The application of exponential random graph models to collaboration networks in biomedical and health sciences: a review
Year: 2024
Type: article
Study design: Systematic Review
Abstract: Collaboration has become crucial in solving scientific problems in biomedical and health sciences. There is a growing interest in applying social network analysis to professional associations aiming to leverage expertise and resources for optimal synergy. As a set of computational and statistical methods for analyzing social networks, exponential random graph models (ERGMs) examine complex collaborative networks due to their uniqueness of allowing for non-independent variables in network modeling. This study took a review approach to collect and analyze ERGM applications in health sciences by following the protocol of a systematic review. We included a total of 30 studies. The bibliometric characteristics revealed significant authors, institutions, countries, funding agencies, and citation impact associated with the publications. In addition, we observed five types of ERGMs for network modeling (standard ERGM and its extensions—Bayesian ERGM, temporal ERGM, separable temporal ERGM, and multilevel ERGM). Most studies (80%) used the standard ERGM, which possesses only endogenous and exogenous variables examining either micro- (individual-based) or macro-level (organization-based) collaborations without exploring how the links between individuals and organizations contribute to the overall network structure. Our findings help researchers (a) understand the extant research landscape of ERGM applications in health sciences, (b) learn to control and predict connection occurrence in a collaborative network, and (c) better design ERGM-applied studies to examine complex relations and social system structure, which is native to professional collaborations.
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,090
Funders: International Development Research Centre, Bundesministerium für Bildung und Forschung, Bundesministerium für Wirtschaft und Technologie, Ministero dell’Istruzione, dell’Università e della Ricerca, Department of Health and Aged Care, Australian Government, Medical Research Council Canada, National Institutes of Health, Centers for Disease Control and Prevention, Quality Enhancement Research Initiative, Canadian Institutes of Health Research, National Health and Medical Research Council, National Medical Research Council, Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz, National Institute on Aging, National Institute of Mental Health, National Institute on Drug Abuse, National Cancer Institute, National Institute of General Medical Sciences, Fogarty International Center, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Dental and Craniofacial Research, National Center for Advancing Translational Sciences
OpenAlex ID: W4391144407