• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.97-122
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• 2023

Metaliteracy is a new framework that reframes information literacy. Metaliteracy is distinguished from information literacy through the intruduction of postmodernism, social constructivism and metacognition. However it has been not examined whether metaliteracy studies reflect the conceptual differences. Therefore, The purpose of the study is to observe research trends of metaliteracy on the difference from information literacy. In the study, literature reviews were conducted, and frequency analysis and knowledge network analysis(co-occurrence and bibliographic coupling) were conducted for 80 metaliteracy studies. The results of the study are as follows. As a result of co-occurrence analysis, metacognition(frequency 1st) and skills(degree centrality 1st, closeness centrality 1st, betweenness centrality 1st) appeared. Since metaliteracy criticizes skill-based information literacy, the result suggests that the concepts of information literacy and metaliteracy are mixed. On the other hand, as a result of bibliographic coupling analysis, studies with high bibliographic coupling explain the difference between information literacy and metaliteracy through metacognition.

• Journal of Korean Library and Information Science Society
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• v.44 no.3
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• pp.405-428
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• 2013

This study tried to explore the relation between research networks(coauthor network, author co-citation network, author bibliographic coupling network) and research performance of Records and Archives Management study in Korea. For the analysis, three basic types of network centrality and three indicators of research performance are used. The summary of this study is as follows: Firstly, there are relations between three centralities and three indicators of research performance in the coauthor network. Secondly, there are relations between betweenness centrality and research performance in the author co-citation/author bibliographic coupling networks. Thirdly, there are relations between three centralities in the each research network. Fourthly, there are not high relations between all centralities of the three research networks.

• Journal of Information Management
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• v.42 no.4
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• pp.75-94
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• 2011

The purpose of this study is to analyze the domain on the field of Electrical Engineering in Korea by the author bibliographic coupling analysis. The data set contains a total of 2,157 articles from two core journals with 23,411 citation data from 2005 to 2009 published in two prestigious journals. In order to achieve the purpose of this study, MDS analysis, clustering analysis and network analysis were used to examine core subject areas. In addition, the centrality analysis in the weighted networks was used to explore the key authors in this field such as the top global centrality authors and the top local centrality authors. The findings of this study can be utilized to guide the current research trend and author network for collection development and information services in the field of Electrical Engineering.

• Journal of the Korean Society for information Management
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• v.37 no.1
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• pp.153-177
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• 2020

In the context of open science, data sharing and reuse are becoming important researchers' activities. Among the discussions about data sharing and reuse, data journals and data papers shows visible results. Data journals are published in many academic fields, and the number of papers is increasing. Unlike the data itself, data papers contain activities that cite and receive citations, thus creating their own intellectual structures. This study analyzed 14 data journals indexed by Web of Science, 6,086 data papers and 84,908 cited references to examine the intellectual structure of data journals and data papers in academic community. Along with the author's details, the co-citation analysis and bibliographic coupling analysis were visualized in network to identify the detailed subject areas. The results of the analysis show that the frequent authors, affiliated institutions, and countries are different from that of traditional journal papers. These results can be interpreted as mainly because the authors who can easily produce data publish data papers. In both co-citation and bibliographic analysis, analytical tools, databases, and genome composition were the main subtopic areas. The co-citation analysis resulted in nine clusters, with specific subject areas being water quality and climate. The bibliographic analysis consisted of a total of 27 components, and detailed subject areas such as ocean and atmosphere were identified in addition to water quality and climate. Notably, the subject areas of the social sciences have also emerged.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.9
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• pp.718-726
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• 1998

