• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.1022-1031
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• 2009

In this paper, we propose a researcher modeling technique based on ontology and construct social network for researchers using diverse relational properties. User ontology schema is created by extending the existing HR-XML model for a researcher model. User ontology schema and instance are created by OWL. We compose social network model for efficient cooperation between researchers using static relational properties such as educational background and dynamic relational properties such as co-authors and co-workers, etc. Closeness has direction because researcher network is differently configured by the researchers. We define inferencing rules using SWRL and inference ontology rules using racer inference machine to compose direct relationships between researchers. The proposed model for researchers can be applied to the cooperation model for researchers by retrieving common expert group dynamically.

• 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 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 the Korea Convergence Society
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• v.8 no.9
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• pp.199-209
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• 2017

This study was carried out to confirm a convergent research pattern and researchers' role in stem cell sector by social network analysis. Articles were extracted from 1996 to 2012 in PubMed, 515 authors of 270 embryonic stem cell and induced pluripotent stem cell articles and 1,515 authors of 580 adult stem cell and mesenchymal stem cell articles. Degree(D) and betweenness(B) centrality was measured and co-author network was generated for researcher's role. As a result, Core researcher and Intermediary researcher was identified in co-author network. Core researcher had high D. centrality, otherwise high B. centrality or not. Intermediary researcher for convergent research had high B. centrality and low D. centrality. Conclusively, co-author network will be used as objective data not only to find core researchers in subject area for improving achievement but also to select experts for research project evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.295-301
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• 2018

In various disciplines, researchers, not single researchers, tend to cooperate to study the same topic. There are many studies to analyze the collaborative form of various researchers through the social network analysis method, but there are few such studies in the computer field. In this paper, we analyze the characteristics of network and various groups of researchers through the social network analysis technique of the co-authors of the Journal of Korea Institute of Information and Communication Engineering, and analyze the degree centrality, the between centrality and edge weight. As a result of the analysis, many groups were extracted from the co-author's network, but the top 20 groups accounted for more than 50% of the total, also, we could find a pair of researchers who do joint research with a very high frequency. These Co-author networks are expected to be the basis for in-depth research on the subject and direction of research through future researches.

• Journal of the Korean Society for information Management
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• v.31 no.4
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• pp.201-227
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• 2014

The collaboration is becoming ever more widespread in scientific research. Unlike collaboration in other areas such as in a company, research collaboration has an unique feature that it is reflected by scholars' characteristics. Based on previous studies on research collaboration, five major factors are identified. We propose five hypotheses from them and examine these by using both in-person questionnaire survey and relational bibliometric analysis. The survey analysis informs individual choice factors and the bibliometric analysis informs collective consequence factors. The results of this study may have implications for science policies and digital collaboration services.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.387-399
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• 2015

Recently collaboration network is generated to find out experts in their field as potential collaborators in health care sector. In this paper, the co-author network of a National Cancer Center researcher was generated for identifying each researcher's role and collaborative research pattern. The co-author network of 2,437 authors was extracted from 1,194 SCI(E) publications from 2000 to 2010 and author's role was analyzed by author's centrality value. Centrality reflecting only the number of papers and centrality weighted by the paper number, impact factor, and authorship contribution was evaluated. On the comparison with simple degree centrality value and the weighted degree centrality, difference of value was statistically significant(t=11.66, p=0.00). Co-author network considering various variables of the paper provides more objective figure of researcher's role. This suggests that co-author network could be more effective in identifying potential collaborators.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.296-298
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• 2019

개방과 협력의 시대로 불리는 현재, 학문분야의 융합과 소통은 이미 오래전부터 강조되었던 가치다. 그러나 현실적으로 오랜 세월 전문 영역의 틀로써 명확히 분리되어왔던 학자들이 다른 영역의 연구자들과 자유롭게 협업 및 교류하는 상황은 쉽게 일어나기 어렵다. 이러한 문제에 대한 해결책으로서 본 연구는 온라인 네트워크 플랫폼에 주목하였다. 특히 학문 전 분야의 전문 연구자들을 연결하는 세계적인 플랫폼인 리서치게이트의 사례를 통해 사용자 동인을 확인해보고자 하였다. 이를 위해 본 연구에서는 국내 리서치게이트 이용자들에 대한 사용성 평가 설문 및 FGI를 계획하였다. 본 연구의 결과는 국내 연구자들을 중심으로 한 전문연구자 정보 네트워크 플랫폼 개발 방향에 대해 현실적인 시사점을 제시할 것으로 기대한다.

• 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 Information Management
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• v.40 no.1
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• pp.199-215
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• 2009

The web 2.0 concept rapidly spreads to the various field which is based on an opening, the participation, and a share. And the research about the recommendation system, that is the personalize feature, and social network is very active. In the case of the recommendation system and social network, it had been developing in the respectively different area and the new research toward the service model of a form that it fuses these is insignificant. In this paper, I'm going to introduce efficient social network which is called the researcher connection network. It is possible to recommend the researcher intellectually who studies the similar field by analyzing the usage log and user profile. Through this study, we could solved the network expandability problem which is due to the user passive participation and the difficulty of the initial network construction that is the conventional social network problem.