Fritz, C., Mehrl, M. orcid.org/0000-0002-5825-9256, Thurner, P.W. et al. (1 more author) (2025) Exponential Random Graph Models for Dynamic Signed Networks: An Application to International Relations. Political Analysis. ISSN 1047-1987
Abstract
Substantive research in the Social Sciences regularly investigates signed networks, where edges between actors are positive or negative. One often-studied example within International Relations for this type of network consists of countries that can cooperate with or fight against each other. These analyses often build on structural balance theory, one of the earliest and most prominent network theories. While the theorization and description of signed networks have made significant progress, the inferential study of link formation within them remains limited in the absence of appropriate statistical models. We fill this gap by proposing the Signed Exponential Random Graph Model (SERGM), extending the well-known Exponential Random Graph Model (ERGM) to networks where ties are not binary but positive or negative if a tie exists. Since most networks are dynamically evolving systems, we specify the model for both cross-sectional and dynamic networks. Based on hypotheses derived from structural balance theory, we formulate interpretable signed network statistics, capturing dynamics such as “the enemy of my enemy is my friend”. In our empirical application, we use the SERGM to analyze cooperation and conflict between countries within the international state system. We find evidence for structural balance in International Relations.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © The Author(s), 2025. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article. |
Keywords: | exponential random graph models; signed networks; structural balance theory; International relations; inferential network analysis |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Politics & International Studies (POLIS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Nov 2024 15:12 |
Last Modified: | 30 Jan 2025 09:19 |
Published Version: | https://www.cambridge.org/core/journals/political-... |
Status: | Published online |
Publisher: | Cambridge University Press |
Identification Number: | 10.1017/pan.2024.21 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:219360 |
Download
Licence: CC-BY-NC-ND 4.0