis. The results revealed that Mortgage, Dispute, Repair, Case, Response, Condensation, Cost, Institution, Standard, and Valuation are the main keywords that characterize apartment housing defects.

Bibliometric Network Analysis on Supply Chain Risk Management Research (공급사슬 리스크 관리 연구동향 분석: 네트워크 분석을 중심으로)

  • Pyun, Jebum;Rha, Jin Sung
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.6
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    • pp.125-138
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    • 2018
  • Recently, most firms have difficulties in predicting business context due to uncontrollable factors such as natural disasters, terrorism, social and political interests, as well as market factors such as rapid technological change, diversification of customer needs, and intensification of competition with competitors, thereby increasing the importance of risk management. The purpose of this study is to analyze trends of the risk management field concentrating on SCM, which is increasingly interested, and to identify key researches in this field and provide useful academic information. This study collected the information of the articles published in journals using the Scopus database, and analyzed both the network generated by keywords proposed in the articles and the network generated by the information for citations and co-authorship.

A Study on the Intellectual Structure of Domestic Open Access Area (국내 오픈액세스 분야의 지적구조 분석에 관한 연구)

  • Shin, Jueun;Kim, Seonghee
    • Journal of the Korean Society for Library and Information Science
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    • v.55 no.2
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    • pp.147-178
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    • 2021
  • In this study, co-word analysis was conducted to investigate the intellectual structure of the domestic open access area. Through KCI and RISS, 124 research articles related to open access in Korea were selected for analysis, and a total of 1,157 keywords were extracted from the title and abstract. Network analysis was performed on the selected keywords. As a result, 3 domains and 20 clusters were extracted, and intellectual relations among keywords from open access area were visualized through PFnet. The centrality analysis of weighted networks was used to identify the core keywords in this area. Finally, 5 clusters from cluster analysis were displayed on a multidimensional scaling map, and the intellectual structure was proposed based on the correlation between keywords. The results of this study can visually identify and can be used as basic data for predicting the future direction of open access research in Korea.

Network Analysis of the Intellectual Structure of Addiction Research in Social Sciences: Based on the KCI Articles Published in 2019 (사회과학 중독연구 분야의 지적구조에 관한 네트워크 분석 : 2019년도 KCI 등재 논문을 기반으로)

  • Lee, Serim;Chun, JongSerl
    • 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.