Generalised popularity-similarity optimisation model for growing hyperbolic networks beyond two dimensions.

ABSTRACT: Hyperbolic network models have gained considerable attention in recent years, mainly due to their capability of explaining many peculiar features of real-world networks. One of the most widely known models of this type is the popularity-similarity optimisation (PSO) model, working in the native disk representation of the two-dimensional hyperbolic space and generating networks with small-world property, scale-free degree distribution, high clustering and strong community structure at the same time. With the motivation of better understanding hyperbolic random graphs, we hereby introduce the dPSO model, a generalisation of the PSO model to any arbitrary integer dimension [Formula: see text]. The analysis of the obtained networks shows that their major structural properties can be affected b

SUBMITTER: Kovacs B 

PROVIDER: S-EPMC8770586 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature