Polarization in Geometric Opinion Dynamics

19Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In light of increasing recent attention to political polarization, understanding how polarization can arise poses an important theoretical question. While more classical models of opinion dynamics seem poorly equipped to study this phenomenon, a recent novel approach by Hazla, Jin, Mossel, and Ramnarayan (HJMR) [19] proposes a simple geometric model of opinion evolution that provably exhibits strong polarization in specialized cases. Moreover, polarization arises quite organically in their model: in each time step, each agent updates opinions ccording to their correlation/response with an issue drawn at random. However, their techniques do not seem to extend beyond a set of special cases they identify, which benefit from fragile symmetry or contractiveness assumptions, leaving open how general this phenomenon really is. In this paper, we further the study of polarization in related geometric models. We show that the exact form of polarization in such models is quite nuanced: even when strong polarization does not hold, it is possible for weaker notions of polarization to nonetheless attain. We provide a concrete example where weak polarization holds, but strong polarization provably fails. However, we show that strong polarization provably holds in many variants of the HJMR model, which are also robust to a wider array of distributions of random issues this suggests that the form of polarization introduced by HJMR is more universal than suggested by their special cases.We also show that the weaker notions connect more readily to the theory of Markov chains on general state spaces.

Cite

CITATION STYLE

APA

Gaitonde, J., Kleinberg, J., & Tardos, E. (2021). Polarization in Geometric Opinion Dynamics. In EC 2021 - Proceedings of the 22nd ACM Conference on Economics and Computation (pp. 499–519). Association for Computing Machinery, Inc. https://doi.org/10.1145/3465456.3467633

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free