Opinion evolution model based on coordination between information networks and social networks

Opinion dynamics is a popular process to model the evolution of group opinions, which provides technical support for public opinion-related decision issues. However, most existing works focus on studying the opinions evolution in social networks while overlooking the influence of information networks. Besides, in social networks, the rules for filtering authoritative individuals only consider public authorities, failing to consider the individuals' heterogeneity. To tackle the above issues, we propose an opinion evolution model based on collaboration between information networks and social networks (ISOE). Specifically, we first update the individual's opinion by judging the quality of the information obtained by the individual in the information network; then, we filter the trusted neighbor set for the current individual by quantifying the attributes of the individual's authority and closeness and update the individual's opinion after comprehensive weighting analysis of the trusted neighbor set; finally, we conduct information exchange between the social and information networks with the inter-layer information transfer mechanism. The above three steps are repeated until the group opinions reach a steady state. Extensive experiments have been carried out to prove the performance superiority of our proposed model.