• 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.

• 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.

• 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.

• Journal of Korean Library and Information Science Society
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• v.46 no.4
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• pp.191-205
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• 2015

As the first step in developing the optimal co-authorship allocation method, this study investigated the co-authorship allocation standards of Korean Universities on journal publications. The study compared the standards of 27 Korean universities with Library and Information Science (LIS) departments, and analyzed author rankings generated by applying inflated, fractional, harmonic, and university standard method of co-authorship allocation to 189 Korean LIS faculty publications from 2001 to 2014. The university standards most similar to the standard co-authorship allocation method in bibliometrics(i.e. Vinkler) were those whose co-author credits summed up to 1. However, the university standards differed from Vinkler's in allocating author credits based on primary and secondary author classification instead of allocation based on author ranks. The statistical analysis of author rankings showed that the harmonic method was most similar to the university standards. However, the correlation between the university standards whose co-author credits summed up to greater than 1 and harmonic method was lower. The study results also suggested that middle-level authors are most sensitive to co-authorship allocation methods. However, even the most generous university standards of co-authorship allocation still penalizes collaborative research by reducing each co-authors credit below those of single authors. Follow-up studies will be needed to investigate the optimal method of co-authorship credit allocation.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.667-671
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• 2006

Co-Authorship analysis is a kind of bibliometric analysis. and a well established tool for character of knowledge network in some technical fields. If more than two authors co-author an article, there is a relation of knowledge. So This study aims at discovering the trends and phases of OLED technology using co-authorship analysis, a kind of bibliographic analysis. The Science Citation Index Expanded(SCIE) database was used to search for the number of times paired Korean articles were co-authored in OLED field.

• 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 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 the Korean Society of Radiology
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• v.83 no.4
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• pp.752-758
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• 2022

Authorship is important for research integrity and publication ethics, acting as the basis for credit and academic achievement. Moreover, publication achievements have a significant impact on research grants and academic careers. Inappropriate authorship has been reported for several reasons, including complex interests and competitive environments. One form of this is representative authorship misuse, which includes honorary and ghost authorships. Kin co-authorship, such as parent-children authorship, is another form of inappropriate authorship that has recently emerged as a social problem in Korea. To address these issues, the International Committee of Medical Journal Editors (ICMJE) has established criteria for authorship. Similarly, many journals use the Contributor Roles Taxonomy (CRediT) and Open Researcher and Contributor ID (ORCID) systems to prevent authorship misuse and systematically evaluate author credit and responsibility. Herein, this article reviews authorship and inappropriate authorship, as well as introduces methods to avoid authorship misuse.

• Journal of Information Science Theory and Practice
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• v.8 no.3
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• pp.15-29
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• 2020

This study aims to describe the general patterns of Korean research in Arts and Kinesiology, particularly from the perspective of authorship. Among the 12 sub-areas of Arts and Kinesiology indexed in the Korean Citation Index (KCI), journals in three sub-areas, "Arts," "Design," and "Kinesiology" have the longest publishing histories and produced the largest volume of articles. 68 journals in the "Arts," "Design," and "Kinesiology" sub-areas were accredited in the KCI between 2001 and 2019; 40,955 articles which were published in the journals between the years of accreditation and the end of 2019 serve as the context of this article. Authorship, affiliated institutions and countries, openness to new authors, top researchers, topological properties of authorship networks, overall research performance by authors, and co-authorship patterns were analyzed and compared among three sub-subjects.

• 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.