• IE interfaces
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• v.25 no.4
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• pp.458-471
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• 2012

In this study, we investigate the cooperative relationships between researchers who have co-authorship in the logistics-related journals in Korea by using social network analysis (SNA). We analyzed the co-authorship data of 781 articles published from 2005 to 2011 in four journals of 'Logistics Study', 'Journal of Korean Society of SCM', 'Korea Logistics Review' and 'Journal of Shipping and Logistics.' We examined the trend of cooperative research in the field of logistics with basic data of the co-authorship network. Then, we analyzed structural properties of the network and the sub-networks of research groups having co-authorship. We could verify the authors who play important roles within the network by using SNA indicators. In addition, we constructed the keyword networks based on the keyword data of all articles by research groups in order to understand the research topics of each group, and thereby we could draw several implications on the cooperative researches in the field of logistics.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.269-284
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• 2022

Exploring research similarity of researchers offers insight on research communities and potential interactions among scholars. While co-authorship is a popular measure for studying research similarity of researchers, it cannot provide insight on authors who have not collaborated yet. In this work, we present novel approach to capture research similarity of authors using citation information. Extensive study is conducted on DATA & KNOWLEDGE ENGINEERING (DKE) publications to demonstrate and compare suggested approach with co-authorship based approach. Analysis result shows that proposed approach distinguishes author relationships that is not shown in co-authorship network.

• 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.

• The Mathematical Education
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• v.52 no.4
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• pp.483-496
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• 2013

In this study, we investigated the structure of the mathematics education scholars' co-authorship relationship in papers registered at the National Research Foundation of Korea by social network analysis. The data were 354 scholars from 257 papers in 4 journals from 2009 to 2013 based on 'the 2009 revised Korean National Curriculum'. For the analysis, Pajek3 and UCINET6.3 were used. The results of this study were as follows: First, each of the mathematics education scholars is connected on average with about 5 paths of intermediate collaborators. Second, Analyses of the first component group found distinguishable scholar groups' characteristics depending on their affiliations, majors, and job statuses. Third, there were scholars having high values in network degree centrality measures despite not having high numbers in published papers. On the contrary, there sere scholars having high numbers in published papers despite not having high values in network analysis. Finally, I suggested the directions for the future research with the limitations of this study.

• 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.

• Journal of vocational education research
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• v.35 no.6
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• pp.85-112
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• 2016

This study aims to identify the cooperative relations among researchers and their network structures based on the academic papers published in the field of lifelong vocational education and training from 2000 to 2015. Authors in three representative journals, 'Journal of Lifelong Education', 'Journal of Vocational Education Research', and 'Korea Research Institute for Vocational Education & Training,' during the periods, were selected and co-authorship network analysis was applied using NetMiner 4.0 in order to find the social relation among researchers and their academic influences. The results showed that the research productivity in the field of lifelong vocational education and training forms a shape of the power function where there exist components called, 'detailed research groups.' This network structure represents characteristics of a small world. In addition, the centrality analysis suggest authors with high centrality serve as co-authors who play as a central role on the network and exchange information with other researchers, while those with high betweenness centrality serve as a channel where they transfer knowledge and information among research groups. Increasing member of co-authorship has positively contributed to the opportunity and development of cooperative research among researchers in the field of lifelong vocational education and training. However it is recommended co-authorship be formed more heterogeneously instead of a few researches centrally dominate co-authorship. Various researchers should continually conduct research for good research performances.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.273-289
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• 2015

This study examined changes in citation index scores and rankings of thirty-five chemistry faculty members at Seoul National University using different co-authorship credit allocation models. Using 1,436 Web of Science papers published between 2007 and 2013, we applied the inflated, fractional, harmonic, network-based allocation, and harmonic+ models to calculate faculty's h-, R-, and normalization of h- and R- index scores and rankings. The harmonic+ model, which is based on our belief that contribution of primary authors should be the same regardless of collaboration, is designed to minimize the penalty for research collaboration imposed by harmonic and NBA models by boosting the contribution of collaborating primary authors to be on the equal footing with single authors. Although citation rankings by different models are correlated with each other within the same type of citation indicator, rankings of many faculty members changed across models, suggesting the importance of an accurate and relevant authorship credit allocation model in the citation assessment of researchers. The study also found that authorship patterns in conjunction with citation counts are important factors for robust authorship models such as harmonic and NBA, and harmonic+ model may be beneficial for collaborating primary authors. Future research that reexamines the models with updated empirical data would provide further insights into the robustness of the models.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.203-219
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• 2020

The primary purpose of this study is to identify spatial distribution patterns of co-authoring activities in Korean cadastral science. The analysis showed that a small number of researchers played an essential role in the Korean cadastral co-authorship network. In particular, some authors not only had a significant influence on other nodes in the network but also served as intermediaries between researchers. Moreover, the distance between researchers influenced co-authorship decisions to a limited extent. This study differs considerably from previous studies in that it used spatial analysis techniques to identify spatial distribution patterns of co-authoring activities. However, this research is limited in that it applied only 2019 data to determine the spatial distribution pattern of co-authoring activities. We can overcome this limitation if we analyze the spatial distribution patterns of co-authoring activities using multi-year data in future studies.

• Korean System Dynamics Review
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• v.17 no.3
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• pp.31-50
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• 2016

This study examines the basic conditions of joint authorship research activities in the Korean System Dynamics Review and points out the structural co-author network characteristics among co-authored papers based on the social network analysis(SNA) techniques. In specific, this study identifies the cooperative relationship of research papers in the Korean System Dynamics Review, knowledge formation, and knowledge propagation paths. The study results imply that Korean System Dynamics Review has exhibited the typical 'Steven's power law,' which is repeatedly observed among complex systems, and that knowledge structure centered upon and propagated around couples of researchers. Additionally, the study results present that there have been active personal exchanges among major researchers. In contrast, personal contacts among research groups and within groups seem relatively weak.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.53-63
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• 2023

The utilization of department information in bibliometric analysis using scientific and technological literature is highly advantageous. In this paper, the department information dataset was built through the screening, data refinement, and classification processing of authors' department type belonging to university institutions appearing in academic journals in the field of science and technology published in Korea, and the automatic classification model based on deep learning was developed using the department information dataset as learning data and verification data. In addition, we analyzed the co-authorship structure and network in the field of computer science using the department information dataset and affiliation information of authors from domestic academic journals. The research resulted in a 98.6% accuracy rate for the automatic classification model using Korean department information. Moreover, the co-authorship patterns of Korean researchers in the computer science and engineering field, along with the characteristics and centralities of the co-author network based on institution type, region, institution, and department type, were identified in detail and visually presented on a map.