Multiplex measures for higher-order networks
CoRR(2024)
摘要
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.
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