A topic dissemination model based on hypernetwork

Individual characteristics, topic characteristics, and network structure factors are crucial for topic dissemination in social networks. However, existing models lack well integrated modelling of higher-order network structures with individual and topic characteristics. A new topic dissemination model based on hypernetwork (HSIRS for short) is proposed in this paper. We introduce an improved method of hypernetwork structure construction for online social networks. Each user's dissemination probability and re-entry probability are defined based on topic attractiveness, user sensitivity to different topics, individual activity, and hyperedge size effect. Our experiments on three simulated networks and three real social networks reveal that topic dissemination in hypernetworks is faster and more extensive compared to two existing models, characterized by pronounced fluctuations and sustained influence. The hyperedge structure facilitates rapid and extensive topic dissemination, but the effects eventually diminish. Topics with intense attractiveness and those linked to individuals with high hyperdegree values and activity levels greatly enhance dissemination rates and volatility.