The inherent community structure of hyperbolic networks.

ABSTRACT: A remarkable approach for grasping the relevant statistical features of real networks with the help of random graphs is offered by hyperbolic models, centred around the idea of placing nodes in a low-dimensional hyperbolic space, and connecting node pairs with a probability depending on the hyperbolic distance. It is widely appreciated that these models can generate random graphs that are small-world, highly clustered and scale-free at the same time; thus, reproducing the most fundamental common features of real networks. In the present work, we focus on a less well-known property of the popularity-similarity optimisation model and the [Formula: see text] model from this model family, namely that the networks generated by these approaches also contain communities for a wide range of the pa

SUBMITTER: Kovacs B 

PROVIDER: S-EPMC8346486 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature