关键词: 跨社交平台, 耦合网络, 舆情传播, 传染病模型, 层间耦合程度, 层间耦合模式

Abstract:

[Purpose/Significance] With the advancement of communication technology and the popularization of smart mobile devices, social media platforms have developed rapidly. The increased exchange of information via social media platforms has increased the complexity and the spread of public opinion. Understanding the topological structure of information dissemination networks across platforms and the mechanisms of public opinion dissemination on them is of great significant guiding importance for predicting trends in online public opinion and formulating guiding strategies. [Methods/Processes] Based on the SEIR model of infectious diseases, a model of the spread of public opinion on cross-social platform coupled networks was constructed. Using the Monte Carlo simulation method, the experiment explored the effect of the degree of coupling between users and the type of coupling between platforms on the speed and extent of the spread of public opinion, revealing the laws of the spread of public opinion in cross-social platform coupled networks. [ [Results/Conclusions] The simulation results indicate that, compared to single-layer networks, the inter-layer edges formed by users across platforms significantly promote the spread of public opinion. As the degree of inter-layer coupling in the network increases, the speed of public opinion diffusion accelerates and the extent of diffusion increases. For inter-layer coupling modes, homophily links are more conducive to the spread of public opinion information than heterophily links. The results of this study provide valuable guidance for public opinion management. In a networked environment, government departments should disseminate accurate and authoritative information promptly through a variety of channels to gain the upper hand in public opinion. Given the positive correlation between inter-layer coupling and the speed at which public opinion spreads, it is crucial to closely monitor other platforms with a high degree of user overlap with the current one, and to accurately understand key data such as user overlap, activity levels, and differentiation between platforms. This will help to identify key users with high influence and activity, and enable more targeted, personalized guidance strategies. For platforms with a high degree of user assortative connectivity, the emergency response to public opinion should be enhanced. Conversely, platforms with a high degree of user disassortative connectivity should implement more stringent information filtering and response measures. The model constructed in this paper can simulate the basic structure of real coupled social networks and the process of spreading public opinion to some extent, but there are still shortcomings. Future research can introduce more factors, such as user behavior characteristics and content attributes, to construct a more refined public opinion diffusion model, thereby enhancing the model's capability to describe the real-world mechanisms of public opinion information diffusion.

Key words: cross-social platform, coupled network, public opinion propagation, infectious disease model, degree of inter-layer coupling, inter-layer coupling pattern