Random graph models of social networks
Bibliographic Data
| ID | 23317201 |
|---|---|
| Authors | M E J Newman (0000-0002-0907-1660, Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501; Department of Sociology, Columbia University, 1180 Amsterdam Avenue, New York, NY 10027; and Department of Theoretical and Applied Mechanics, Cornell University, Ithaca, NY 14853-1503, corresponding author), Duncan J Watts (0000-0001-5005-4961, Santa Fe Institute), Steven H Strogatz (0000-0003-2923-3118, Santa Fe Institute) |
| Year | 2002 |
| Volume | 99 |
| Issue | suppl_1 |
| Pages | 2566-2572 |
| Publication date | 2002-02-19 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Proceedings of the National Academy of Sciences (JOURNAL) |
| Journal identifiers | ISSN: 0027-8424 • E-ISSN: 1091-6490 |
| Publisher | National Academy of Sciences (PUBLISHER • US) |
| DOI | 10.1073/pnas.012582999 |
| PMID | 11875211 |
| PMCID | PMC128577 |
| OpenAlex | W2101267973 |
| Language | EN |
| Citations received | 73 |
| References cited | 23 |
We describe some new exactly solvable models of the structure of social networks, based on random graphs with arbitrary degree distributions. We give models both for simple unipartite networks, such as acquaintance networks, and bipartite networks, such as affiliation networks. We compare the predictions of our models to data for a number of real-world social networks and find that in some cases, the models are in remarkable agreement with the data, whereas in others the agreement is poorer, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph.
Biological network · Bipartite graph · Combinatorics · Complex network · Degree distribution · Evolving networks · Exponential random graph models · Graph · Random graph · Simple (philosophy) · Social media · Social network (sociolinguistics) · World Wide Web · Complex Network Analysis Techniques · Computer Science · Mathematics · Opinion Dynamics and Social Influence · Peer-to-Peer Network Technologies · Theoretical Computer Science
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| Unique citing works | 73 |
|---|---|
| Citations per year | 2,92 |
| Citation span | 2001 - 2026 (26) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 63 |