Modeling public opinion dissemination in a multilayer network with SEIR model based on real social networks

Due to the complexity of social relationships, Internet users are active in multiple social networks and receive or release information in various ways and channels. Therefore, the spread of public opinion is not limited to a closed single network. Considering the structural characteristics of WeChat, Weibo and Tiktok, we built a multi-layer network based on the complex network theory. Based on the environmental and personal factors, the calculation methods of transmission rate and immunity rate is proposed. The trends of information transmission in the multi-layer network is simulated through an improved SEIR model. Through simulation, the differences of information transmission between multi-layer networks and single-layer networks are explored, and the impacts of network structure, coupling strength between layers and interlayer connection mode on information transmission are studied. More than 76,000 tweets from 7 events on Weibo are collected to verify the effectiveness of the model and explore the dissemination trends of actual public opinions. Through the research, it is found that (1) the public opinion transmission efficiency of multi-layer network is higher, the scale is larger, and the time is longer. (2) Compared with Weibo and Tiktok, the information transmission in WeChat is more efficient and lasts longer, and promotes the information transmission in the other two networks. (3) With the increase of coupling strength between layers, the efficiency of information transmission becomes higher and the scale becomes larger. This study provides new ideas for the research of public opinion dissemination, and helps relevant departments to correctly guide public opinion.