Maximally modular structure of growing hyperbolic networks

Balogh, Sámuel G. ✉ [Balogh, Gáspár Sámuel (Statisztikus fizi...), author] Department of Biological Physics (ELTE / ELU FoS); Kovács, Bianka [Kovács, Bianka (Komplex rendszere...), author] Department of Biological Physics (ELTE / ELU FoS); Palla, Gergely [Palla, Gergely (Elméleti és matem...), author] Egészségügyi Menedzserképző Központ (SU / DHS); Department of Biological Physics (ELTE / ELU FoS)

English Article (Journal Article) Scientific
Published: COMMUNICATIONS PHYSICS 2399-3650 2399-3650 6 (1) Paper: 76 , 12 p. 2023
  • SJR Scopus - Physics and Astronomy (miscellaneous): D1
Fundings:
  • (K128780) Funder: NR-DIO
  • European Union’s Horizon 2020 research and innovation programme(101021607)
  • (RRF-2.3.1-21-2022-00004)
Hyperbolic network models provide a particularly successful approach to explain many peculiar features of real complex networks including, for instance, the small-world and scale-free properties, or the relatively high clustering coefficient. Here we show that for the popularity-similarity optimisation (PSO) model from this family, the generated networks become also extremely modular in the thermodynamic limit, despite lacking any explicitly built-in community formation mechanism in the model definition. In particular, our analytical calculations indicate that the modularity in PSO networks can get arbitrarily close to its maximal value of 1 as the network size is increased. We also derive the convergence rate, which turns out to be dependent on the popularity fading parameter controlling the degree decay exponent of the generated networks.
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2025-04-01 23:07