Kevin Munger

2.3k citations
42 papers · 1.1k · h-index 18

Impact in

Papers in

Kevin Munger

40 papers receiving 1.1k citations

Peers

Kevin Munger
Comparison fields: 5 of 77
  • Communication 597
  • Sociology and Political Science 707
  • General Social Sciences 41
  • Artificial Intelligence 296
  • Statistical and Nonlinear Physics 108
Replace Adrian Rauchfleisch with:
Adrian Rauchfleisch Taiwan
Judith Möller Netherlands
M. B. Fallin Hunzaker United States
Adam Edwards United Kingdom
Lisa P. Argyle United States
Neta Kligler-Vilenchik Israel
Friedolin Merhout United States
Shannon C. McGregor United States
Christian Baden Israel
Ashley Muddiman United States
Kevin Munger relative to Adrian Rauchfleisch Taiwan Adrian Rauchfleisch's profile →
Citations per field
00.5×2.9×
Adrian Rauchfleisch · 1×
Citations per year

Countries citing papers authored by Kevin Munger

Since Specialization
Citations

This map shows the geographic impact of Kevin Munger'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 Kevin Munger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Munger more than expected).

Fields of papers citing papers by Kevin Munger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin Munger. 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 Kevin Munger. The network helps show where Kevin Munger may publish in the future.

Co-authors

The 25 scholars most cited alongside Kevin Munger, 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 Kevin Munger Line = papers co-authored together Kevin Munger links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016196
2 2020127
3 201992
4 201882
5 202170
6 201965
7 202255
8 201949
9 202245
10 201842
11 202040
12 201930
13 202122
14 202320
15 202020
16 202220
17 202019
18 202118
19 202316
20 202015

About Kevin Munger

Kevin Munger is a scholar working on Communication, Sociology and Political Science, Artificial Intelligence, Political Science and International Relations and Statistical and Nonlinear Physics, having authored 42 papers that have together received 1.1k indexed citations. Recurring topics across this work include Social Media and Politics (28 papers), Misinformation and Its Impacts (17 papers), Media Influence and Politics (12 papers), Hate Speech and Cyberbullying Detection (9 papers), Opinion Dynamics and Social Influence (6 papers), Electoral Systems and Political Participation (4 papers), Computational and Text Analysis Methods (4 papers) and Media Studies and Communication (4 papers). The work is most often cited by research in Communication (597 citations), Sociology and Political Science (707 citations), General Social Sciences (41 citations), Artificial Intelligence (296 citations) and Statistical and Nonlinear Physics (108 citations). Kevin Munger has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Joseph Phillips, Andrew M. Guess, Jonathan Nagler, Joshua A. Tucker, Kenneth Benoit, Arthur Spirling, Eszter Hargittai, Mario Luca, Richard Bonneau and James Bisbee. Their work appears in journals such as Political Communication, Journal of Experimental Political Science, Public Opinion Quarterly, The Journal of Politics and Social Media + Society.

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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