Social contagion models on hypergraphs
Resumen: Our understanding of the dynamics of complex networked systems has increased significantly in the last two decades. However, most of our knowledge is built upon assuming pairwise relations among the system's components. This is often an oversimplification, for instance, in social interactions that occur frequently within groups. To overcome this limitation, here we study the dynamics of social contagion on hypergraphs. We develop an analytical framework and provide numerical results for arbitrary hypergraphs, which we also support with Monte Carlo simulations. Our analyses show that the model has a vast parameter space, with first- and second-order transitions, bistability, and hysteresis. Phenomenologically, we also extend the concept of latent heat to social contexts, which might help understanding oscillatory social behaviors. Our work unfolds the research line of higher-order models and the analytical treatment of hypergraphs, posing new questions and paving the way for modeling dynamical processes on higher-order structures.
Idioma: Inglés
DOI: 10.1103/PhysRevResearch.2.023032
Año: 2020
Publicado en: Physical Review Research 2, 2 (2020), 023032 [6 pp]
ISSN: 2643-1564

Financiación: info:eu-repo/grantAgreement/ES/DGA/E36-17R-FENOL
Financiación: info:eu-repo/grantAgreement/ES/MINECO-FEDER/FIS2017-87519-P
Tipo y forma: Article (Published version)
Área (Departamento): Área Física Teórica (Dpto. Física Teórica)
Exportado de SIDERAL (2023-06-21-15:03:29)


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 Notice créée le 2021-02-18, modifiée le 2023-06-22


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