Multi-group Binary Choice with Social Interaction and a Random Communication Structure -- a Random Graph Approach
arXiv:1904.11890 · doi:10.1016/j.physa.2020.124735
Abstract
We construct and analyze a random graph model for discrete choice with social interaction and several groups of equal size. We concentrate on the case of two groups of equal sizes and we allow the interaction strength within a group to differ from the interaction strength between the two groups. Given that the resulting graph is sufficiently dense we show that, with probability one, the average decision in each of the two groups is the same as in the fully connected model. In particular, we show that there is a phase transition: If the interaction among a group and between the groups is strong enough the average decision per group will either be positive or negative and the decision of the two groups will be correlated. We also compute the free energy per particle in our model.
References in corpus (10)
- Majority Model on a network with communities
- Modularity produces small-world networks with dynamical time-scale separation
- Macroscopic limit of a bipartite Curie-Weiss model: a dynamical approach
- Belief propagation, robust reconstruction and optimal recovery of block models
- Scaling Limits for Multispecies Statistical Mechanics Mean-Field Models
- Phase of Ising spins on modular networks analogous to social polarization
- Fluctuation results for general block spin Ising models
- Optimal modularity for nucleation in network-organized Ising model
- On Penrose's square-root law and beyond
- Two Groups in a Curie-Weiss Model
Cited by in corpus (6)
- Fluctuations of the magnetization in the Block Potts Model
- Limit theorems for the cubic mean-field Ising model
- Local Central Limit Theorem for Multi-Group Curie-Weiss Models
- Models of Opinion Dynamics with Random Parametrisation
- Large deviations and a phase transition in the Block Spin Potts models
- Optimal Weights in a Two-Tier Voting System with Mean-Field Voters