Opinion dynamics produced by the bounded confidence (BC) model [33] with and without noise.

<p>Populations consist of agents. Opinions vary between −250 and 250. Initial opinions are uniformly distributed. For visualization, the opinion scale is divided into 50 bins of equal size. Color coding indicates the relative frequency of agents in each bin. (A) Dynamics of the <i>BC-model without noise </i><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000959#pcbi.1000959-Hegselmann1" target="_blank">[33]</a> over 10 iterations (Each iteration consists of simulation events .). At each simulation event, one agent's opinion is replaced by the average opinion of those other agents who hold opinions within the focal agent's confidence interval (). For , one finds several homogeneous clusters, which stabilize when the distance between all clusters exceeds the confidence threshold . (B) Computer simulation of the same BC-model, but considering <i>interaction noise</i>. Agents that would otherwise not have been influential, now influence the focal agent's opinion with a probability of . This small noise is sufficient to eventually generate monoculture. (C) Simulation of the BC-model with opinion noise. After each opinion update, a random value drawn from a normal distribution with an average of zero and a standard deviation of (abbreviated by ) is added to the opinion. For weak opinion noise (), one cluster is formed, which carries out a random walk on the opinion scale. When the opinion noise is significantly increased (), there is still one big cluster, but many separated agents exist as well (cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000959#pcbi-1000959-g004" target="_blank">Fig. 4</a>). With even stronger opinion noise (), the opinion distribution becomes completely random.