Synchronous CODA opinion dynamics over social networks

The continuous opinion and discrete actions (CODA) model is a practical approach in the field of opinion dynamics to investigate how action observation can change an agent's opinion and decision in a community. However, the original CODA model takes only a fixed number of agents' action in the process of opinion updating when, in fact, the opinion of an individual in society will be influenced by a group of agents whose opinions are close to him/her. In this study, we develop a variant of the Hegelsman-Krause (HK) model that averages the opinions updated by the CODA rule after observing neighbors' actions. Using this approach, we investigate the influence of social imitation on collective opinion evolution and decision making. We use a social network generated by the Barabasi-Albert(BA) algorithm to represent a social group. Simulation results show that agents' opinions are more likely to be polarized after communicating with more neighbors. The impact of the level of biased-mindedness is also investigated. The results show that agents in a biased-minded social group could reach opinion stabilization faster than in a non-biased minded social group. In addition, the ratio of choice increases monotonically with the level of bias.