Schwämmle V, González M C, Moreira A A, Andrade J S, Herrmann H J
Departamento de Física, Universidade Federal do Ceará, 60451-970 Fortaleza, Ceará, Brazil.
Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Jun;75(6 Pt 2):066108. doi: 10.1103/PhysRevE.75.066108. Epub 2007 Jun 25.
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.
理解观点如何在一个群体中传播，或者在嘈杂环境中如何达成共识，可能会对我们理解个体之间的社会关系产生重大影响。在这项工作中，引入了一个观点形成动力学模型。该模型基于主体观点向量之间的非线性相互作用，再加上一个随机变量，以说明主体交流方式中噪声的影响。所呈现的动力学能够在没有领导者或集中控制的情况下，生成具有相同观点的相互作用群体或集群的丰富动力学模式。我们的结果表明，通过增加噪声强度，系统会从共识状态转变为无序状态。根据竞争观点的数量和相互作用网络的细节，系统会显示一阶或二阶转变。我们比较了不同相互作用拓扑结构的行为：一维链、退火网络和复杂网络。
