• Title/Summary/Keyword: 키워드 동시 출현 네트워크

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Research Trends Analysis on the Mediterranean Area Studies using Co-appearance Keywords (동시 출현 키워드를 활용한 지중해지역 연구 동향 분석)

  • Lee, Dong-Yul;Kang, Ji-Hoon;Moon, Sang-Ho
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.6 no.5
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    • pp.409-419
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    • 2016
  • In general, Area studies have very flexible field of research, so it is very difficult to proceed all field of research at the same time. Due to this, researches on Area studies have been changed the field of research and research trends according to age. So it is important to identify research trends for performing Area studies. Also, interests for understanding the research trend of Area studies are increasing constantly. In this paper, we analyze research trends of Mediterranean Area studies in Korea by using co-appearance keywords. To do this, we first analyze article types and extract co-appearance keywords on articles of 『Journal of Mediterranean Area Studies』, which is the representative journal of Mediterranean region in Korea. In details, trends analysis of Mediterranean Area studies would be performed by using cp-keywords of article and visualizing network graph forms.

Exploring the Research Topic Networks in the Technology Management Field Using Association Rule-based Co-word Analysis (연관규칙 기반 동시출현단어 분석을 활용한 기술경영 연구 주제 네트워크 분석)

  • Jeon, Ikjin;Lee, Hakyeon
    • Journal of Technology Innovation
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    • v.24 no.4
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    • pp.101-126
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    • 2016
  • This paper identifies core research topics and their relationships by deriving the research topic networks in the technology management field using co-word analysis. Contrary to the conventional approach in which undirected networks are constructed based on normalized co-occurrence frequency, this study analyzes directed networks of keywords by employing the confidence index of association rule mining for pairs of keywords. Author keywords included in 2,456 articles published in nine international journals of technology management in 2011~2014 are extracted and categorized into three types: THEME, METHOD, and FIELD. One-mode networks for each type of keywords are constructed to identify core research keywords and their interrelationships with each type. We then derive the two-mode networks composed of different two types of keywords, THEME-METHOD and THEME-FIELD, to explore which methods or fields are frequently employed or studied for each theme. The findings of this study are expected to be fruitfully referred for researchers in the field of technology management to grasp research trends and set the future research directions.

A Content Analysis of Journal Articles Using the Language Network Analysis Methods (언어 네트워크 분석 방법을 활용한 학술논문의 내용분석)

  • Lee, Soo-Sang
    • Journal of the Korean Society for information Management
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    • v.31 no.4
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    • pp.49-68
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    • 2014
  • The purpose of this study is to perform content analysis of research articles using the language network analysis method in Korea and catch the basic point of the language network analysis method. Six analytical categories are used for content analysis: types of language text, methods of keyword selection, methods of forming co-occurrence relation, methods of constructing network, network analytic tools and indexes. From the results of content analysis, this study found out various features as follows. The major types of language text are research articles and interview texts. The keywords were selected from words which are extracted from text content. To form co-occurrence relation between keywords, there use the co-occurrence count. The constructed networks are multiple-type networks rather than single-type ones. The network analytic tools such as NetMiner, UCINET/NetDraw, NodeXL, Pajek are used. The major analytic indexes are including density, centralities, sub-networks, etc. These features can be used to form the basis of the language network analysis method.

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.

Examining the Intellectual Structure of Reading Studies with Co-Word Analysis Based on the Importance of Journals and Sequence of Keywords (학술지 중요도와 키워드 순서를 고려한 단어동시출현 분석을 이용한 독서분야의 지적구조 분석)

  • Zhang, Ling Ling;Hong, Hyun Jin
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.25 no.1
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    • pp.295-318
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    • 2014
  • The purpose of this study is to analyze the intellectual structure of reading studies by using Co-Word Analysis based on the mixed weight in which the level of academic journals and the position of keywords are calculated. To achieve it, 838 academic articles relating to reading studies from KCI during the period from 2003 to 2012 were retrieved and 56 keywords were extracted. The results of clustering analysis, MDS, network analysis are that the network based on the mixed weight has a better performance in above three methods and reading studies can be divided into 4 bigger divisions and 11 subdivisions. Finally, the result of document analysis shows reading studies changes its research tendency from theoretical studies to empirical studies.

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.

