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.

许多民主社会在政治上变得更加两极分化，美国就是主要的例子。这种现象的起源仍然没有得到很好的理解，也存在争议。为了深入了解政治两极分化的某些机制，我们开发了一个数学框架，并采用贝叶斯马尔可夫链蒙特卡洛 (MCMC) 和信息论概念来分析皮尤研究中心从 1994 年收集的关于政治两极分化的经验数据到 2017 年。我们的框架可以捕捉到美国公众中倾向于民主党和共和党的部分两极分化的演变，并让我们能够确定其驱动因素。我们的实证和定量证据表明，美国的政治两极分化主要是由民主党强大的政治/文化倡议推动的。