• Title/Summary/Keyword: KCI(Korea Citation Index)

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KCI vs. WoS: Comparative Analysis of Korean and International Journal Publications in Library and Information Science

  • Yang, Kiduk;Lee, Hyekyung;Kim, Seonwook;Lee, Jongwook;Oh, Dong-Geun
    • Journal of Information Science Theory and Practice
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    • v.9 no.3
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    • pp.76-106
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    • 2021
  • The study analyzed bibliometric data of papers published in Korea Citation Index (KCI) and Web of Science (WoS) journals from 2002 to 2021. After examining size differences of KCI and WoS domains in the number of authors, institutions, and journals to put publication and citations counts in perspective, the study investigated co-authorship patterns over time to compare collaboration trends of Korean and international scholars and analyzed the data at author, institution, and journal levels to explore how the influences of authors, institutions, and journals on research output differ across domains. The study also conducted frequency-based analysis of keywords to identify key topics and visualized keyword clusters to examine topic trends. The result showed Korean LIS authors to be twice as productive as international authors but much less impactful and Korean institutions to be at comparable levels of productivity and impact in contrast to much of productivity and impact concentrated in top international institutions. Citations to journals exhibited initially increasing pattern followed by a decreasing trend though WoS journals showed far more variance than KCI journals. Co-authorship trends were much more pronounced among international publication, where larger collaboration groups suggested multi-disciplinary and complex nature of international LIS research. Keyword analysis found continuing diversification of topics in international research compared to relatively static topic trend in Korea. Keyword visualization showed WoS keyword clusters to be much denser and diverse than KCI clusters. In addition, key keyword clusters of WoS were quite different from each other unlike KCI clusters which were similar.

A Study on the Trend of papers published by Korean Association of Information Education (한국정보교육학회 게재 논문들의 추세적 변화에 대한 고찰)

  • Moon, Wae-shik
    • Journal of The Korean Association of Information Education
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    • v.22 no.6
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    • pp.681-687
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    • 2018
  • Many papers are published in KCI-listed journals for objectively validating research results and evaluations. This study collected articles published from 2008 to October, 2018 (10 years) of KAIE, which is a representative KCI registration institute which publishes various research related to elementary information education, and classified and analyzed by 10 subject areas. As a result, 34.2% of the papers published in the topic related to software education were found in the whole papers, and 33% of the papers published in this society showed the highest number of citations of papers relating to software education. Many of the remaining articles analyzed by subject area were overlapped with software education in the field of small scale medicine. In the future, a considerable number of researchers are expected to focus on software education.

Collaborative Research Network and Scientific Productivity: The Case of Korean Statisticians and Computer Scientists

  • Kwon, Ki-Seok;Kim, Jin-Guk
    • Asian Journal of Innovation and Policy
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    • v.6 no.1
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    • pp.85-93
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    • 2017
  • This paper focuses on the relationship between the characteristics of network and the productivity of scientists, which is rarely examined in previous studies. Utilizing a unique dataset from the Korean Citation Index (KCI), we examine the overall characteristics of the research network (e.g. distribution of nodes, density and mean distance), and analyze whether the network centrality is related to the scientific productivity. According to the results, firstly we have found that the collaborative research network of the Korean academics in the field of statistics and computer science is a scale-free network. Secondly, these research networks show a disciplinary difference. The network of statisticians is denser than that of computer scientists. In addition, computer scientists are located in a fragmented network compared to statisticians. Thirdly, with regard to the relationship between the researchers' network position and scientific productivity, a significant relation and their disciplinary difference have been observed. In particular, the degree centrality is the strongest predictor for the scientists' productivity. Based on these findings, some policy implications are put forward.

Review of Domestic Research Trends on Layered Double Hydroxide (LDH) Materials: Based on Research Articles in Korean Citation Index (KCI) (이중층수산화물(layered double hydroxide, LDH) 소재의 국내 연구동향 리뷰: 한국학술지인용색인(KCI)에 발표된 논문을 대상으로)

  • Seon Yong Lee;YoungJae Kim;Young Jae Lee
    • Economic and Environmental Geology
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    • v.56 no.1
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    • pp.23-53
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    • 2023
  • In this review paper, previous studies on layered double hydroxides (LDHs) published in the Korean Citation Index (KCI) were examined to investigate a research trend for LDHs in Korea. Since the first publication in 2002, 160 papers on LDHs have been published until January 2023. Among the 31 academic fields, top 5 fields appeared in the order of chemical engineering, chemistry, materials engineering, environmental engineering, and physics. The chemical engineering shows the highest record of published paper (71 papers) while around 10 papers have been published in the other four fields. All papers were reclassified into 15 research fields based on the industrial and academic purposes of using LDHs. The top 5 in these fields are in order of environmental purification materials, polymer catalyst materials, battery materials, pharmaceutical/medicinal materials, and basic physicochemical properties. These findings suggest that researches on the applications of LDH materials in the academic fields of chemical engineering and chemistry for the improvement of their functions such as environmental purification materials, polymer catalysts, and batteries have been being most actively conducted. The application of LDHs for cosmetic and agricultural purposes and for developing environmental sensors is still at the beginning of research. Considering a market-potential and high-efficiency-eco-friendly trend, however, it will deserve our attention as emerging application fields in the future. All reclassified papers were summarized in our tables and a supplementary file, including information on applied materials, key results, characteristics and synthesis methods of LDHs used. We expect that our findings of overall trends in LDH research in Korea can help design future researches with LDHs and suggest policies for resources and energies as well as environments efficiently.

Topic Modeling on Research Trends of Industry 4.0 Using Text Mining (텍스트 마이닝을 이용한 4차 산업 연구 동향 토픽 모델링)

  • Cho, Kyoung Won;Woo, Young Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.7
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    • pp.764-770
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    • 2019
  • In this research, text mining techniques were used to analyze the papers related to the "4th Industry". In order to analyze the papers, total of 685 papers were collected by searching with the keyword "4th industry" in Korea Journal Index(KCI) from 2016 to 2019. We used Python-based web scraping program to collect papers and use topic modeling techniques based on LDA algorithm implemented in R language for data analysis. As a result of perplexity analysis on the collected papers, nine topics were determined optimally and nine representative topics of the collected papers were extracted using the Gibbs sampling method. As a result, it was confirmed that artificial intelligence, big data, Internet of things(IoT), digital, network and so on have emerged as the major technologies, and it was confirmed that research has been conducted on the changes due to the major technologies in various fields related to the 4th industry such as industry, government, education field, and job.

Analysis of Research Trends in Home Economics Education by Language Network Analysis: Focused on the KCI Journals (2000-2019) (언어 네트워크 분석에 기반 한 가정과교육 연구 동향 분석: 2000-2019년 KCI 등재지를 중심으로)

  • Gham, Kyoung Won;Park, Mi Jeong
    • Journal of Korean Home Economics Education Association
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    • v.32 no.3
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    • pp.179-197
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    • 2020
  • This study analyzed the trends in home economics education research using the language network analysis method, focusing on papers published in the KCI list for 20 years from 2000 to 2019. A total of 501 home economics education papers analyzed through word cloud, centrality analysis, and topic modeling using NetMiner 4.4, and the results are as follows. First, the number of papers in home economics education published in the KCI listing increased gradually to 186 in the 2000s and 315 in the 2010s. The academic journals in which home economics education papers were published have been diversified to 16 in the 2000s and 22 in the 2010s. 60% of all papers were published in the 'Journal of Korean Home Economics Education Association', and since 2018, the number of papers published in the 'Journal of Learner-Centered Curriculum and Instruction' has increased dramatically. Second, in the 2000s and 2010s, home economics education studies published in KCI were categorized into home economics education content analysis, home economics educational program development & application, curriculum analysis, perception survey & direction exploration. In the 2000s, 'Home Economics Teacher' appeared as the main keyword, and a lot of perception survey & direction exploration were conducted. Relatively, the influence of 'development' increased in the 2010s, and many studies were conducted to analyze home economics education contents and develop and apply home economics programs. This study has significance in that it analyzed the research trend of HEE by expanding the analysis target and analysis period of the existing studies.

