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Community detection in networks with positive and negative links
1Department of Mathematical Engineering, Université Catholique de Louvain, Bâtiment Euler, Avenue G Lemaître, 4 B-1348 Louvain-la-neuve, Belgium. vincent.traag@uclouvain.be
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|November 13, 2009
Summary
This study introduces a new community detection method for complex networks that accounts for both positive and negative links. Applied to international relations, it reveals six distinct global power blocs.
Area of Science:
- Network Science
- Sociology
- Political Science
Background:
- Community detection is crucial for network analysis.
- Existing methods often ignore negative links, limiting their applicability.
- Real-world networks frequently contain both positive and negative relationships.
Purpose of the Study:
- To develop a generalized community detection method for networks with both positive and negative links.
- To extend the Potts model to accommodate signed relationships in complex networks.
- To analyze the structure of international relations using the new method.
Main Methods:
- Extension of the Potts model to incorporate negative link values.
- Application of the generalized Potts model to a signed graph of international alliances and disputes (1993-2001).
- Comparison with existing community detection techniques and social balance theory.
Main Results:
- The developed method successfully identifies communities in networks with signed links.
- Analysis of international relations data revealed six distinct power blocs.
- The identified blocs show similarities to Huntington's civilizations, with some deviations.
Conclusions:
- The generalized Potts model offers a more comprehensive approach to community detection in signed networks.
- The findings provide insights into the macro-level structure of global power dynamics.
- The method's applicability extends beyond international relations to other complex systems with signed interactions.
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