• Proceedings of the Korean Society for Information Management Conference
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• 2016.08a
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• pp.23-27
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• 2016

최근 학제간 연구에 대한 관심이 커지면서 자연스럽게 연구자들 간의 협력관계, 특히 학술적 협력관계에 대한 관심 역시 증가하고 있다. 이에 따라 공저 네트워크 자체의 속성에 대한 연구 뿐만 아니라 공저 분석 기법을 통해 특정 학문 분야의 지적 구조를 해석하려는 연구들이 꾸준히 진행되고 있다. 본 연구는 공저 네트워크 분석을 통해 국외 학제적 저널의 공저 현황과 소속기관 유형을 살펴보고 매개 중심성과 연결정도 중심성을 통해 학술지별 주요 소속기관과 저자들의 위치, 그리고 그들간의 협력 관계를 살펴보고자 하였다.

• Journal of the Korean Society for information Management
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• v.33 no.4
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• pp.175-199
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• 2016

We analyzed the relationships between the co-authorship network centralities and the research performance indicators with the authors and the number of citations of the papers published for 10 years in Korean library and information science journals. In particular, the research performance indicators were calculated with normal counting and with fractional counting also. As a result of correlation analysis between the variables by setting the different ranges of the author groups to be analyzed according to the number of articles, it was possible to explain the inconsistent results of the previous studies on the correlations between the researchers' citation indicators and their co-authorship network centralities. Overall, the degree of co-authorship activities measured by collaboration coefficient showed no or negatively correlated with research performance. There were statistically significant positive correlations between the centralities and the research performance indicators, but the correlation was not significant in the analysis of the top 30 authors by number of articles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.83-86
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• 2019

This study proposes a methodology for predicting co-authorship of contributors to a highly anticipated paper through link analysis and learning, taking into account the result of collaborative research. Previous studies predict the co-authorship with high accuracy, but this shows limitations in that the quality of the predicted relationship is not considered. Therefore, to solve the above problem, we propose three steps to predict the co-authorship that will help with the expected performance: (1) Construct a heterogeneous graph to measure results of collaborative research. (2) Analyze and learn links based on results of collaborative research. (3) Predict links that are anticipated to have high expectation. It is expected to be useful for increasing confidence in the predicted co-authorship.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.54-56
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• 2012

최근 다양한 관점에서의 사회관계망 분석이 확대되면서 R&D분야도 연구자 간의 네트워크를 이해하고자 하는 요구사항도 증가하고 있지만 국내에서는 연구자나 과학자 사이의 네트워크 분석 및 서비스에 대한 시도가 다양하지 않은 상황이다. 본 논문은 국내 R&D분야의 사회관계망에 대한 이해증진을 위하여 구현한 공저자 네트워크 가시화 서비스에 대한 기술이다. 사회 관계망 분석과 서비스를 위하여 동명이인 저자를 식별하고 이들 간의 공저자 관계를 계량정보 분석기법을 이용하여 분석하였으며 연구자들 간의 네트워크를 쉽게 조망할 수 있도록 정보를 가시화 하였다. 본 논문에서 구현한 공저자 네트워크 서비스는 국내 연구자들 간의 협업형태를 직관적으로 이해할 수 있도록 하며 각 연구 분야의 핵심연구자 및 다양한 연구 분야를 연계하는 허브 연구자의 확인을 용이하게 한다.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.231-258
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• 2018

This study attempted to identify dynamically changing structure and analyze factors of collaboration. In order to perform this study, 1,631 articles in SCI journals were collected, and 3,898 researchers' information were extracted. To examine the dynamics of collaboration networks, the co-authorship data collected from 2001 to 2015 were divided into three sets, and were analyzed with respect to each period. The results of this study were summed up as: 1) "Co-authorship of the last year" was entirely significant factors while research career was significant only in the period of 2 to 3. 2) It was found that "Influence of the researchers" and "Emergence of the researchers" were significant factors in the period of 2 to 3 and in the period of 1 to 2. 3) "Same institutions", "Same subject", and "Journal similarity" were significant factors in all periods.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.2
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• pp.149-169
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• 2021

As collaboration of research is increasing in social science, this study aims to investigate the changes in patterns of research collaboration in the field of library and information science, over the years from 2002 to 2020. The data used for this study were collected from four major journals in the field to analyze the frequency of co-authored research articles by journals and by institutions that all authors were associated with. Also, the institutions data were used to build a co-authorship network, which produced various indices including TBC (Triangle Betweenness Centrality) that showed which institutions were more central than others in the network. The result shows the number of co-authored articles were constantly increasing in all journals, and some institutions, mostly universities, showed the higher centrality scores than others and the range of collaboration were also expanded.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.90-94
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• 2006

The research about social network for analyzing human relationship has been steadily worked due to the importance in the social science field. It is also important that analyzing the relationship between researchers in the academic and research fields. Especially, the network by joint research or citation between researchers is useful to evaluating projects or making policy on academic and research fields. This paper describes a method that generates two kinds of researcher networks showing co-authorship and citation relationship between researchers based on national R&D reference information ontology. We infer pair of researchers in co-authorship or citation relationship by SPARQL query from the ontology which is composed of research outcomes and their participating researchers in RDF triples. By postprocessing, we construct researcher network which links researchers in co-authorship and citation relationship.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1259-1270
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• 2011

This study analyzed an aspect of co-author relationship in papers published in the Korean Journal of Applied Statistics by social network analysis. The data were extracted from 664 papers in the journal from 2000 to 2010. Authors at center of the network are detected by a network centrality analysis. Sub-network analysis found distinguishable research groups from the point of view of their topics or affiliations. The significance of affiliations to co-author relationship was examined by logistic regression analysis.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.2
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• pp.153-168
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• 2003

A hyperlink on academic World Wide Web has started to be recognized as a form of collaborative communication network connecting individual researchers and research groups and expanding their collaboration relations by making possible easy and direct online contact among people or groups anywhere in the world. This paper describes the structure of academic hyperlinks embedded in universities' Web sites hosted at the 10 Asian countries and further, examines the association between the structure of the hyperlink network and collaborative communication pattern among those countries based on their frequency of co-authoring articles. This research found that the number of inter-hyperlinks among universities' Web sites was significantly correlated with the frequency of co-authored articles across the 10 countries.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.193-207
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• 2008

The study investigates the co-authorship networks of MIS Quarterly as one of the leading journals in IS field and examines patterns of collaboration networks of the intellectuals. These issues are addressed through a systematic Social Network Analysis (SNA) of 242 articles published from 1996 to 2004 in MIS Quarterly. Results of co-authorship network analysis indicate that the whole incomplete network has a low degree of density. Thus, we analyzed three biggest sub-networks to find out who the key players of each sub-network are. Then, following the keyword classification scheme, relevant data from the articles were collected and coded to analyze three major co-authorship networks of MIS Quarterly community. Some implications are drawn from different research keywords of each sub-network.