2007/01/31 by V. Schwammle, Veit Schwämmle, M. C. Gonzalez +7 · 2 citations
Mathematics · Physics and Astronomy · Social Sciences · #Artificial intelligence #Complex Network Analysis Techniques #Complex network #Comprehension #Computer science #Economics #Evolutionary Game Theory and Cooperation #Herding #Mathematics #Multi-agent system #Network topology #Noise (video) #Nonlinear system #Opinion Dynamics and Social Influence #Opinion leadership #Order (exchange) #Physics #Political science #Public relations #Statistical physics #Topology (electrical circuits) #physics.comp-ph #physics.soc-ph
paper · pdf · doi:10.1103/physreve.75.066108
published as Phys. Rev. E 75, 066108 (2007) · 6 pages, 8 figures
openalex publication_date 2007/06/25 · arxiv created 2007/07/02 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Understanding how opinions spread through a community or how consensus emerges in noisy environments can have a significant impact on our comprehension of social relations among individuals. In this work a model for the dynamics of opinion formation is introduced. The model is based on a nonlinear interaction between opinion vectors of agents plus a stochastic variable to account for the effect of noise in the way the agents communicate. The dynamics presented is able to generate rich dynamical patterns of interacting groups or clusters of agents with the same opinion without a leader or centralized control. Our results show that by increasing the intensity of noise, the system goes from consensus to a disordered state. Depending on the number of competing opinions and the details of the network of interactions, the system displays a first- or a second-order transition. We compare the behavior of different topologies of interactions: one-dimensional chains, and annealed and complex networks.