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Cited by 1,354

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Why social networks are different from other types of networks

Open access
Newman, M. E. J., Park, Juyong·2003·Physical Review E

Abstract

We argue that social networks differ from most other types of networks, including technological and biological networks, in two important ways. First, they have nontrivial clustering or network transitivity and second, they show positive correlations, also called assortative mixing, between the degrees of adjacent vertices. Social networks are often divided into groups or communities, and it has recently been suggested that this division could account for the observed clustering. We demonstrate that group structure in networks can also account for degree correlations. We show using a simple model that we should expect assortative mixing in such networks whenever there is variation in the sizes of the groups and that the predicted level of assortative mixing compares well with that observed in real-world networks.

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Metadata

Authors
Newman, M. E. J., & Park, J.
Venue
Physical Review E
Published
2003-09-22
Volume
68
Issue
3
Pages
036122-036122
ISSN
  • 1063-651X (ISSN-L)
  • 1095-3787
OpenAlex
W2000159446
Cited by
1,354
References
4
FWCI
20.18
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Why social networks are different from other types of networks. https://app.cochat.ai/papers/10.1103/physreve.68.036122
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Newman, M. E. J., & Park, J. (2003). Why social networks are different from other types of networks. Physical Review E. https://doi.org/10.1103/physreve.68.036122

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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.