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Cited by 497

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Random Graphs with Clustering

Open access
Newman, M. E. J.·2009·Physical Review Letters

Abstract

We offer a solution to a long-standing problem in the theory of networks, the creation of a plausible, solvable model of a network that displays clustering or transitivity--the propensity for two neighbors of a network node also to be neighbors of one another. We show how standard random-graph models can be generalized to incorporate clustering and give exact solutions for various properties of the resulting networks, including sizes of network components, size of the giant component if there is one, position of the phase transition at which the giant component forms, and position of the phase transition for percolation on the network.

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Metadata

Authors
Newman, M. E. J.
Venue
Physical Review Letters
Published
2009-07-27
Volume
103
Issue
5
Pages
058701-058701
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
OpenAlex
W2000687288
Cited by
497
References
1
FWCI
21.08
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Random Graphs with Clustering. https://app.cochat.ai/papers/10.1103/physrevlett.103.058701
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Newman, M. E. J. (2009). Random Graphs with Clustering. Physical Review Letters. https://doi.org/10.1103/physrevlett.103.058701

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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.