Abstract
We here discuss a model of continuous opinion dynamics in which agents adjust continuous opinions as a result of random binary encounters whenever their difference in opinion is below a given threshold. We concentrate on the version of the model in the presence of few extremists which might drive the dynamics to generalized extremism. A network version of the dynamics is presented here, and its results are compared to those previously obtained for the full-mixing case. The same dynamical regimes are observed, but in rather different parameter regions. We here show that the combination of meso-scale features resulting from the first interaction steps determines the asymptotic state of the dynamics.
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