• Title/Summary/Keyword: Degree centrality

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A Study on the Library Marketing Research Trends through Keyword Network Analysis: Comparative Analysis of Korea and Other Countries (키워드 네트워크 분석을 통한 도서관마케팅 연구 경향 분석 - 우리나라와 국외연구의 비교분석 -)

  • Lee, Seongsin
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.3
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    • pp.383-402
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    • 2016
  • The purpose of this study is to study library marketing research trends in Korea and other countries through the analysis of author keyword network of peer-reviewed journal articles. The author keyword was collected from four major LIS journals in Korea and Scopus academic database for other countries'. The data was analyzed using NetMiner4 software. The results of the study were as follows: 1) In Korea, lots of library marketing studies focused on public libraries. However, there was a range of library marketing researches focused on academic libraries in other countries, 2) In Korea, there was not a variety of subjects of library marketing studies and the studies were mainly led by a few scholars, 3) In other countries, many scholars paid attention to digital library marketing through social media and/or web, and 4) there little library marketing studies focused on school libraries both in Korea and other countries.

Research Trends of Korean Journalism and Communication Studies Using a Semantic Network Analysis (언어 네트워크 분석을 통해 살펴본 한국 언론학 분야 연구의 연구동향 분석)

  • Lee, Sungjoon
    • The Journal of the Korea Contents Association
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    • v.16 no.7
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    • pp.179-189
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    • 2016
  • This aim of this study is identify research trends and intellectual structure in the field of Korean journalism and communication studies. For this purpose, a semantic network analysis was employed to analyze keywords in the abstracts of published articles in the Korean Journal of Journalism and Communication Studies from 2005 to 2015. The results showed that "frame", "Twitter", "content analysis" and "social media" are among the most frequently used keywords in the abstracts during this period. With regards to degree and eigenvector centrality, "social capital", "trust" and "twitter" were among the highest. The findings of the periodic characteristics of research trends revealed that there are more studies that employ the traditional media effect theories including Uses and Gratification Theory, Agenda Setting Theory, and Framing Theory before the year of 2010 while those that focus on the specific new media such as smartphones and twitter after 2011. This study has implications in the sense that it can be used as guidelines for making a curriculum or establishing the research system for Korean journalism and communication studies in the future.

Exploring Research Trends in Curriculum through Keyword Network Analysis (키워드 네트워크 분석을 통한 교육과정 연구 동향 탐색)

  • Jang, Bong Seok
    • Journal of Industrial Convergence
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    • v.18 no.2
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    • pp.45-50
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    • 2020
  • The purpose of this study is to analyze relationships among essential keywords in curriculum. The number of 1,935 keyword was collected from 644 manuscripts published between 2002 and 2019. For data analysis, this study selected softwares of KrKwic and KrTitle to compose a 1-mode network matrix and UCINET 6 and NetDraw to implement network analysis and visualization. Results are as follows. First, the frequency of keyword was curriculum, curriculum development, national curriculum, competency-based curriculum, 2015 revised national curriculum, curriculum implementation, understanding by design, competency, teacher education, school curriculum, and IBDP from highest to lowest. Second, degree centrality was curriculum development, curriculum, competency-based curriculum, national curriculum, 2015 revised national curriculum, understanding by design, competency, key competency, high school curriculum, textbook, curriculum implementation, teacher education, and IBDP from highest to lowest.

A Study on the Keyword Extraction for ESG Controversies Through Association Rule Mining (연관규칙 분석을 통한 ESG 우려사안 키워드 도출에 관한 연구)

