# Dimension matters when modeling network communities in hyperbolic spaces

@inproceedings{Desy2022DimensionMW, title={Dimension matters when modeling network communities in hyperbolic spaces}, author={B'eatrice D'esy and Patrick Desrosiers and Antoine Allard}, year={2022} }

Over the last decade, random hyperbolic graphs have proved successful in providing geometric explanations to many key properties of real-world networks, including strong clustering, high navigability, and heterogeneous degree distributions. Although a few studies have shown that hyperbolic models can generate community structures, another salient feature observed in real networks, we argue that the current models are overlooking the choice of the latent space dimensionality that is required to…

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