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When the interactions of agents on a network are assumed to follow theDeffuant opinion dynamics model, the outcomes are known to depend on thestructure of the underlying network. This behavior cannot be captured byexisting mean-field approximations for the Deffuant model. In this paper, ageneralised mean-field approximation is derived that accounts for the effectsof network topology on Deffuant dynamics through the degree distribution orcommunity structure of the network. The accuracy of the approximation isexamined by comparison with large-scale Monte Carlo simulations on bothsynthetic and real-world networks.

A generalised mean-field approximation for the Deffuant opinion dynamics model on networks