  • Ahn, Tae Wook;Lee, Hee Seung;Yi, June Suh
    • The Journal of Information Systems
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    • v.30 no.1
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    • pp.123-149
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    • 2021
  • Purpose The purpose of this study is to define the anti-ESG activities of companies recognized by media by reflecting ESG recently attracted attention. This study extracts keywords for ESG controversies through association rule mining. Design/methodology/approach A research framework is designed to extract keywords for ESG controversies as follows: 1) From DeepSearch DB, we collect 23,837 articles on anti-ESG activities exposed to 130 media from 2013 to 2018 of 294 listed companies with ESG ratings 2) We set keywords related to environment, social, and governance, and delete or merge them with other keywords based on the support, confidence, and lift derived from association rule mining. 3) We illustrate the importance of keywords and the relevance between keywords through density, degree centrality, and closeness centrality on network analysis. Findings We identify a total of 26 keywords for ESG controversies. 'Gapjil' records the highest frequency, followed by 'corruption', 'bribery', and 'collusion'. Out of the 26 keywords, 16 are related to governance, 8 to social, and 2 to environment. The keywords ranked high are mostly related to the responsibility of shareholders within corporate governance. ESG controversies associated with social issues are often related to unfair trade. As a result of confidence analysis, the keywords related to social and governance are clustered and the probability of mutual occurrence between keywords is high within each group. In particular, in the case of "owner's arrest", it is caused by "bribery" and "misappropriation" with an 80% confidence level. The result of network analysis shows that 'corruption' is located in the center, which is the most likely to occur alone, and is highly related to 'breach of duty', 'embezzlement', and 'bribery'.

A Keyword Network Analysis on Research Trends in the Area of Health Insurance (건강보험 연구동향에 대한 키워드 네트워크 분석)

  • Lee, Su Jung;Lee, Sun-Hee
    • Health Policy and Management
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    • v.31 no.3
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    • pp.335-343
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    • 2021
  • Background: The purpose of this study was to extract the major areas of interest in health insurance research in Korea, and infer policy agendas related to health insurance by analyzing research keywords. Methods: For this study, 2,590 articles were selected from among 7,459 academic papers related to health insurance published between January 1987 and December 2018, which were looked up using the Research Information Sharing Service (RISS). Keyword extraction and keyword network analysis were performed using the KrKwic, KrTitle, and UCINET software. Results: First, the number of studies in the area of health insurance continued to increase in all government terms, and it was not until after the 2000s that the subjects of health insurance researches were diversified. Second, degree centrality showed that 'medical expenditure' and 'medical utilization' were consistently high-ranking keywords regardless of the government in power. Aging and long-term care insurance-related keywords were ranked higher in the Lee Myung-bak government, Park Geun-hye government, and Moon Jae-in government. Third, betweenness centrality showed the same high ranking in key topics such as medical expenditure and medical utilization, while the ranking of key keywords differed depending on the interests and characteristics of each government policy. Conclusion: We confirm that health insurance as a research topic has been the main theme in Korean health care research fields. Research keywords extracted from articles also corresponded to the main health policies promoted during each government period. Efforts to systematically investigate policy megatrends are needed to plan adaptive future policies.

A Text Network Analysis of North Korean Library Journal, 『Reference Materials for Librarian』 (북한 도서관잡지 『도서관일군 참고자료』의 텍스트 네트워크 분석)

  • Lee, Seongsin;Kim, Hyunsook;Baek, Sumin;Yoon, Subin;Choi, Jae-Hwang
    • Journal of Korean Library and Information Science Society
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    • v.53 no.3
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    • pp.169-191
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    • 2022
  • The purpose of this study is to attempt a text network analysis for two years of 『Reference Materials for Librarian』 (2016-2017) published by the Library Operation Methodology Research Institute in North Korea. A text network analysis can measure how important a particular word by grasping the connectivity and relationship between words beyond a simple word frequency analysis, and it is also possible to interpret specific social phenomena and derive implications. Frequency, degree centrality, the betweenness centrality, community analysis of the collected words were calculated using NetMiner. As a result, the terms 'users', 'information services', 'information needs', 'information technology', 'social learning', 'computers', 'databases', 'information acquisition', 'information retrieval' and 'librarian' were appeared as important ones in understanding North Korean libraries.

Analysis of International Research Trends in Metaverse: Focusing on the Publications in Web of Science Indexed Journals

  • Jang, Phil-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.10
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    • pp.155-162
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    • 2022
  • In this paper, we examined the research trends and characteristics related to the metaverse in global journals published between 2000 and 2022 from the Web of Science database. The analysis included descriptive statistics, multidimensional scaling, keyword network analysis, and visualization. In addition, semantic network models were constructed, and centrality (betweenness and degree) analysis was performed using R and KH coder in two separate categories based on the trends and aspects of the publication: analysis period 1 (Jan 2000 to Dec 2020) and period 2 (Jan 2021 to Jun 2022). The results showed that the recent global research trends related to the metaverse could be quantitatively characterized using the semantic network analysis. Also, the results could be applied to suggest future research topics in the field of metaverse based on quantitative and empirical data.