J-E 특성 AC 임피더스 분석 그리고 주파수- 전도 특성들을 실험하여 임펄스 전류 서지가 ZnO 바리스터의 열화(degradation)에 미치는 영향을 고찰하였다. ZnO 바리스터 시편에 임펄스 전류(300A/$cm^24, 8/50$\mu s$)를 인가시킨 결과, 입계(grain boundary) 특성을 나타내는 비선형계수 $\alpha$와 E\ulcorner\ulcorner의 값은 크게 감소하였으나, 입자 특성을 나타내는 E_{100A}, E_{300A}$ 값에서는 큰 변화가 없었다. 이러한 열화 현상은 입계의 위치한 부성 전하 밀도, $N_s$의 감소에 한 쇼트키 장벽의 변화에 기인한 것으로 나타났다. 임펄스 서지에 의해 열화된 ZnO 바리스터는 AC 임피더스 분석에서 현저한 non-Debye 특성을 보이며, 이는 병렬 RC 네트워크로 모델링한 Cole-Cole 완화 관계식으로 입계의 열화 특성을 잘 설명할 수 있었다. 주파수-전도도 관계를 검토한 결과 Zno 바리스터는 호핑 전도(hopping conduction),\$sigma(\omega)\varpropto\omega^{\eta}$ 특성을 나타내면, 임펄스 서지가 인가된 이후 n 값이 감소하였다. 이는 임펄스 서지에 의해 입RP 결합 상태(defect states)가 호핑 전도가 발생하기 쉽고 다중(multiple)호핑에 의한 전도 메커니즘을 갖는 것으로 고찰되었다.

• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.177-195
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• 2017

This study attempts to infer research fronts using factor graph model based on heterogeneous features. The model suggested by this study infers research fronts having documents with the potential to be cited multiple times in the future. To this end, the documents are represented by bibliographic, network, and content features. Bibliographic features contain bibliographic information such as the number of authors, the number of institutions to which the authors belong, proceedings, the number of keywords the authors provide, funds, the number of references, the number of pages, and the journal impact factor. Network features include degree centrality, betweenness, and closeness among the document network. Content features include keywords from the title and abstract using keyphrase extraction techniques. The model learns these features of a publication and infers whether the document would be an RF using sum-product algorithm and junction tree algorithm on a factor graph. We experimentally demonstrate that when predicting RFs, the FG predicted more densely connected documents than those predicted by RFs constructed using a traditional bibliometric approach. Our results also indicate that FG-predicted documents exhibit stronger degrees of centrality and betweenness among RFs.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.133-154
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• 2016

Interdisciplinary approach has been recognized as one of key strategies to address various and complex research problems in modern science. The purpose of this study is to investigate the interdisciplinary characteristics and structure of the field of big data. Among the 1,083 journals related to the field of big data, multiple Subject Categories (SC) from the Web of Science were assigned to 420 journals (38.8%) and 239 journals (22.1%) were assigned with the SCs from different fields. These results show that the field of big data indicates the characteristics of interdisciplinarity. In addition, through bibliographic coupling network analysis of top 56 journals, 10 clusters in the network were recognized. Among the 10 clusters, 7 clusters were from computer science field focusing on technical aspects such as storing, processing and analyzing the data. The results of cluster analysis also identified multiple research works of analyzing and utilizing big data in various fields such as science & technology, engineering, communication, law, geography, bio-engineering and etc. Finally, with measuring three types of centrality (betweenness centrality, nearest centrality, triangle betweenness centrality) of journals, computer science journals appeared to have strong impact and subjective relations to other fields in the network.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.231-238
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• 2008

With the development of methodologies, there are also the researches for the concrete item selection for selecting the future emerging researches and technologies. In this paper, we use scientometrics for that purpose in the sectors of construction and transportation. In our scientometric analysis, we use Scopus database, top 1% cited papers, bibliographic coupling, cosine coefficient, and hierarchical clustering and then carry additional experts verification on our results. We try to show the detailed process of scientometric analysis and its possibility as objective methodologies to select the future emerging researches and technologies.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.18-29
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• 2022

The purpose of this exploratory study is to examine the intellectual structure of data science. For this purpose, this research examined a total of 17,997 bibliographies on data science indexed in Web of Science(WoS) of Clarivate Analytics from 2012 to 2021. This research applied methods such as descriptive analysis, citation analysis, co-author network analysis, co-occurrence network analysis, bibliographic coupling analysis, and co-citation analysis. This research contributes to finding the research directions of future data science topics.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.