Research Trends of Studies Related to the Nature of Science in Korea Using Semantic Network Analysis (언어 네트워크 분석을 이용한 과학의 본성에 관한 국내연구 동향)

  • Lee, Sang-Gyun
    • Journal of the Korean Society of Earth Science Education
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    • v.9 no.1
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    • pp.65-87
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    • 2016
  • The purpose of this study is to examine Korean journals related to science education in order to analyze research trends into Nature of science in Korea. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, "Nature of science" in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to Word Cloud Analysis the frequency of key words, Centrality Analysis, co-occurrence and Cluster Dendrogram Analysis throughout a variety of research articles. The results show that 91 research papers were published in 25 journals from 1991 to 2015. Specifically, the 2 major journals published more than 50% of the total papers. In relation to research fields., In addition, key phrases, such as 'Analysis', 'recognition', 'lessons', 'science textbook', 'History of Science' and 'influence' are the most frequently used among the research studies. Finally, there are small language networks that appear concurrently as below: [Nature of science - high school student - recognize], [Explicit - lesson - effect], [elementary school - science textbook - analysis]. Research topic have been gradually diversified. However, many studies still put their focus on analysis and research aspects, and there have been little research on the Teaching and learning methods.

Research trends related to childhood and adolescent cancer survivors in South Korea using word co-occurrence network analysis

  • Kang, Kyung-Ah;Han, Suk Jung;Chun, Jiyoung;Kim, Hyun-Yong
    • Child Health Nursing Research
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    • v.27 no.3
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    • pp.201-210
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    • 2021
  • Purpose: This study analyzed research trends related to childhood and adolescent cancer survivors (CACS) using word co-occurrence network analysis on studies registered in the Korean Citation Index (KCI). Methods: This word co-occurrence network analysis study explored major research trends by constructing a network based on relationships between keywords (semantic morphemes) in the abstracts of published articles. Research articles published in the KCI over the past 10 years were collected using the Biblio Data Collector tool included in the NetMiner Program (version 4), using "cancer survivors", "adolescent", and "child" as the main search terms. After pre-processing, analyses were conducted on centrality (degree and eigenvector), cohesion (community), and topic modeling. Results: For centrality, the top 10 keywords included "treatment", "factor", "intervention", "group", "radiotherapy", "health", "risk", "measurement", "outcome", and "quality of life". In terms of cohesion and topic analysis, three categories were identified as the major research trends: "treatment and complications", "adaptation and support needs", and "management and quality of life". Conclusion: The keywords from the three main categories reflected interdisciplinary identification. Many studies on adaptation and support needs were identified in our analysis of nursing literature. Further research on managing and evaluating the quality of life among CACS must also be conducted.

Topic Modeling of Suicide Papers using Text Mining (텍스트마이닝을 활용한 자살 관련 논문 토픽 모델링)

  • Cho, Kyoung Won;Kim, Ha-young;Kim, Mi-ri;Woo, Young Woon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.275-277
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    • 2019
  • The purpose of this study is to classify the topics related to the suicide papers published so far and to identify the proporations of the main topics and the trends of the topics over the past 20 years. For this purpose, a text mining technique used in big data analysis was used as a data base of the Korean Journal of Citation Index (KCI), where information sharing about the papers is most active. This study, which grasps the trends of suicide related research according to the changes of the times, will become a basic data for establishing a strategy to adapt the academic direction related to suicide in the future.

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Analysis of sustainable fashion research trends using topic modeling (토픽 모델링을 이용한 지속가능패션 연구 동향 분석)

  • Lee, Hana
    • The Research Journal of the Costume Culture
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    • v.29 no.4
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    • pp.538-553
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    • 2021
  • As interest in the sustainable fashion industry continues to increase along with climate issues, it is necessary to identify research trends in sustainable fashion and seek new development directions. Therefore, this study aims to analyze research trends on sustainable fashion. For this purpose, related papers were collected from the KCI (Korean Citation Index) and Scopus, and 340 articles were used for the study. The collected data went through data transformation, data preprocessing, topic modeling analysis, core topic derivation, and visualization through a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: consumer clothing consumption behavior and environment, upcycle product development, product types by environmental approach, ESG business activities, materials and material development, process-based approach, lifestyle and consumer experience, and brand strategy. Topics were related to consumption, production, and education of sustainable fashion, respectively. KCI analysis results and Scopus analysis results derived eight topics but showed differences from the comprehensive analysis results. This study provides primary data for exploring various themes of sustainable fashion. It is significant in that the data were analyzed based on probability using a research method that excluded the subjective value of the researcher. It is recommended that follow-up studies be conducted to examine social trends.