• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.85-97
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• 2021

In this paper, in order to support rapid and effective decision-making and response in disaster situations, we identified the author's organization of academic research papers and conducted a collaborative relationship analysis study based on this. For this purpose, 2,308 papers in 69 Korean academic journals classified by disaster and safety type were selected for analysis and experimental data were constructed based on the Korea Science Citation Database (KSCD) and institutional identification data provided by KISTI. Collaborative relationship analysis was conducted for each of the four units (Institution, Institution type, Institution region and University department type). First, statistical status such as frequency of appearance was compared, and basic properties and main centrality index of each co-occurrence network were calculated and analyzed using Social Network Analysis Method. In addition, a visualization map was created and presented for each network so that the collaborative relationship could be viewed and understood as a whole. The results of this study are expected to contribute to the search activities of institutions and cooperative groups that support effective disaster response and to lay the foundation for the information service system.

• 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.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.121-148
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• 2023

The purpose of this study is to propose a scholarly paper recommendation system based on metadata attribute similarity with excellent performance. This study suggests a scholarly paper recommendation method that combines techniques from two sub-fields of Library and Information Science, namely metadata use in Information Organization and co-citation analysis, author bibliographic coupling, co-occurrence frequency, and cosine similarity in Bibliometrics. To conduct experiments, a total of 9,643 paper metadata related to "inequality" and "divide" were collected and refined to derive relative coordinate values between author, keyword, and title attributes using cosine similarity. The study then conducted experiments to select weight conditions and dimension numbers that resulted in a good performance. The results were presented and evaluated by users, and based on this, the study conducted discussions centered on the research questions through reference node and recommendation combination characteristic analysis, conjoint analysis, and results from comparative analysis. Overall, the study showed that the performance was excellent when author-related attributes were used alone or in combination with title-related attributes. If the technique proposed in this study is utilized and a wide range of samples are secured, it could help improve the performance of recommendation techniques not only in the field of literature recommendation in information services but also in various other fields in society.

• 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.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.63-83
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• 2016

As the usage of information resources produced in various media and forms has been increased, the importance of metadata as a tool of information organization to describe the information resources becomes increasingly crucial. The purposes of this study are to analyze and to demonstrate the intellectual structure in the field of metadata through co-word analysis. The data set was collected from the journals which were registered in the Core collection of Web of Science citation database during the period from January 1, 1998 to July 8, 2016. Among them, the bibliographic data from 727 journals was collected using Topic category search with the query word 'metadata'. From 727 journal articles, 410 journals with author keywords were selected and after data preprocessing, 1,137 author keywords were extracted. Finally, a total of 37 final keywords which had more than 6 frequency were selected for analysis. In order to demonstrate the intellectual structure of metadata field, network analysis was conducted. As a result, 2 domains and 9 clusters were derived, and intellectual relations among keywords from metadata field were visualized, and proposed keywords with high global centrality and local centrality. Six clusters from cluster analysis were shown in the map of multidimensional scaling, and the knowledge structure was proposed based on the correlations among each keywords. The results of this study are expected to help to understand the intellectual structure of metadata field through visualization and to guide directions in new approaches of metadata related studies.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.309-330
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• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.89-114
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• 2018

Research on changes in research trends in academic disciplines is a method that enables observation of not only the detailed research subject and structure of the field but also the state of change in the flow of time. Therefore, in this study, in order to observe the changes of research trend in library and information science field in Korea, co-word analysis was conducted with Korean author keywords from three types of journals which were listed in the Korea Citation Index(KCI) and have top citation impact factor were selected. For the time series analysis, the 15-year research period was accumulated in 5-years units, and divided into 2003~2007, 2003~2012, and 2003~2017. The keywords which limited to the frequency of appearance 10 or more, respectively, were analyzed and visualized. As a result of the analysis, during the period from 2003 to 2007, the intellectual structure composed with 25 keywords and 8 areas was confirmed, and during the period from 2003 to 2012, the structure composed by 3 areas 17 sub-areas with 76 keywords was confirmed. Also, the intellectual structure during the period from 2003 to 2017 was crowded into 6 areas 32 consisting of a total of 132 keywords. As a result of comprehensive period analysis, in the field of library and information science in Korea, over the past 15 years, new keywords have been added for each period, and detailed topics have also been subdivided and gradually segmented and expanded.

• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.23-50
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• 2022

Source memory is a cognitive process that combines the representation of the origin of the episodic experience with an item. By studying this daily process, researchers have made fundamental discoveries that make up the foundation of brain and behavior research, such as executive function and binding. In this paper, we review and conduct a bibliometric analysis on source memory papers published from 1989 to 2020. This review is based on keyword co-occurrence networks and author citation networks, providing an in-depth overview of the development of source memory research and future directions. This bibliometric analysis discovers a change in the research trends: while research prior to 2010 focused on individuality of source memory as a cognitive function, more recent papers focus more on the implication of source memory as it pertains to connectivity between disparate brain regions and to social neuroscience. Keyword network analysis shows that aging and executive function are continued topics of interest, although frameworks in which they are viewed have shifted to include developmental psychology and meta memory. The use of theories and models provided by source memory research seem essential for the future development of cognitive enhancement tools within and outside of the field of Psychology.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.323-341
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• 2021

Various research are being published in the areas of humanities, history, aviation/ports, and regional development, centering on the Incheon area which has issues such as large-scale ports and airports, archipelago, and urban regeneration. This study explored the scope of the subject and the distribution of researchers using a informetric analysis focusing on the studies of Incheon. Specifically, this study extracted authors from about 500 Incheon-related research papers listed in the Korean journal's citation index and analyzed the co-author relationship network to understand the cooperative behavior between authors' institutions. In addition, by extracting keywords from the articles and performing a weighted network (PFNET) analysis on the relationship between keywords, the intellectual structure was analyzed. As a result, it was found that Inha University and Incheon National University showed a high TBC, and Incheon Development Institute showed the high NNC. Meanwhile, the intellectual structure of Incheon-related research was found to be composed of 11 thematic clusters, and the social issues of Incheon, ports, and aviation were analyzed as representative clusters.

• Restorative Dentistry and Endodontics
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• v.48 no.4
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• pp.41.1-41.17
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• 2023

Objectives: This scientometric and bibliometric analysis explored scientific publications related to hydraulic calcium silicate-based (HCSB) sealers used in endodontology, aiming to describe basic bibliometric indicators and analyze current research trends. Materials and Methods: A comprehensive search was conducted in Web of Science and Scopus using specific HCSB sealer and general endodontic-related terms. Basic research parameters were collected, including publication year, authorship, countries, institutions, journals, level of evidence, study design and topic of interest, title terms, author keywords, citation counts, and density. Results: In total, 498 articles published in 136 journals were retrieved for the period 2008-2023. Brazil was the leading country, and the universities of Bologna in Italy and Sao Paolo in Brazil were represented equally as leading institutions. The most frequently occurring keywords were "calcium silicate," "root canal sealer MTA-Fillapex," and "biocompatibility," while title terms such as "calcium," "sealers," "root," "canal," "silicate based," and "endodontic" occurred most often. According to the thematic map analysis, "solubility" appeared as a basic theme of concentrated research interest, and "single-cone technique" was identified as an emerging, inadequately developed theme. The co-occurrence analysis revealed 4 major clusters centered on sealers' biological and physicochemical properties, obturation techniques, retreatability, and adhesion. Conclusions: This analysis presents bibliographic features and outlines changing trends in HCSB sealer research. The research output is dominated by basic science articles scrutinizing the biological and specific physicochemical properties of commonly used HCSB sealers. Future research needs to be guided by studies with a high level of evidence that utilize innovative, sophisticated technologies.