Hypermodularity and community detection in higher-order networks

Autor:	del Genio, Charo I.
Rok vydání:	2024
Předmět:	Physics - Physics and Society Condensed Matter - Disordered Systems and Neural Networks Computer Science - Social and Information Networks
Druh dokumentu:	Working Paper
Popis:	Numerous networked systems feature a structure of non-trivial communities, which often correspond to their functional modules. Such communities have been detected in real-world biological, social and technological systems, as well as in synthetic models thereof. While much effort has been devoted to develop methods for community detection in traditional networks, the study of community structure in networks with higher-order interactions is still relatively unexplored. In this article, we introduce a formalism for the hypermodularity of higher-order networks that allows us to use spectral methods to detect community structures in hypergraphs. We apply this approach to synthetic random networks as well as to real-world data, showing that it produces results that reflect the nature and the dynamics of the interactions modelled, thereby constituting a valuable tool for the extraction of hidden information from complex higher-order data sets. Comment: 13 pages, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2412.06935 Zobrazit plný text záznamu View this record from Arxiv