Abstract: Heterogeneous networks can effectively model various complex real-world application scenarios. Based on the diversity of individuals on the Weibo platform, this paper proposes a heterogeneous Weibo information hypernetwork model that incorporates individual attributes. In this model, users and topics are treated as two types of heterogeneous nodes, while user participation in topic discussions forms hyperedges, resulting in a scale-free heterogeneous hypernetwork model. Building on this framework, the SEIR propagation model is integrated to quantitatively analyze the individual attributes of heterogeneous nodes. Meta-path methods are employed to design calculation approaches for user influence, infection rate, and immunity rate. Furthermore, simulation experiments are conducted to analyze the dynamic processes and patterns of information dissemination across different network structures, investigating the impacts of user influence, confidence levels, interest values, and information timeliness on the dissemination process. Additionally, the validity and accuracy of the model are verified using the case study of the "Japan Nuclear Wastewater Discharge" incident. The results demonstrate that this model effectively captures the trends and processes of information dissemination in real social networks. This work provides valuable insights for research on the model construction of heterogeneous hypernetworks and hypernetwork-based information dissemination, contributing to a deeper understanding of more complex and diverse information propagation mechanisms.