  We study the dynamics of public opinion in a model in which agents change
their opinions as a result of random binary encounters if the opinion
difference is below their individual thresholds that evolve over time. We
ground these thresholds in a simple individual cost-benefit analysis with
linear benefits of diversity and quadratic communication costs. We clarify and
deepen the results of earlier continuous-opinion dynamics models (Deffuant et
al., Adv Complex Systems 2000; Weisbuch et al., Complexity 2002) and establish
several new results regarding the patterns of opinions in the asymptotic state
and the cluster formation time.
