• Journal of the Korean Society for Library and Information Science
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• v.57 no.4
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• pp.311-331
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• 2023

This study attempted to explore the characteristics of knowledge communication and investigate important research topics and key authors by analyzing major academic papers in the field of LIS in Korea for five years from 2018 to 2022. The research method collected and analyzed papers published for five years in four key journals in the field of domestic Library and Information Science from the Korean Citation Index (KCI) database. The paper was selected to extract the author data of the paper and the data of the reference, and network visualization was performed by conducting literature co-citation analysis and author co-citation analysis using Netminer. As a result of the analysis, it was possible to derive a pair of co-citations between authors, and it was confirmed that it is important to include multiple authors in the intellectual structure analysis in the academic field through co-citation frequency analysis among researchers. The literature confirmed the correlation between the topics of the paper, and it was found that research related to Library and Information Science was centered on the topics of library, digital, user, service, and data.

• Journal of Information Management
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• v.24 no.1
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• pp.32-57
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• 1993

The purpose of this study is to analyze the intellectual structure of economics field in Korea by author co-citation analysis and to investigate the limitations of author co-citation analysis by a new method, namely, indexing term analysis of citing documents.

• Journal of the Korean Society for information Management
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• v.29 no.1
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• pp.115-134
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• 2012

The author co-citation analysis is generally based on the frequency of the first author because most citation databases include only the first author in the bibliographic information. In this sense, the purpose of this study is to provide a better knowledge structure by utilizing the multiple authorship of author co-citation analysis. To achieve the purpose of this study, four different data sets are prepared: (1) counting the first author, (2) counting all the author without limiting the total frequency, (3) counting all the author with limiting the total frequency, and (4) counting adjusted frequencies based on the order of author subscription. The findings of this study show that there are clear differences between the knowledge structure counting all the author and the one counting only the first author. In addition, depending on the different methods, there are subtle changes of cluster members for authors.

• Proceedings of the Korean Society for Information Management Conference
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• 2017.08a
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• pp.11-14
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• 2017

딥러닝 연구동향에 대한 계량서지적 분석을 자아 중심 주제 인용분석 기법을 활용하여 시도하였다. 이를 위해서 Web of Science에서 'deep learning'으로 검색된 인용빈도 상위 15건의 논문을 핵심 논문으로 삼고, 이들 핵심 논문 15편을 인용한 논문 집합을 자아 문헌집합으로 삼았으며, 자아 문헌집합들이 인용한 주요 문헌들을 인용 정체성 문헌집합으로 설정하였다. 인용 정체성 문헌집합에 대해 동시인용분석을 실시하여 주요 문헌, 주요 연구 주제를 파악하고, 영향을 끼친 주요 선행 연구를 파악해보았다.

• Proceedings of the Korean Society for Information Management Conference
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• 2016.08a
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• pp.15-18
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• 2016

전 세계적으로 부는 한류열풍으로 인해 우리나라에 대한 관심이 증대되고 있으며 이에 따른 한류 관련 연구의 수 또한 증가하고 있다. 따라서 본 연구에서는 한류 연구의 핵심 문헌을 선정하고 이를 대상으로 동시인용 분석을 수행하여 한류 연구의 지적구조를 파악하고자 하였다. 이를 위하여 KCI 인용 데이터베이스에서 국내 한류 연구 문헌 116건과 2,042건의 인용정보를 수집하였다. 문헌동시인용기법을 활용하여 분석한 결과 한류 연구 영역을 한류의 파급효과와 영향력 관련 영역, 한류의 정체성 관련 영역으로 2개의 대군집과 5개의 중군집으로 구분 지을 수 있었다.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.77-106
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• 2015

By document co-citation analysis with Korean Citation Index (KCI) data, this study accurately identified the research fronts and hot topics in Korean library and information science (LIS) from 2004 to 2013. 159 core papers in LIS domain and their citations are scraped manually from Korean Citation Index web site. In the cluster analysis and network analysis, 159 core papers were grouped into 27 clusters with multiple papers and 8 singlton clusters. Among the 27 clusters which have multple papers, 'LIS education' cluster was the largest with 16 core papers, and 'citation analysis & intellectual structure analysis' cluster had the strongest citation impact according to the ehs-index. Closer observation of the citations to the core papers in each research front showed that 67.5% of the citations were made by LIS research papers and 32.5% of the citations were made by non-LIS research papers. Considering the share of citations and the citation impact growth index, 'local documentation', 'citation analysis & intellectual structure analysis', and 'research trends analysis' were identified as the most emerging research front in Korean library and information science. The analytical methods used in this study have great potential in discovering the characteristics of research fronts in Korean interdisciplinary research domains.

• Journal of the Korean Society for Library and Information Science
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• v.36 no.4
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• pp.21-47
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• 2002

The present study, on the bass of a premise that reference lists are one of the social products, reflecting various social environments of their own society, was made as part of an attempt to explore the co-occurrence phenomenon of both Korean and Non-Korean Literatures occurred within the Korean references. 321 authors (articles) of 43 Korean journals on Social Sciences were surveyed on research channels and citation motivations and their 11358 references were analyzed. The findings are as follows : 1) The extent of the co-occurrence was that Non-Korean literatures were more 1.9 times (65.3%) cited than Korean ones and English (61.5%)-American (50.4%) predominancy was heavily found. 2) Research channel, worked as an indicator of the identity of researcher as well as the source of research ideas was most Non-Korean channel orientedness (55.8%). 3) Citation motivations were significantly depended on whether Korean or Non-Korean literatures and non-Korean literatures were cheifly cited to be conceptual motivations than other motivations. 4) Research channel among variables was worked as a main effect predicting major citation motivations on Non-Korean literatures. Finally, this study is very suggestive : 1) It might be a new approach and interpretation by adopting citation motivations to explore a process of knowledge producting of researchers 2) Partly, it proved empirically the relationship of knowledge producted by Korean researchers to Non-Korean knowledge through the analysis of citation motivations.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.459-461
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• 2024

본 논문은 국내 정보보안 분야 학술 연구에서 참고문헌 인용행태를 파악하고자 해당 분야 대표 학술지의 인용문헌 현황 및 패턴을 분석하였다. 실험데이터는 "정보보호학회논문지"를 대상으로 수록된 모든 논문과 참고문헌 정보를 수집하고 개별 학술지 및 학술대회의 식별 과정을 통해 구축하였다. 이를 기반으로 참고문헌 현황, 인용나이 통계 분석 결과와 동시출현네트워크 (학술지 및 학술대회)의 생성을 통한 네트워크 중심성 및 시각화 지도를 제시하였다.

• Journal of the Korean Society for information Management
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• v.16 no.2
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• pp.7-26
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• 1999

This experimental study examines informetric analysis of World Wide Web based upon cocitation analysis of Web pages and features of Web resources in the field of communication studies. Cocitation analysis is basically performed to examine the intellectual structure of the communication studies in reflecting link count on the Web. The selected Web resources in the field are mapped in two dimensions based upon the similarities of cocitation frequency, correlation matrix, mutidimensional scale and cluster analysis. Cocitation analysis methods using organizational homepage, personal homepage, or Web index, to Web produced clustering of Web resources that had topical similarities. So far, although informetric analysis of Web resources is in the preliminary stage, it shows that Web can be a new tool for indicating the intellectual structure of a specific research field. In addition, this study analyzes characteristics of printing resources and Web resources, and differences of research methods in applying cocitation analysis.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.