Complex contagions with social reinforcement from different layers and neighbors

Abstract

Researches about complex contagions on complex networks always neglect the reinforcement effect from different layers and neighbors simultaneously. In this paper we propose a non-Markovian model to describe complex contagions in which a susceptible node becoming adopted must take the social reinforcement from different layers and neighbors into consideration. Through extensive numerical simulations we find that the final adoption size will increase sharply with the information transmission probability at a large adoption threshold. In addition, for small values of adoption threshold, a few seeds could trigger a global contagion. However, there is a critical seed size below which the global contagion becomes impossible for large values of adoption threshold. Besides that, we develop an edge-based compartmental (EBC) theory to describe the proposed model, and it agrees well with numerical simulations.