A Multiplex Social Contagion Dynamics Model to Shape and Discriminate D2D Content Dissemination

Abstract

5G network technology is growing fast, thus the number of devices and the traffic are likely to pose impressive challenges. A new paradigm called 'Internet-of-People' (IoP) represents a valid approach to include the social aspect. Following an IoP perspective, we believe that the knowledge of social multiplex interactions and dynamics could drive more sustainable growth. By merging this with the Device-to-Device communication (D2D), we originate a new paradigm presented in this work. We propose a novel bio-inspired approach for quantifying the impact of the social multiplex structure on D2D contents' dissemination. Through rigorous mathematical modelling, we have shaped the D2D data dissemination process as a social contagion dynamics of two co-evolving spreading processes. We weigh the dynamic interactions by including the concepts of homophily and awareness. We have measured the effect of homophily, awareness and network heterogeneity on information diffusion. The bio-inspired mechanism is evaluated through a rigorous mathematical and algorithm analysis, and a meaningful simulation. We show that this mechanism is effective in tuning network awareness and alertness, breaking the 'echo chambers' effect. Through our model, we have defined and proposed the guidelines to discriminate the nature of the contents based on contents' dissemination.