Information Propagation Influenced by Overlimit Psychology on Weighted Networks

In psychology, there exists a phenomenon known as the overlimit effect, where individuals may experience a decrease or even a complete loss of original interests due to an excess of external information. We refer to similar manifestations observed in real scenarios as overlimit psychological behavior. To explore the impact of overlimit psychological behaviors on information propagation in social networks, a probability adoption function is first developed to model overlimit psychological behaviors, and individuals are categorized into two groups based on their susceptibility to the overlimit effect: those with strong overlimit psychology(SOP) and those with weak overlimit psychology(WOP). Subsequently, a monolayer network model incorporating edge weight distribution is proposed. Theoretical analysis and experimental simulations are finally conducted by using edge-based compartmental theory. The final results reveal phase transitions during the propagation process. When the proportion of WOP individuals is relatively high, the spreading range shows a firstorder discontinuous growth. As SOP individuals becomes dominant, the growth of the spreading scale transitions to a second-order continuous growth. Moreover, the variation in the proportions of the two groups also affects the speed of information outbreaks and the final propagation scale. Additionally, different edge weight distributions alter the speed of information outbreaks, and diverse degree distribution heterogeneity influences the final spreading range and phase transition. Ultimately, all theoretical analysis aligns with simulation results.