Identification of research communities of environmental engineering and their evolution using coauthor network analysis. (March 2022)

• Record Type: Journal Article
• Authors: Park, Jaebeom; Park, Jeryang; Choi, Yongju
• Is Part Of: Environmental modelling & software. Volume 149(2022)
• Publication Date: 2022-03
• Subjects: Bibliometric analysis -- Coauthor network -- Community evolution -- Environmental engineering -- Research pattern -- Trend analysis; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105320
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Networks of coauthorship for scientific publication well represent the collaboration dynamics among members of a scientific community. Here, we employed a coauthor network analysis to identify research communities and their evolutionary patterns as the first attempt to characterize the dynamics of collaboration in environmental engineering. Using bibliometric data from 2007 to 2018 in environmental engineering, 20 research communities were identified and two major drivers of scientific collaboration were revealed: research interest and country of one's affiliation. We developed a novel methodology that enables tracking cluster's evolutionary patterns. This methodology allowed systematic stereotyping of each cluster as "mature" or "emerging". The two stereotypes did not show a significant difference in the annual growth rate of the volume of publications, implying that comparable attention has been paid to advancing the knowledge of formerly-established subjects and exploring innovative subjects of environmental engineering. Highlights: A total of 68, 881 environmental engineering papers published 2007–2018 were collected to construct the coauthor network. Twenty clusters identified from the coauthor network represent research communities in environmental engineering developed from spontaneous coauthoring. Major drivers of scientific collaboration in environmental engineering were research interest and country of author's affiliation. Novel methodology developed herein categorized evolutionary behaviors of research communities into "mature" or "emerging".