Pairwise comparison

Quantum mechanics

Complex system

Statistics

Emotional contagion

Social psychology

Social dynamics

Theoretical computer science

Stability (learning theory)

Operating system

Economics

Computer science

Statistical physics

Physics

Hysteresis

Psychology

Mathematics

Sociology

Condensed matter physics

Artificial intelligence

Monte Carlo method

Finance

Bistability

Order (exchange)

Space (punctuation)

Machine learning

Physical Review Research

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, bi-stability, 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 these networks.

Social contagion models on hypergraphs