Multiplex measures for higher-order networks

Fuente: arXiv
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Auteurs principaux: Lotito, Quintino Francesco, Montresor, Alberto, Battiston, Federico
Format: Preprint
Publié: 2024
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author Lotito, Quintino Francesco
Montresor, Alberto
Battiston, Federico
author_facet Lotito, Quintino Francesco
Montresor, Alberto
Battiston, Federico
contents A wide variety of complex systems are characterized by interactions of different types involving varying numbers of units. Multiplex hypergraphs serve as a tool to describe such structures, capturing distinct types of higher-order interactions among a collection of units. In this work, we introduce a comprehensive set of measures to describe structural connectivity patterns in multiplex hypergraphs, considering scales from node and hyperedge levels to the system's mesoscale. We validate our measures with three real-world datasets: scientific co-authorship in physics, movie collaborations, and high school interactions. This validation reveals new collaboration patterns, identifies trends within and across movie subfields, and provides insights into daily interaction dynamics. Our framework aims to offer a more nuanced characterization of real-world systems marked by both multiplex and higher-order interactions.
format Preprint
id arxiv_https___arxiv_org_abs_2402_16782
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multiplex measures for higher-order networks
Lotito, Quintino Francesco
Montresor, Alberto
Battiston, Federico
Physics and Society
Social and Information Networks
A wide variety of complex systems are characterized by interactions of different types involving varying numbers of units. Multiplex hypergraphs serve as a tool to describe such structures, capturing distinct types of higher-order interactions among a collection of units. In this work, we introduce a comprehensive set of measures to describe structural connectivity patterns in multiplex hypergraphs, considering scales from node and hyperedge levels to the system's mesoscale. We validate our measures with three real-world datasets: scientific co-authorship in physics, movie collaborations, and high school interactions. This validation reveals new collaboration patterns, identifies trends within and across movie subfields, and provides insights into daily interaction dynamics. Our framework aims to offer a more nuanced characterization of real-world systems marked by both multiplex and higher-order interactions.
title Multiplex measures for higher-order networks
topic Physics and Society
Social and Information Networks
url https://arxiv.org/abs/2402.16782