• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.117-122
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• 2022

최근 국내외 ESG 연구가 활발해지고 있는 가운데, ESG 연구는 급격한 양적 성장을 하고 있음에도 학술지의 질적 수준을 평가할 수 있는 계량적인 논문은 부족한 상태이다. 본 연구는 한국학술지인용색인(KCI)에서 경영학 분야 내의 KCI 인용지수를 활용하여 상위 10개의 학회를 선정하고 이들 간의 ESG 논문 인용빈도와 네트워크 분석을 하였다. 상호 인용빈도를 활용하여 연결망을 작성하고 네트워크 분석 관점에서 ESG 주제에 관한 각 학술지 간 상호인용빈도를 통해 주어진 학술지의 영향력지수(Impact Factor)와 중심성 지수를 기초하여 연구하였다. 이러한 연구를 바탕으로 학술지들이 핵심 문헌을 식별하고 학문 내 지적 구조를 규명하여 경영학 분야의 ESG 연구 동향을 파악하고자 한다. 본 연구는 국내 발간된 경영학 학술지의 ESG에 대한 학술지의 영향력 인용지수를 비교해 보고 나아가 경영학 학술지의 자기 인용 비율을 확인하고 경영학뿐만 아니라 타 학문 분야에서 경영학 관련 학술지에 대한 인용이 이루어질 수 있도록 다학제적 교류와 추가 연구의 필요성을 제기하고자 한다.

• Proceedings of the Korean Society for Information Management Conference
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• 2010.08a
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• pp.15-20
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• 2010

최근 Web of Science에 도입된 Eigenfactor지수와 논문 영향력 지수(Article Influence Score), 그리고 Scopus에 도입된 SJR 지수는 구글의 PageRank 알고리즘과 같은 네트워크 분석 방식의 인용지수이다. 국내 인용 색인 데이터베이스는 인용 링크가 외부로 향하는 비율과 자기 인용 비율이 높으므로 기존의 네트워크 인용 지수 산출 방식을 그대로 적용하기에는 어려움이 많다. 이 연구에서는 국내 인용색인DB에 대해서 대표적인 네트워크 인용 지수인 저널 페이지랭크를 시험적으로 측정해보고 국내 학술지의 상황을 고려한 개선방안을 모색하였다.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.283-308
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• 2008

In this study, we testify that network structural attributes of a citation network can explain other aspects of journal citation behaviors and the importances of journals. And we also testify various citation impact indicators of journals including JIF and h-index to verify the difference among them especially focused on their ability to explain an institution's local features of citation behaviors. An institutional citation network is derived using the articles published in 2006-2007 by biotechnology faculties of Y University. And various journal citation impact indicators including JIF, SJR, h-index, EigenFactor, JII are gathered from different service sites such as Web of Science, SCImago, EigenFactor.com, Journal-Ranking.com. As a results, we can explain the institution's 5 research domains with inter-citation network. And we find that the co-citation network structural features can show explanations on the patterns of institutional journal citation behavior different from the simple cited frequency of the institution or patterns based on general citation indicators. Also We find that journal ranks with various citation indicators have differences and it implies that total-based indices, average-based indices, and hybrid index(h-index) explain different aspects of journal citation pattern. We also reveal that the coverage of citation DB doesn't be a matter in the journal ranking. Analyzing the citation networks derived from an institution's research outputs can be a useful and effective method in developing several library services.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.947-957
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• 2016

KCI is a database for the citations of journals and papers published in Korea. Classification of a journal listed in KCI was mainly determined by the publisher who registered the journal at the time of application for the journal. However, journal classification in KCI was known for not properly representing the quoting rate between journals. In this study, we extracted communities of the journals registerd in KCI based on quoting relationship using various network clustering algorithms. Among them, the infomap algorithm turned out to give a classification more being alike to the current KCI's in the aspect of the modular structure.