Research trends in the field of multicultural education Network analysis:Focusing on Time series analysis of Co-word (다문화교육 분야의 연구동향에 대한 네트워크 분석: 동시출현단어의 시계열 분석중심으로)

  • Bae, Kyungim
    • Journal of Convergence for Information Technology
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    • v.11 no.10
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    • pp.159-170
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    • 2021
  • The purpose of this study was to understand the knowledge structure through keyword network analysis for the purpose of identifying research trends in the research field of multicultural education. To this end, the research trends and intellectual structure of multicultural education were identified through network analysis of words that appeared more than 6 times in the keywords of the papers registered in the KCI (Korean Journal of Citation Index) from 2002 to 2020. Study changes were analyzed by analysis. As a result of the analysis, the first period (2002-2010) focused on multicultural society and multiculturalism, while the second period (2011-2015) additionally introduced multicultural families, globalization, and teacher education, and the third period (2016-2020), multicultural receptivity, multicultural sensitivity, and multicultural efficacy were newly revealed. The research trend of multicultural education in Korean society over the past 19 years has been confirmed that the research topic has changed from theoretical research to empirical research, and the content of multicultural education has also been specified and expanded by field and subject.

Domain Analysis on the Field of Open Access by Co-Word Analysis (동시출현단어 분석 기반 오픈 액세스 분야 지적구조에 관한 연구)

  • Seo, SunKyung;Chung, EunKyung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.24 no.1
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    • pp.207-228
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    • 2013
  • Due to the advance of scholarly communication, the field of open access has been studied over the last decade. The purpose of this study is to analyze and demonstrate the field of open access via co-word analysis. The data set was collected from Web of Science citation database during the period from January 1998 to July 2012 using the Topic category. A total of 479 journal articles were retrieved and 8,643 noun keywords were extracted from the titles and abstracts. In order to achieve the purpose of this study, network analysis, clustering analysis and multidimensional scaling mapping were used to examine the domain and the sub-domains of open access field. 18 clusters in the network analysis are recognized and 4 clusters are shown in the map of multidimensional scaling. In addition, the centrality analysis in the weighted networks was used to explore the significant keywords in this field. The results of this study are expected to demonstrate and guide the intellectual structure and new approaches of open access field.

Development of Detection of Adverse Drug Reactions based on Named Entity Recognition and Keyword Network Analysis (개체명 인식과 키워드 네트워크 분석을 활용한 약물 이상 반응 탐지 시스템 개발)

  • Chae-Yeon Lee;Hyon Hee Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.670-672
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    • 2023
  • 본 논문에서는 소셜 미디어 약물 리뷰 데이터로부터 약물 이상 반응을 탐지하는 모델인 FC-BERT 를 기반으로 소셜 네트워크 분석을 활용하여 웹 애플리케이션을 구현하였다. FC-BERT 모델을 거쳐 나온 개체명 인식 결과 중에 같은 의미를 가진 서로 다른 약물 이상 반응 표현들을 MedDRA 부작용 사전을 참고하여 하나의 MedDRA 용어로 표준화하여 매핑했다. 해당 결과에 소셜 네트워크 분석 기법을 적용하여 생성한 상위 15 개의 ADR 동시 출현 그래프를 상위 30 개의 워드 클라우드와 함께 시각화하여 보여주는 웹 애플리케이션을 개발했다. 동시 출현 그래프는 가장 많은 리뷰에서 동시에 나타나는 ADR 쌍을 보여준다. 본 논문에서 제안한 웹 애플리케이션은 사람마다 다르게 나타나는 다양한 약물 이상 반응을 사용자에게 좀 더 접근성이 좋게 제공할 수 있을 것으로 보인다.

An Analysis of Research Trends on Public Libraries in Korea Using Keyword Network Analysis (키워드 네트워크 분석을 활용한 국내 공공도서관 연구 동향 분석)

  • Rosa Chang
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.34 no.4
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    • pp.285-302
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    • 2023
  • Based on this study, the research trends were identified for the field of public libraries in Korea by utilizing the keyword network analysis. For 20 years from 2003 to 2022, a total of 752 papers related to the public libraries published in the four largest academic journals in the field of library and information science in Korea were analyzed. The research results are as follows. First, from 2003 to 2022, an annual average of 37.6 papers were published, demonstrating a pattern of repeated rise and fall. Second, the keywords of 'service' and 'culture' were identified as the most discussed keywords as they were found to be among the top five in terms of the frequency of occurrence, connection centrality, and the mediation centrality analysis results. Third, in terms of the results of analyzing the co-occurrence frequency of keyword pairs, attention was paid to the keyword pairs of education-program, service-user, service-children, and service-disability.