• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.185-196
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• 2018

This study investigates the social network among authors to improve the quality of Panel researches. Korea Health Panel (KHP), implemented by the collaborative work between KIHASA (Korea Institute for Health and Social Affairs) and NHIC (National Health Insurance Service) since 2008, provides a critical infrastructure for policy making and management for insurance system and healthcare service. Using bibliographic data extracted from academic databases, eighty articles were extracted in domestic and international journals from 2008 to 2014, April. Data were analyzed by NetMiner 4.0, social network analysis software, to identify the extent to which authors are involved in healthcare use research and the patterns of collaboration between them. Analysis reveals that most authors publish a very small number of articles and collaborate within tightly knit circles. Centrality measures confirm these findings by revealing that only a small percentage of the authors are structurally dominant, and influence the flow of communication among others. It leads to the discovery of dependencies between the elements of the co-author network such as affiliates in health panel communities. Based on these findings, we recommend that Korea Health Panel could benefit from cultivating a wider base of influential authors and promoting broader collaborations.

• Journal of Information Science Theory and Practice
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• v.2 no.1
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• pp.35-47
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• 2014

Korean researchers' scientific outputs are increasing rapidly with the growth of both Korea's economy and industry size. This is the time to analyze the scientific output (STEM area) of Korea over the last 40 years. For this analysis, this study used the SCIE database of Web of Science (WoS), which is a representative global Citation Index Service. The objects of analysis are every Korean document published in the SCIE journal, and the research scopes are (1) analysis of citation and subject categories and (2) analysis of co-authorship. Through this study, characteristics such as cited trend and research trend by subject, and the status of collaboration between Korea and other countries including the 50 states of the USA were revealed.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.618-627
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• 2014

This paper aims to construct and analyze the domestic collaborative research network in industrial engineering. Using co-authorship information contained in the papers published in the two journals of the Korean Institute of Industrial Engineers, the collaborate research network at the institutional level is constructed. The core institutions in the network are identified by means of the centrality indexes of social network analysis. In addition, the five types of roles of the institutions in industry-university-institute cooperation are examined through brokerage analysis: coordinator, consultant, gatekeeper, representative, and liaisons. The findings are expected to be fruitfully utilized in formulation of R&D strategy of relevant organizations and technology policy making for promoting collaborative research in industrial engineering.

• Journal of Information Science Theory and Practice
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• v.6 no.3
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• pp.45-60
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• 2018

Research performance evaluation in Korean universities follows strict guidelines that specify scoring systems for publication venue categories and formulas for co-authorship credit allocation. To find out how the standards differ across universities and how they differ from bibliometric research evaluation measures, this study analyzed 25 standards from major Korean universities and rankings produced by applying standards and bibliometric measures such as publication and citation counts, normalized impact score, and h-index to the publication data of 195 tenure-track professors of library and information science departments in 35 Korean universities. The study also introduced a novel impact score normalization method to refine the methodology from prior studies. The results showed the university standards to be mostly similar to one another but quite different from citation-driven measures, which suggests the standards are not quite successful in quantifying the quality of research as originally intended.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.19-37
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• 2014

In an attempt to develop comprehensive evidence-based methods for evaluation of the R&D performance of cross-disciplinary projects, a joint bibliometric analysis of patents and publications was performed for two industry-university-government collaborative projects aimed at commercialization: Hokkaido University Research & Business Park Project (2003-2007; 63 inventors; 176 patents; 853 papers), and Matching Program for Innovations in Future Drug Discovery and Medical Care - phase I (2006-2010; 46 inventors; 235 patents; 733 papers). Besides the simple output indicators (for five years period), and citations (from the publication date to the end of 2012), science maps based on the network analysis of words and co-authorship relations were generated to identify the prominent research themes and teams. Our joint analysis of publications and patents yields objective and mutually complementing information, which provides better insights on research and commercialization performance of the large-scale projects. Hence, such analysis has potential for use in the industry-university project's performance evaluation.

