• Journal of the Korean Data and Information Science Society
• /
• v.26 no.2
• /
• pp.335-346
• /
• 2015

The purpose of this study is to compare not only network influence of individual coauthor but also the types and properties of two coauthor networks of Communications for Statistical Applications and Methods and the Korean Journal of Applied Statistics which are published by the Korean Statistical Society using social network analysis.As the result of two network structure comparison, density, inclusiveness, reciprocity and clustering coefficient which represent the type of coauthor networks show almost similar values and the Korean Journal of Applied Statistics has bigger values in average degree, average distance and diameter because it has more nodes than Communications for Statistical Applications and Methods. Finally two journals have very similar type of coauthor network. In the comparison of network centrality of two coauthor networks, closeness centrality and betweenness centrality of the Korean Journal of Applied Statistics are bigger than those of Communications for Statistical Applications and Methods at the statistical significance level 0.05. The coauthor network of the Korean Journal of Applied Statistics has faster information delivery and stronger betweenness than that of Communications for Statistical Applications.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06c
• /
• pp.54-56
• /
• 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 Korea Convergence Society
• /
• v.8 no.9
• /
• pp.199-209
• /
• 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.

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

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

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

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

• Proceedings of the Korean Society for Information Management Conference
• /
• 1994.12a
• /
• pp.47-50
• /
• 1994

사회과학 분야의 공저율(12%)은 자연과학 분야(93%)와 비교하여 현저한 차이를 보였다. 그러나 문헌정보학의 한 소주제 분야인 정보학의 공저율은 80%로 학문간의 접목상태에 따른 공저율의 변화가 측정되었다. 한편 핵심저자군으로 구성된 공저자망 분석결과 매우 공저율이 높거나 거의 공저활동이 없는 두 유형의 저자군이 발견되었다.

• Journal of Korean Library and Information Science Society
• /
• v.42 no.2
• /
• pp.105-125
• /
• 2011

This paper grasps about various features of the coauthorship network based on the co-author frequency in the Korean LIS Research Community. This issue includes many topics such as changable aspects of coauthorship network, properties of higher cooperative authors groups. This work is mostly analyzed through a bibliographic analysis of articles which is published from 2000 to 2009(10 years) in Korean Library & Information Science major four journals. The results show three major implications. 1) There is a various structural changes of coauthorship network on the change of the co-author frequency. 2) There are 21 research pairs in the higher cooperative authors groups with the co-author frequency more than five. 3) There seems that any subjective relations between the articles which is produced by 21 research pairs were not clearly presents.

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