Name
Abstract | ||
|---|---|---|
We demonstrate that the self-similarity of some scale-free networks with respect to a simple degree-thresholding renormalization scheme finds a natural interpretation in the assumption that network nodes exist in hidden metric spaces. Clustering, i.e., cycles of length three, plays a crucial role in this framework as a topological reflection of the triangle inequality in the hidden geometry. We prove that a class of hidden variable models with underlying metric spaces are able to accurately reproduce the self-similarity properties that we measured in the real networks. Our findings indicate that hidden geometries underlying these real networks are a plausible explanation for their observed topologies and, in particular, for their self-similarity with respect to the degree-based renormalization. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1103/PhysRevLett.100.078701 | PHYSICAL REVIEW LETTERS |
DocType | Volume | Issue |
Journal | 100 | 7 |
ISSN | Citations | PageRank |
0031-9007 | 44 | 2.86 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| m angeles serrano | 1 | 44 | 2.86 |
| Dmitri Krioukov | 2 | 1138 | 90.70 |
| Marián Boguñá | 3 | 111 | 7.39 |