Identification of research communities of environmental engineering and their evolution using coauthor network analysis

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.