Information propagation characteristic by individual hesitant-common trend on weighted network

Within the context of contemporary society, the propagation of information is often subject to the influence of inter-individual connectivity, and individuals may exhibit divergent receptive attitudes towards identical information, a phenomenon denoted as the Hesitant-Common (HECO) trait. In light of this, the present study initially constructs a propagation network model devoid of correlation configurations to investigate the HECO characteristics within weighted social networks. Subsequently, the study employs a theoretical framework for edge partitioning, predicated on edge weights and HECO traits, to quantitatively analyze the mechanisms of individual information dissemination. Theoretical analyses and simulation outcomes consistently demonstrate that an augmentation in the proportion of common individuals facilitates both the diffusion and adoption of information. Concurrently, a phase transition crossover is observed, wherein the growth pattern of the ultimate adoption range, denoted as R(∞), transitions from a first-order discontinuous phase transition to a second-order continuous phase transition as the proportion of common individuals increases. An escalation in the weight distribution exponent is found to enhance information propagation. Furthermore, a reduction in the heterogeneity of degree distribution is conducive to the spread of information. Conversely, an increase in degree distribution heterogeneity and a diminution in the collective decision-making capacity can both exert inhibitory effects on the propagation of information.