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巨大分歧:美国公众两极分化的驱动因素

The great divide: drivers of polarization in the US public.

作者信息

Böttcher Lucas, Gersbach Hans

机构信息

Department of Computational Medicine, UCLA, Life Sciences Bldg., Box 951766, Los Angeles, US.

Institute for Theoretical Physics, ETH Zurich, Wolfgang-Pauli-Str. 27, 8093 Zurich, Switzerland.

出版信息

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

DOI:10.1140/epjds/s13688-020-00249-4
PMID:33134015
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7591448/
Abstract

UNLABELLED

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.

摘要

未标注

许多民主社会在政治上变得更加两极分化,美国是主要例子。这一现象的起源仍未得到很好的理解,且存在争议。为深入了解政治两极分化背后的一些机制,我们建立了一个数学框架,并运用贝叶斯马尔可夫链蒙特卡罗(MCMC)和信息论概念来分析皮尤研究中心在1994年至2017年期间收集的关于政治两极分化的实证数据。我们的框架能够捕捉美国公众中倾向民主党和共和党的群体中两极分化的演变,并使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由民主党强大的政治/文化倡议推动。

电子补充材料

本文的在线版本(10.1140/epjds/s13688-020-00249-4)包含补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/a499a586e2c6/13688_2020_249_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/1a781ebd7e1f/13688_2020_249_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/b1acd07e22fe/13688_2020_249_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/0510609b1787/13688_2020_249_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/677f105600a8/13688_2020_249_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/99c57e50df55/13688_2020_249_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/a499a586e2c6/13688_2020_249_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/1a781ebd7e1f/13688_2020_249_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/b1acd07e22fe/13688_2020_249_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/0510609b1787/13688_2020_249_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/677f105600a8/13688_2020_249_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/99c57e50df55/13688_2020_249_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb9/7591448/a499a586e2c6/13688_2020_249_Fig6_HTML.jpg

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本文引用的文献

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2
Clout, activists and budget: The road to presidency.影响力、活动家和预算:通往总统宝座之路。
PLoS One. 2018 Mar 1;13(3):e0193199. doi: 10.1371/journal.pone.0193199. eCollection 2018.
3
Greater Internet use is not associated with faster growth in political polarization among US demographic groups.互联网使用的增加与美国人口群体中政治分化的快速增长无关。
Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):10612-10617. doi: 10.1073/pnas.1706588114. Epub 2017 Sep 19.
4
Temporal dynamics of online petitions.在线请愿的时间动态。
PLoS One. 2017 May 18;12(5):e0178062. doi: 10.1371/journal.pone.0178062. eCollection 2017.
5
Critical Behaviors in Contagion Dynamics.传染病动力学中的关键行为
Phys Rev Lett. 2017 Feb 24;118(8):088301. doi: 10.1103/PhysRevLett.118.088301. Epub 2017 Feb 23.
6
Failure and recovery in dynamical networks.动力网络中的故障与恢复。
Sci Rep. 2017 Feb 3;7:41729. doi: 10.1038/srep41729.
7
Modeling confirmation bias and polarization.建模确认偏误和极化。
Sci Rep. 2017 Jan 11;7:40391. doi: 10.1038/srep40391.
8
Comparing vector–host and SIR models for dengue transmission.比较登革热传播的向量-宿主和 SIR 模型。
Math Biosci. 2013 Dec;246(2):252-9.
9
Biased assimilation, homophily, and the dynamics of polarization.偏见同化、同质性和极化的动态。
Proc Natl Acad Sci U S A. 2013 Apr 9;110(15):5791-6. doi: 10.1073/pnas.1217220110. Epub 2013 Mar 27.
10
Structural diversity in social contagion.社会传播中的结构多样性。
Proc Natl Acad Sci U S A. 2012 Apr 17;109(16):5962-6. doi: 10.1073/pnas.1116502109. Epub 2012 Apr 2.