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DOI: https://doi.org/10.4491/eer.2020.475
The driving force for collaboration networks in environmental engineering in South Korea
Jaebeom Park1, Jeryang Park2, and Yongju Choi1
1Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Republic of Korea
2Department of Civil and Environmental Engineering, Hongik University, 94 Wausan-ro, Mapo-gu, Seoul, Republic of Korea
Corresponding Author: Yongju Choi ,Tel: +82 2 880 7376, Fax: +82 2 873 2684, Email: ychoi81@snu.ac.kr
Received: August 20, 2020;  Accepted: January 27, 2021.
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ABSTRACT
Here, for the first time, coauthor network and cluster analysis were utilized in the environmental engineering field to identify the driving force for scientific collaboration among individuals and the formation of clusters. Papers published in South Korean domestic environmental engineering journals from 2004 to 2018 were assessed, which enabled identification of unique network characteristics that represent not only the field of study, but also the regional boundaries of the data source. Despite being limited to a single country, the study identifies network characteristics, such as scale invariance, that are typically found in other coauthor networks. Nine clusters were identified, the identity of which could be defined by two variables: research interests and author affiliations. The clusters were divided by the sameness or geographical proximity of author affiliations and problem-oriented research topics. These also describe the inter-cluster relationships, validating the notion that the two variables are the major driving force for collaboration networks. This study substantially advances the understanding of scientific collaboration in the environmental engineering field and can guide future studies, such as the role of coauthor networks in environmental engineering within or outside of regional boundaries and the role of networks in domestic publications in other fields of study.
Keywords: Cluster analysis | Coauthor network | Collaboration pattern | Complex network analysis | Environmental engineering
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