An opinion evolution model for online social networks considering higher-order interactions.

ABSTRACT: As the number of users in online social networks increases, the diffusion of information and users' opinions on events become more complex, making it difficult for traditional complex networks to accurately capture their characteristics and patterns. To address this, this paper proposes an online social network opinion evolution model that accounts for higher-order interactions. The model incorporates the higher-order effects of group interactions and introduces the acceptance, non-commitment, and rejection dimensions from social judgment theory. Different approaches, such as acceptance, neutrality, and contrastive rejection, are adopted when individuals exchange opinions with their neighbors. Through numerical simulations, it is shown that higher-order interactions significantly enhance t

SUBMITTER: Liu Q 

PROVIDER: S-EPMC12002442 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature