Influence of behavioral adoption preference based on heterogeneous population on multiple weighted networks

Abstract

The study of behavioral propagation is taken more into account intimate heterogeneity on social networks. Meanwhile, with the development of information technology, people present a multiplicity of social ways, i.e., individuals normally receive or spread information on different social networks. More importantly, the behavioral preference of heterogenous population lacks in-depth research on the information propagation. Firstly, a multi-layer network with edge weighted distribution is considered. Then, we build a trapezoid-like and a triangle-like probability functions to represent individual continuous fashion trend (ICFT) and individual fashion passion trend (IFPT) behaviors separately, defining the adoption behavior preference of different population. Furthermore, a generalized edge-based compartmental theory including edge weight, ICFT and IFPT thresholds is proposed to reveal the behavioral preference. Through simulated experiments, decreasing the proportion of sensitive individuals can raise a hybrid phase transition, in which the final adoption size first increases continuously at the first critical value, and then increases discontinuously at the second critical value. Moreover, when the proportion of sensitive individuals is fixed, the strong adoption capacity of individuals can induce a discontinuous phase transition. Contrarily, the weak adoption capacity of individuals can induce a continuous phase transition. Finally, the edge weight and degree heterogeneity can alter the behavioral propagation on social networks.