Modeling and analyzing multiplatform coupled information propagation dynamics based on real social networks

Abstract

With the booming development of social media, multi-platform information propagation is becoming increasingly prevalent and intricate. Understanding how information spreads rapidly in the multi-platform network has emerged as a pivotal focus in current research. Particularly, information dynamic models are of significance for public opinion governance in the Omnimedia era. Incorporating the comprehensive influence of multiple factors, this paper proposes an emotion-driven Multi-platform Susceptible-Exposed-Propagating-Immune (MP-SEPI) propagation dynamic model based on real social networks. By applying the Monte Carlo (MC) method to implement numerical fitting and comparative analyses in the X-Weibo-TikTok coupled network, we demonstrate the superior performance of the proposed model in simulating multi-platform information diffusion, with values of $R^2$ being over 0.93. Furthermore, our analyses of influencing factors highlight the crucial role of the coupled network and reveal the mechanisms underlying information propagation and emotion evolution across diverse platforms. Therefore, the proposed modeling framework provides efficient strategies for public opinion guidance, regulation, and management, alleviating the burden of relevant agencies.