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Research Articles

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

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Pages 340-361 | Received 20 Jan 2023, Accepted 20 Feb 2024, Published online: 06 May 2024
 

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.

Disclosure statement

No potential conflict of interest was reported by the author(s).