The Krause-Hegselmann Consensus Model with Discrete Opinions

Abstract

The consensus model of Krause and Hegselmann can be naturally extended to the case in which opinions are integer instead of real numbers. Our algorithm is much faster than the original version and thus more suitable for applications. For the case of a society in which everybody can talk to everybody else, we find that the chance to reach consensus is much higher as compared to other models; if the number of possible opinions Q<=7, in fact, consensus is always reached, which might explain the stability of political coalitions with more than three or four parties. For Q>7 the number S of surviving opinions is approximately the same independently of the size N of the population, as long as Q<N. We considered as well the more realistic case of a society structured like a Barabasi-Albert network; here the consensus threshold depends on the outdegree of the nodes and we find a simple scaling law for S, as observed for the discretized Deffuant model.

12 pages, 6 figures

Cited by in corpus (8)

• Vector Opinion Dynamics in a Bounded Confidence Consensus Model
• On the Consensus Threshold for the Opinion Dynamics of Krause-Hegselmann
• The bridges to consensus: Network effects in a bounded confidence opinion dynamics model
• Diffusion in scale-free networks with annealed disorder
• Communication regimes in opinion dynamics: Changing the number of communicating agents
• When open mindedness hinders consensus
• Dynamical phase transitions in Hegselmann-Krause model of opinion dynamics and consensus
• On the Hegselmann-Krause conjecture in opinion dynamics