• Herbal Formula Science
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• v.18 no.1
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• pp.57-77
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• 2010

Objective : This study reviews the recent trend of oriental medical prescription research. The data examined are the articles published in the Korean Journal of Oriental Medical Prescription from 1990 to 2009. Method : The data are retrieved through the internet database Oriental Medicine Advanced Searching Integrated System (OASIS) and the collection of the Korean Journal of Oriental Medical Prescription. The number of articles examined is 385, published in 25 volumes of the journal. This study examines the nature of the articles, research methods, subjects, and author information. Research subjects are sorted out by the OASIS key words for the articles published before 1999, and by key word indexes cited in the abstracts for the articles published sinceafter. Results : Among the 385 articles collected, 206 are research articles, 143 philological articles, 35 case studies, and 1 special contribution. A majority of research articles are experimental studies (199 articles or 96.6%), while clinical reports (5 articles or 2.43%), and others studies (2 articles) occupy a small portion. Most of experimental studies (183 articles or 91%) examine the effectiveness of certain prescriptions or treatments. Among the effectiveness studies, 114 articles (62.3%) employ in vivo experiment design, 52 articles (28.42%) in vitro experiments, and 17 articles (9.29%) both in vivo and in vitro experiments. In terms of research subject, the most frequently indexed key words are hepatotoxicity among diseases (9 articles), Bojungikgitang (Bu-Zhong-Yi-Qi-Tang) among prescriptions (10 articles), Buja (Acontii Tuber) among meteria medica (4 articles), immunity and anti-oxidation among efficacy terminology (6 articles each), and Donguibogam(東醫寶鑑) among references in the key words (25 articles). Universities are the main affiliation of authors (76.42%), followed by university hospitals (6.71%), non-academic research institutes (5.55%), local clinics (4.67), academic research institutes (2.81%), hospitals (2.38%), and others (1.44%). The most affiliated institute of the first and correspondent authors is Wonkwang University. In terms of authorship, co-authorship outnumbers sole-authorship by 82.08% to 17.92%. The proportion of authors of a single article is 63.54% which is near the author productivity distribution described by Lotka's law.

• Journal of the Korean Society for information Management
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• v.36 no.1
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• pp.117-135
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• 2019

Data journals and data papers have grown and considered an important scholarly practice in the paradigm of open science in the context of data sharing and data reuse. This study investigates a total of 713 data papers published in Scientific Data in terms of author, citation, and subject areas. The findings of the study show that the subject areas of core authors are found as the areas of Biotechnology and Physics. An average number of co-authors is 12 and the patterns of co-authorship are recognized as several closed sub-networks. In terms of citation status, the subject areas of cited publications are highly similar to the areas of data paper authors. However, the citation analysis indicates that there are considerable citations on the journals specialized on methodology. The network with authors' keywords identifies more detailed areas such as marine ecology, cancer, genome, database, and temperature. This result indicates that biology oriented-subjects are primary areas in the journal although Scientific Data is categorized in multidisciplinary science in Web of Science database.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.5
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• pp.169-176
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• 2018

The purpose of this study is to analyze the relationship between the centrality and the research performance by conducting the social network analysis for the social science journal in the last 10 years. As a result of the relationship analysis, the correlation between centrality and research productivity was highly correlated in most groups, but the impact factor and frequency of citations were not significant. In relation with the comprehensive research such as a H-index, middle productive group correlation was more significant than the upper productive group.

• Journal of Korean Neurosurgical Society
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• v.67 no.1
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• pp.50-59
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• 2024

Objective : This study aimed to conduct a bibliometric analysis on pelvic parameter related research over the last 30 years, analyzing trends, hotspots, and influential works within this field. Methods : A comprehensive Web of Science database search was performed. The search yielded 3249 results, focusing on articles and reviews published from 1992 to 2022 in English. Data was analyzed using CiteSpace and VOSviewer for keyword, authorship, and citation burst analysis, co-citation analysis, and clustering. Results : The number of publications and citations related to pelvic parameters has increased exponentially over the last 30 years. The USA leads in publication count with 1003 articles. Top publishing journals include the European Spine Journal, Spine, and Journal of Neurosurgery: Spine, with significant contributions by Schwab, Lafage V, and Protoptaltis. The most influential articles were identified using centrality and sigma values, indicating their role as key articles within the field. Research hotspots included spinal deformity, total hip arthroplasty, and sagittal alignment. Conclusion : Interest in pelvic parameter related research has grown significantly over the last three decades, indicating its relevance in modern orthopedics. The most influential works within this field have contributed to our understanding of spinal deformity, pelvic incidence, and their relation to total hip arthroplasty. This study provides a comprehensive overview of the trends and influential research in the field of pelvic parameters.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.