Influence, inertia, and independence: a diffusion model for temporal social networks

Abstract

In this work, we propose a diffusion model for temporal social networks and relate it to other well-known models of social influence by investigating its formal properties. The model establishes dyadic influence weights based on two antagonistic components: the susceptibility to be influenced (or, conversely, inertia with respect to the status quo) and becoming independent of prior influence. The proposed model generalizes the Friedkin-Johnsen model by the inertia with respect to the current influence relationships. We show that this generalization is an over-parameterization for static but not for dynamic influence networks. These findings suggest that the model at hand expands the set of existing social influence models in a non-trivial way.