The great divide: drivers of polarization in the US public

Lucas Böttcher; Hans Gersbach

doi:10.1140/epjds/s13688-020-00249-4

The great divide: drivers of polarization in the US public

EPJ Data Sci. 2020;9(1):32. doi: 10.1140/epjds/s13688-020-00249-4. Epub 2020 Oct 28.

Authors

Lucas Böttcher^{1

2

3}, Hans Gersbach³

Affiliations

¹ Department of Computational Medicine, UCLA, Life Sciences Bldg., Box 951766, Los Angeles, US.
² Institute for Theoretical Physics, ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland.
³ Center of Economic Research, ETH Zurich, Zürichbergstrasse 18, 8092 Zurich, Switzerland.

Abstract

Many democratic societies have become more politically polarized, with the U.S. being the main example. The origins of this phenomenon are still not well-understood and subject to debate. To provide insight into some of the mechanisms underlying political polarization, we develop a mathematical framework and employ Bayesian Markov chain Monte-Carlo (MCMC) and information-theoretic concepts to analyze empirical data on political polarization that has been collected by Pew Research Center from 1994 to 2017. Our framework can capture the evolution of polarization in the Democratic- and Republican-leaning segments of the U.S. public and allows us to identify its drivers. Our empirical and quantitative evidence suggests that political polarization in the U.S. is mainly driven by strong political/cultural initiatives in the Democratic party.

Electronic supplementary material: The online version of this article (10.1140/epjds/s13688-020-00249-4) contains supplementary material.

Keywords: Bayesian inference; Markov chains; Political polarization.