Name
Abstract | ||
|---|---|---|
All real networks are different, but many have some structural properties in common. There seems to be no consensus on what the most common properties are, but scale-free degree distributions, strong clustering, and community structure are frequently mentioned without question. Surprisingly, there exists no simple generative mechanism explaining all the three properties at once in growing networks. Here we show how latent network geometry coupled with preferential attachment of nodes to this geometry fills this gap. We call this mechanism geometric preferential attachment (GPA), and validate it against the Internet. GPA gives rise to soft communities that provide a different perspective on the community structure in networks. The connections between GPA and cosmological models, including inflation, are also discussed. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1038/srep09421 | SCIENTIFIC REPORTS |
Keywords | Field | DocType |
applied mathematics,statistics,complex networks,nonlinear phenomena | Community structure,Existential quantification,Computer science,Theoretical computer science,Artificial intelligence,Generative grammar,Cluster analysis,Inflation,Preferential attachment,Network geometry,The Internet | Journal |
Volume | Issue | ISSN |
5 | 1 | 2045-2322 |
Citations | PageRank | References |
10 | 0.67 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Konstantin Zuev | 1 | 13 | 2.09 |
| Marián Boguñá | 2 | 10 | 0.67 |
| Ginestra Bianconi | 3 | 357 | 13.32 |
| Dmitri V. Krioukov | 4 | 42 | 3.91 |