• 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 Korean Library and Information Science Society
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• v.50 no.4
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• pp.77-100
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• 2019

This study aims to analyze and compare centrality and brokerage measures of journal citation network focusing on textmining research. The analytic sample was 193 academic articles collected from 136 KCI journals published in 2018. The journal citation network was constructed based on citation relations. The characteristics, centralities, and brokerages of network was analyzed. The journal citation network consisted 136 nodes and 413 links with directed and weight. According to the five types of centrality(out-degree, in-degree, out-closeness, in-closeness, betweenness), journals of social sciences, engineering, and interdisciplinary research showed higher centrality. Social sciences, engineering and interdisciplinary research journals also showed higher brokerages as a result of brokerage analysis which identify five types of brokerage roles(coordinator, gatekeeper, representative, consultant, liaison). The centralities and brokerages of journals are positively correlated. This study suggested how to construct journal citation network from the articles focusing on certain topics. This was meaningful study in terms of conducting brokerage analysis and comparing it with centrality in the journal citation network.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.79-86
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• 2019

It is very important to analyze and provide information resources for research output produced in the computer field, the core science of the 4th Industrial Revolution. In this paper, SCI journals cited from domestic journals in the computer field were identified and the citation rankings and their co-citation networks were generated, analyzed, mapped and visualized. For this, the bibliographic and citation index information from 2015 to 2017 in the KSCD were used as the basis data, and the co-citation method and network centrality analysis were used. As a result of this study, the number of citations and the citation ranks of SCI journals and papers cited by korean journals in the computer field were analyzed, and peak time(2 years), half-life(6.6 years), and immediacy citation rate(2.4%) were measured by citation age analysis. As a result of network centrality analysis, Three network centralities(degree, betweenness, closeness) of the cited SCI journals were calculated, and the ranking of journals by each network centrality was measured, and the relationship between the subject classifications of the cited SCI journals was visualized through the mapping of the network.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.827-839
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• 2015

Extraction of communities from a journal citation database by the citation structure is a useful tool to see closely related groups of the journals. SCI of Thomson Reuters or SCOPUS of Elsevier have had tried to grasp community structure of the journals in their indices according to citation relationships, but such a trial has not been made yet with the Korean Citation Index, KCI. Therefore, in this study, we extracted communities of the journals of the natural science area in KCI, using various clustering algorithms for a social network based on citations among the journals and compared the groups obtained with the classfication of KCI. The infomap algorithm, one of the clustering methods applied in this article, showed the best grouping result in the sense that groups obtained by it are closer to the KCI classification than by other algorithms considered and reflect well the citation structure of the journals. The classification results obtained in this study might be taken consideration when reclassification of the KCI journals will be made in the future.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.221-238
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• 2020

This study aims to investigate the scholarly communications and citation influences in library and information science field by conducting journal citation network analysis. For data collection, four major journals in library and information science field were chosen and 4,471 of research papers and 18,424 of citation records were collected from Korean Citation Index. The results show that Journal of the Korean Society for Library and Information Science was the most influential journal with highest citation in LIS fields, while Journal of the Korean Society for Library and Information Science Management influenced other research fields.

• Journal of the Korean Society for information Management
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• v.38 no.1
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• pp.53-69
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• 2021

This study aims to understand the research landscape of South Korea using the data of 2020 Google Scholar Metrics. To achieve the goal, we constructed and analyzed four types of networks including the university collaboration network, the keyword co-occurrence network, the journal citation network, and the discipline citation network. Through the analysis of the university collaboration network, we found major universities such as Seoul National University, Keimyung University, and Sungkyunkwan University that have led collaborative research. Job related keywords such as job change intention and job satisfaction have been frequently studied with other keywords. Through the analysis of the journal citation network, we found multiple journals such as The Journal of the Korea Contents Association, Korean Journal of Sociology, and Korean Journal of Culture and Social Issues that have been widely cited by the other journals and influenced them. Finally, Education, Business administration, and Social welfare were identified as the top influential disciplines that have influenced other disciplines through the knowledge diffusion. The study is the first of its kind to use the data of Google Scholar Metrics and conduct a stepwise network analysis (e.g., keyword, journal, and discipline) to broadly understand the research landscape of South Korea. Our results can be used by government agencies and universities to develop effective strategies of promoting university collaboration and interdisciplinary research.