Joseph E. Uscinski

75 papers receiving 3.5k citations

Joseph E. Uscinski's Hit Papers

The Relationship Between Social Media Use and Beliefs in Conspiracy Theories and Misinformation 2021 · 157 citations
1570+4+8Years since publication250500750

Peers

Joseph E. Uscinski
Comparison fields: 5 of 122
  • Communication 1.1k
  • Health 710
  • Sociology and Political Science 3.2k
  • Cognitive Neuroscience 726
  • Artificial Intelligence 957
Replace Casey Klofstad with:
Casey Klofstad United States
Aleksandra Cichocka United Kingdom
Jon Roozenbeek United Kingdom
Adam Enders United States
Emily K. Vraga United States
Leticia Bode United States
Andrew M. Guess United States
Fabiana Zollo Italy
Hugo Mercier France
Emily Thorson United States
Joseph E. Uscinski relative to Casey Klofstad United States Casey Klofstad's profile →
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Countries citing papers authored by Joseph E. Uscinski

Since Specialization
Citations

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Fields of papers citing papers by Joseph E. Uscinski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joseph E. Uscinski. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joseph E. Uscinski. The network helps show where Joseph E. Uscinski may publish in the future.

Co-authors

The 25 scholars most cited alongside Joseph E. Uscinski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Joseph E. Uscinski Line = papers co-authored together Joseph E. Uscinski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Understanding Conspiracy Theories
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2019834
2
American Conspiracy Theories
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2014493
3
Why do people believe COVID-19 conspiracy theories?
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2020283
4
What Drives Conspiratorial Beliefs? The Role of Informational Cues and Predispositions
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2016282
5 2013168
6
The Relationship Between Social Media Use and Beliefs in Conspiracy Theories and Misinformation
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2021157
7 2020128
8
American Politics in Two Dimensions: Partisan and Ideological Identities versus Anti‐Establishment Orientations
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2021105
9 2017104
10 202289
11 202271
12 201769
13 201967
14 202154
15 202249
16 200949
17 201548
18 202246
19 202145
20 202241

About Joseph E. Uscinski

Joseph E. Uscinski is a scholar working on Sociology and Political Science, Communication, Artificial Intelligence, Political Science and International Relations and Cognitive Neuroscience, having authored 80 papers that have together received 3.7k indexed citations. Recurring topics across this work include Misinformation and Its Impacts (46 papers), Media Influence and Politics (24 papers), Hate Speech and Cyberbullying Detection (20 papers), Social Media and Politics (17 papers), Electoral Systems and Political Participation (15 papers), Psychology of Moral and Emotional Judgment (7 papers), Gender Politics and Representation (6 papers) and Political Influence and Corporate Strategies (6 papers). The work is most often cited by research in Communication (1.1k citations), Health (710 citations), Sociology and Political Science (3.2k citations), Cognitive Neuroscience (726 citations) and Artificial Intelligence (957 citations). Joseph E. Uscinski has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Casey Klofstad, Adam Enders, Joseph M. Parent, Türkay Salim Nefes, Robbie M. Sutton, Chee Siang Ang, Farzin Deravi, Aleksandra Cichocka, Karen M. Douglas and Matthew Atkinson. Their work appears in journals such as PS Political Science & Politics, Social Science Quarterly, Research & Politics, Scientific Reports and Critical Review.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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