Frederic Amblard, Guillaume Deffuant, Jean Nadal, Gérard Weisbuch

Paper #: 01-11-072

We present a model of 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. High thresholds yield convergence of opinions towards an average opinion, whereas low thresholds result in several opinion clusters. The model is further generalized to network interactions, threshold heterogeneity, adaptive thresholds and binary strings of opinions.

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