A Study on the Network Text Analysis about Oral Health in Aging-Well

  • Seol-Hee Kim
    • Journal of dental hygiene science
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    • v.23 no.4
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    • pp.302-311
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    • 2023
  • Background: Oral health is an important element of well aging. And oral health also affects overall health, mental health, and quality of life. In this study, we sought to identify oral health influencing factors and research trends for well-aging through text analysis of research on well-aging and oral health over the past 12 years. Methods: The research data was analyzed based on English literature published in PubMed from 2012 to 2023. Aging well and oral health were used as search terms, and 115 final papers were selected. Network text analysis included keyword frequency analysis, centrality analysis, and cohesion structure analysis using the Net-Miner 4.0 program. Results: Excluding general characteristics, the most frequent keywords in 115 articles, 520 keywords (Mesh terms) were psychology, dental prosthesis and Alzheimer's disease, Dental caries, cognition, cognitive dysfunction, and bacteria. Research keywords with high degree centrality were Dental caries (0.864), Quality of life (0.833), Tooth loss (0.818), Health status (0.727), and Life expectancy (0.712). As a result of community analysis, it consisted of 4 groups. Group 1 consisted of chewing and nutrition, Group 2 consisted oral diseases, systemic diseases and management, Group 3 consisted oral health and mental health, Group 4 consisted oral frailty symptoms and quality of life. Conclusion: In an aging society, oral dysfunction affects mental health and quality of life. Preventing oral diseases for well-aging can have a positive impact on mental health and quality of life. Therefore, efforts are needed to prevent oral frailty in a super-aging society by developing and educating systematic oral care programs for each life cycle.

An Analysis of Domestic Research Trend on Research Data Using Keyword Network Analysis (키워드 네트워크 분석을 이용한 연구데이터 관련 국내 연구 동향 분석)

  • Sangwoo Han
    • Journal of Korean Library and Information Science Society
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    • v.54 no.4
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    • pp.393-414
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    • 2023
  • The goal of this study is to investigate domestic research trend on research data study. To achieve this goal, articles related research data topic were collected from RISS. After data cleansing, 134 author keywords were extracted from a total of 58 articles and keyword network analysis was performed. As a result, first, the number of studies related to research data in Korea is still only 58, so it was found that many related studies need to be conducted in the future. Second, most research fields related to research data were focused on library and information science among complex studies. Third, as a result of frequency analysis of author keywords related to research data, 'research data management', 'research data sharing', 'data repository', and 'open science' were analyzed as major frequent keywords, so research data-related research focuses on the above keywords. The keyword network analysis results also showed that high-frequency keywords occupy a central position in degree centrality and betweenness centrality and are located as core keywords in related studies. Through the results of this study, we were able to identify trends related to recent research data and identify areas that require intensive research in the future.

A co-authorship network analysis on mathematics education scholars (수학교육 연구자의 공동출판 연결망)

  • Kim, Sungyeun
    • The Mathematical Education
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    • v.52 no.4
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    • pp.483-496
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    • 2013
  • In this study, we investigated the structure of the mathematics education scholars' co-authorship relationship in papers registered at the National Research Foundation of Korea by social network analysis. The data were 354 scholars from 257 papers in 4 journals from 2009 to 2013 based on 'the 2009 revised Korean National Curriculum'. For the analysis, Pajek3 and UCINET6.3 were used. The results of this study were as follows: First, each of the mathematics education scholars is connected on average with about 5 paths of intermediate collaborators. Second, Analyses of the first component group found distinguishable scholar groups' characteristics depending on their affiliations, majors, and job statuses. Third, there were scholars having high values in network degree centrality measures despite not having high numbers in published papers. On the contrary, there sere scholars having high numbers in published papers despite not having high values in network analysis. Finally, I suggested the directions for the future research with the limitations of this study.