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The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes.

Yuanzhao Zhang¹, Maxime Lucas^2,3, Federico Battiston⁴

¹Santa Fe Institute, Santa Fe, NM, USA. yzhang@santafe.edu.

Nature Communications

|March 24, 2023

Summary

This summary is machine-generated.

Higher-order networks reveal that how we represent complex systems, like hypergraphs or simplicial complexes, significantly impacts their collective behavior. The chosen representation, not just the interactions, affects dynamics such as synchronization.

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Area of Science:

Complex systems science
Network science
Mathematical physics

Background:

Higher-order networks model systems beyond pairwise interactions.
Representations include simplicial complexes and hypergraphs.
Representation choice has often been based on convenience.

Purpose of the Study:

To demonstrate the representation-dependent effects of higher-order interactions.
To analyze how different network representations influence collective dynamics.
To provide theoretical insights into synchronization in higher-order networks.

Main Methods:

Using synchronization as a case study for collective dynamics.
Comparing synchronization behavior in hypergraph and simplicial complex representations.
Developing theoretical links between network structure and synchronizability.

Main Results:

Higher-order interactions enhance synchronization in hypergraphs.
Higher-order interactions inhibit synchronization in simplicial complexes.
Synchronizability correlates with degree heterogeneity and cross-order degree correlations.

Conclusions:

The choice of network representation critically impacts collective dynamics.
Appropriate representation selection is crucial for studying systems with nonpairwise interactions.
Findings have implications for modeling contagion, diffusion, and other processes.