Influential groups for seeding and sustaining nonlinear contagion in heterogeneous hypergraphs

@article{StOnge2022InfluentialGF,
  title={Influential groups for seeding and sustaining nonlinear contagion in heterogeneous hypergraphs},
  author={Guillaume St‐Onge and Iacopo Iacopini and Vito Latora and Alain Barrat and Giovanni Petri and Antoine Allard and Laurent H'ebert-Dufresne},
  journal={Communications Physics},
  year={2022}
}
Contagion phenomena are often the results of multibody interactions—such as superspreading events or social reinforcement—describable as hypergraphs. We develop an approximate master equation framework to study contagions on hypergraphs with a heterogeneous structure in terms of group size (hyperedge cardinality) and of node membership (hyperdegree). By mapping multibody interactions to nonlinear infection rates, we demonstrate the influence of large groups in two ways. First, we characterize… 
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References

SHOWING 1-10 OF 84 REFERENCES
The physics of higher-order interactions in complex systems
TLDR
Evidence from neural systems shows that higher-order effects are present and important both statistically10–12 and topologically13,14, and there is also evidence to suggest that such higher- order signatures might in some cases be redundant.
Vanishing size of critical mass for tipping points in social convention
TLDR
This poster presents a probabilistic procedure for estimating the total number of components in a Response to the Response of the immune system to disease.
Social contagion on higher-order structures
TLDR
The results highlight the rich phenomenology brought by taking into account higher-order contagion effects: both continuous and discontinuous transitions are observed, and critical mass effects emerge.
Universal Nonlinear Infection Kernel from Heterogeneous Exposure on Higher-Order Networks.
TLDR
It is found that combining heterogeneous exposure with the concept of minimal infective dose induces a universal nonlinear relationship between infected contacts and infection risk.
Node and Edge Eigenvector Centrality for Hypergraphs
TLDR
This work motivate, define and analyze a class of spectral centrality measures for identifying important nodes and hyperedges in hypergraphs, generalizing existing network science concepts and illustrating the measures on realistic data sets.
Network clique cover approximation to analyze complex contagions through group interactions
TLDR
The authors propose a mathematical framework able to accurately characterize the phase diagram of these contagion processes in social higher-order networks, focusing on interaction structures represented as simplicial complexes.
Magnetotransport of dirty-limit van Hove singularity quasiparticles
Tuning of electronic density-of-states singularities is a common route to unconventional metal physics. Conceptually, van Hove singularities are realized only in clean two-dimensional systems. Little
Temporal properties of higher-order interactions in social networks
TLDR
This work investigates the higher-order organizations of temporal social networks by analyzing five publicly available datasets collected in different social settings and finds that higher- order interactions are ubiquitous and, similarly to their pairwise counterparts, characterized by heterogeneous dynamics.
The effect of heterogeneity on hypergraph contagion models
TLDR
A hyperdegree-based mean-field description of the dynamics of the susceptible–infected–susceptible model on hypergraphs is presented and it is found that explosive transitions can be suppressed by heterogeneity in the link degree distribution when links and triangles are chosen independently or when link and triangle connections are positively correlated when compared to the uncorrelated case.
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