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Cited by 434

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Community detection in networks with positive and negative links

Open access
Traag, V. A., Bruggeman, Jeroen·2009·Physical Review E

Abstract

Detecting communities in complex networks accurately is a prime challenge, preceding further analyses of network characteristics and dynamics. Until now, community detection took into account only positively valued links, while many actual networks also feature negative links. We extend an existing Potts model to incorporate negative links as well, resulting in a method similar to the clustering of signed graphs, as dealt with in social balance theory, but more general. To illustrate our method, we applied it to a network of international alliances and disputes. Using data from 1993-2001, it turns out that the world can be divided into six power blocs similar to Huntington's civilizations, with some notable exceptions.

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Metadata

Authors
Traag, V. A., & Bruggeman, J.
Venue
Physical Review E
Published
2009-09-21
Volume
80
Issue
3
Pages
036115-036115
ISSN
  • 1539-3755 (ISSN-L)
  • 1550-2376
OpenAlex
W2112461976
Cited by
434
References
35
FWCI
9.73
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Community detection in networks with positive and negative links. https://app.cochat.ai/papers/10.1103/physreve.80.036115
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Traag, V. A., & Bruggeman, J. (2009). Community detection in networks with positive and negative links. Physical Review E. https://doi.org/10.1103/physreve.80.036115

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.