This paper first introduces the concept of information diffusion in social networks and its characteristics, then clarifies the objectives and scope of social network data collection. Data related to user attention and follower counts were obtained through APIs, web scraping programs, and open data. To understand the impact of the complexity and uncertainty of information diffusion in social networks on the system, a dynamical model of information diffusion in social media networks under uncertain conditions was constructed based on system dynamics theory. Finally, the model is used to analyze the evolutionary trends of information diffusion in social networks and the moderating effects on older adults’ social participation. The results show that there are strong interactive relationships between various variables in the dynamical system and information diffusion in social networks. Through the dynamical model, it is found that the evolution of numerical information characteristics reveals significant fluctuations in the network propagation speed of information within the first hour, which is related to the control capabilities of news media over information. Additionally, within the first hour, 72.72% of news media information dissemination networks had an average in-degree >1, under which conditions the social participation of the elderly was higher. Increasing the social participation of the elderly under conditions of high social network information diffusion can help maintain their cognitive function stability, playing an important role in their physical health.
