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Social interactions influence people's opinions. In some situations, these interactions result in a consensus opinion; in others, they result in opinion fragmentation and the formation of different opinion groups in the form of "echo chambers". Consider a social network of individuals, who hold continuous-valued scalar opinions and change their opinions when they interact with each other. In such an opinion model, it is common for an opinion-update rule to depend on the mean opinion of interacting individuals. However, we consider an alternative update rule - which may be more realistic in some situations - that instead depends on a weighted median opinion of interacting individuals. Through numerical simulations of our opinion model, we investigate how the limit opinion distribution depends on network structure. For configuration-model networks, we also derive a mean-field approximation for the asymptotic dynamics of the opinion distribution when there are infinitely many individuals in a network.
Mohr et al. (Tue,) studied this question.
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