Kyle L. Saunders

4.2k total citations · 2 hit papers
30 papers, 2.6k citations indexed

About

Kyle L. Saunders is a scholar working on Political Science and International Relations, Sociology and Political Science and Communication. According to data from OpenAlex, Kyle L. Saunders has authored 30 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Political Science and International Relations, 16 papers in Sociology and Political Science and 13 papers in Communication. Recurrent topics in Kyle L. Saunders's work include Electoral Systems and Political Participation (20 papers), Social Media and Politics (12 papers) and Misinformation and Its Impacts (5 papers). Kyle L. Saunders is often cited by papers focused on Electoral Systems and Political Participation (20 papers), Social Media and Politics (12 papers) and Misinformation and Its Impacts (5 papers). Kyle L. Saunders collaborates with scholars based in United States, United Kingdom and Denmark. Kyle L. Saunders's co-authors include Alan I. Abramowitz, Joanne M. Miller, Christina E. Farhart, Lonna Rae Atkeson, Susan M. Opp, Gregory D. Schmidt, Thad E. Hall, Joseph E. Uscinski, Hugo Drochon and Adam Enders and has published in prestigious journals such as Scientific Reports, American Journal of Political Science and The Journal of Politics.

In The Last Decade

Kyle L. Saunders

26 papers receiving 2.4k citations

Hit Papers

Is Polarization a Myth? 2008 2026 2014 2020 2008 2015 250 500 750

Peers

Kyle L. Saunders
Comparison fields: 5 of 107
  • Sociology and Political Science 1.5k
  • Political Science and International Relations 1.5k
  • Communication 898
  • Gender Studies 358
  • Strategy and Management 276
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Citations per field, relative to Kyle L. Saunders
Kyle L. Saunders · 1×
Citations per year, relative to Kyle L. Saunders
Kyle L. Saunders · 1×

Countries citing papers authored by Kyle L. Saunders

Since Specialization
Citations

This map shows the geographic impact of Kyle L. Saunders's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kyle L. Saunders with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle L. Saunders more than expected).

Fields of papers citing papers by Kyle L. Saunders

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyle L. Saunders. 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 Kyle L. Saunders. The network helps show where Kyle L. Saunders may publish in the future.

Co-authorship network of co-authors of Kyle L. Saunders

This figure shows the co-authorship network connecting the top 25 collaborators of Kyle L. Saunders. A scholar is included among the top collaborators of Kyle L. Saunders based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kyle L. Saunders. Kyle L. Saunders is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 7
2 0
3 0
4 2
5 5
6 71
7 2
8 15
9 2
10 33
11
Why Donald Trump’s election may mean we see more liberal conspiracy theories about the government
0
12
Conspiracy Endorsement as Motivated Reasoning: The Moderating Roles of Political Knowledge and Trust breakdown →
402
13 43
14 116
15 185
16 9
17 0
18 4
19 77
20 398

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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