Cited by 109Electoral Systems and Political ParticipationOpinion Dynamics and Social InfluenceSocial Media and Politics

A sign of the times? Weak and strong polarization in the U.S. Congress, 1973–2016

Neal, Zachary P.·2020·Social Networks

Integrity signals

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Crossref · 10.1016/j.socnet.2018.07.007

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2 of 2 references verified0 citation errors · 0 not checkable

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  • There is a strong consensus among scholars of politics in the USA that liberal and conservative political elites have grown increasingly polarized over the past few decades.

    “For example, there is a strong consensus among scholars of politics in the USA that liberal and conservative political elites (including members of Congress, party activists, donors and judicial appointees) have grown increasingly polarized over the past few decades27–34.”

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Authors
Neal, Z. P.
Affiliations
Michigan State University (US)
Corresponding author
Neal, Zachary P.
Venue
Social Networks
Publisher
Elsevier BV
Published
2020-01
Volume
60
Pages
103-112
ISSN
0378-8733 (ISSN-L)
OpenAlex
W2894413073
Cited by
109
References
2
Citations by year
2026: 3 · 2025: 14 · 2024: 14 · 2023: 32 · 2022: 20 · 2021: 15 · 2020: 8 · 2019: 3
FWCI
28.29
Type
journal article
Language
en
Open access
closed
Locations
Social Networks (publishedVersion)
Topics
  • Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
  • Social Sciences › Communication › Social Media and Politics
Keywords
political polarization, United States Congress, intergroup relations, signed networks, House of Representatives, Senate, political affiliation, majority party, legislative networks

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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