
Open access
Date
2020Type
- Journal Article
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. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000448243Publication status
publishedExternal links
Journal / series
EPJ Data ScienceVolume
Pages / Article No.
Publisher
SpringerSubject
Political polarization; Markov chains; Bayesian inferenceOrganisational unit
03729 - Gersbach, Hans / Gersbach, Hans
03571 - Sigrist, Manfred / Sigrist, Manfred
More
Show all metadata