Nicholas Landry, University of Virginia

Abstract

The division of a social group into subgroups with opposing opinions, which we refer to as opinion disparity, is a prevalent phenomenon in society. This phenomenon has been modeled by including mechanisms such as opinion homophily, bounded confidence interactions, and social reinforcement mechanisms. We present a complementary mechanism for the formation of opinion disparity based on higher-order interactions, i.e., simultaneous interactions between multiple agents. We present an extension of the planted partition model for uniform hypergraphs as a simple model of community structure, and we consider the hypergraph Susceptible-Infected-Susceptible (SIS) model on a hypergraph with two communities where the binary ideology can spread via links (pairwise interactions) and triangles (three-way interactions). We approximate this contagion process with a mean-field model and find that for strong enough community structure, the two communities can hold very different average opinions. We determine the regimes of structural and infectious parameters for which this opinion disparity can exist, and we find that the existence of these disparities is much more sensitive to the triangle community structure than to the link community structure. Lastly, we discuss the algorithmic considerations when numerically validating these analytical results. To this end, we present the CompleX Group Interactions (XGI) software package and demonstrate how it can be used to enable research on higher-order networks.

Speaker Bio:

Nicholas Landry is an assistant professor of biology at the University of Virginia. He studies how the structure of networks and groups affect the spread of diseases, information, and ideology. He accomplishes this through dynamical models, Bayesian inference, and open-source software. Nicholas is one of the founding members of the XGI project, a software package for analyzing, modeling, and visualizing higher-order networks. Prior to joining UVA, he completed a Ph.D. in Applied Mathematics at the University of Colorado Boulder and then was a postdoctoral research fellow at the Translational Global Infectious Disease Research Center (TGIR) in the Vermont Complex Systems Center at the University of Vermont.