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arXiv · 2206.08773

Maximally modular structure of growing hyperbolic networks

Sámuel G. Balogh·Bianka Kovács·Gergely Palla
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Abstract

Hyperbolic models are remarkably good at reproducing the scale-free, highly clustered and small-world properties of networks representing real complex systems in a very simple framework. Here we show that for the popularity-similarity optimization model from this family, the generated networks become also extremely modular in the thermodynamic limit, in spite of lacking any explicit community formation mechanism in the model definition. According to our analytical results supported by numerical simulations, when the system size is increased, the modularity approaches one surprisingly fast.

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Sámuel G. Balogh, Bianka Kovács, Gergely Palla. 2022-06-17. Maximally modular structure of growing hyperbolic networks. https://doi.org/10.1038/s42005-023-01182-4

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