Preferential Attachment, Homophily, and the Structure of International Networks, 1816–2003
Abstract
This study examines the extent to which network formation processes in international relations parallel models that characterize the formation processes of physical, biological, and social networks. I introduce two influential models from networks sciences: Preferential Attachment (PA) models state that the probability of a new node forming a link with an existing node is a function of the latter node’s centrality. Networks that form through a PA process tend to have a power-law degree distribution. The Homophily (HO) model states that nodes tend to attach to similar other nodes. Such networks evolve into a set of homogenous subgroups. An analysis of alliance and trade networks over the 1816 (1870)–2003 period reveals strong evidence that alliance networks are affected by homophily processes. Trade networks form via a preferential attachment process. The tendency of international networks to evolve according to such processes increases over time. I discuss the implications of these results.
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This kind of 'preferential attachment' can have large impacts on network structures, which could include AI systems assuming a more critical and central role than intended, or leading to an unequal distribution of resources or power.
“This kind of 'preferential attachment' can have large impacts on network structures (Kunegis et al., 2013; Maoz, 2012), which could include AI systems assuming a more critical and central role than intended, or leading to an unequal distribution of resources or power (see Section 4.3).”
From Multi-Agent Risks from Advanced AI (2025) · cites this paper as Maoz, 2012
Cites
The Dissemination of Culture: A Model with Local Convergence and Global Polarization
Axelrod, R. (1997) · Journal of Conflict Resolution · doi:10.1177/0022002797041002001 · Cited by 1,918 · see citing works
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Acosta, B. (2016) · Journal of Peace Research · doi:10.1177/0022343315618001 · Cited by 32 · see citing works
Multi-Agent Risks from Advanced AI
Hammond, L., Chan, A., Clifton, J., Hoelscher-Obermaier, J., Khan, A., McLean, E., Smith, C., Barfuss, W., Foerster, J., Gavenčiak, T., et al. (2025) · arXiv · doi:10.48550/arxiv.2502.14143 · Cited by 10 · see citing works
- Authors
- Maoz, Z.
- Affiliations
- University of California, Davis and Interdisciplinary Center, Herzliya, Israel
- Venue
- Conflict Management and Peace Science
- Publisher
- SAGE Publications
- Published
- 2012-07
- Volume
- 29
- Issue
- 3
- Pages
- 341-369
- ISSN
- 0738-8942
- 1549-9219
- Cited by
- 67
- References
- 1
- Language
- en
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