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Cited by 290

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Static network structure can stabilize human cooperation

Open access
Rand, David G., Nowak, Martin A., Fowler, James H., Christakis, Nicholas A.·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: Human populations are both extremely cooperative and highly structured. Mathematical models have shown that fixed network interaction structures can lead to cooperation under certain conditions, by allowing cooperators to cluster together. Here, we provide empirical evidence of this phenomenon. We explore how different fixed social network structures can promote cooperation using economic game experiments. We find that people cooperate at high stable levels, as long as the benefits created by cooperation are larger than the number of neighbors in the network. This empirical result is consistent with a rule predicted by mathematical models of evolution. Our findings show the important role social networks can play in human cooperation and provide guidance for promoting cooperative behavior.

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Metadata

Authors
Rand, D. G., Nowak, M. A., Fowler, J. H., & Christakis, N. A.
Venue
Proceedings of the National Academy of Sciences
Published
2014-11-17
Volume
111
Issue
48
Pages
17093-17098
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2105123723
Cited by
290
References
13
FWCI
86.48
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Static network structure can stabilize human cooperation. https://app.cochat.ai/papers/10.1073/pnas.1400406111
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Rand, D. G., Nowak, M. A., Fowler, J. H., & Christakis, N. A. (2014). Static network structure can stabilize human cooperation. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1400406111

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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.