Social reinforcement inducing discontinuous spreading in complex networks

Abstract

Social reinforcement originating from memory is the key characteristic of behavioral adoption in social contagion. Here, we introduce a non-Markovian susceptible-adopted-recovered (SAR) model to incorporate the memory mechanism. The higher the number of accumulated pieces of exposures an individual is exposed to, the larger is the probability that he/she will adopt the behavior. We observed that when the adopting probability per piece of behavioral information was smaller than a critical value, the final adoption size increased with the behavioral information probability discontinuously. Otherwise, the final adoption size increased with the behavioral information probability continuously. A physical understanding of the mechanism inducing discontinuous spreading was obtained through an edge-based compartment method, which also matched well with the simulation results.

Analysis of Influence of Behavioral Adoption Threshold Diversity on Multi-Layer Network

“…In this section, tests on the multi-layer ER network [ 32 ] and SF network [ 33 ] are used to simulate and assess the proposed model. The ER(ErdOs-Renyi) random network is an equal opportunity network model, i.e., given a certain number of nodes, the probability of inter connection with other surrounding nodes is the same.…”

Time‐Varying Spatial Memory Model and Its Impact on Virus Spreading

“…Especially in social networks, social reinforcement derived from memory is the main feature of social contagions. It is of great practical significance to add memory mechanism [33][34][35][36][37][38][39][40] in time-varying networks. Moreover, it is known that, in our daily life, we tend to have more contact with the people around us or those close to us, while there is little work to consider spatial factors on the basis of the activity model.…”