Jacob Brown

9 papers receiving 181 citations

Hit Papers

The measurement of partisan sorting for 180 million voters 2021 · 121 citations
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Peers

Jacob Brown
Comparison fields: 5 of 45
  • Communication 44
  • Political Science and International Relations 73
  • Sociology and Political Science 126
  • Urban Studies 8
  • Transportation 9
Replace Jeffrey Lyons with:
Jeffrey Lyons United States
Sören Carlson Germany
Jen Birks United Kingdom
Joep Schaper Netherlands
Sol Gamsu United Kingdom
Nikita Carney United States
Nicholas DeMaria Harney Australia
Omer Yair Israel
Sono Shah United States
Stefan Weick Germany
Jacob Brown relative to Jeffrey Lyons United States Jeffrey Lyons's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jacob Brown

Since Specialization
Citations

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

Fields of papers citing papers by Jacob Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Jacob Brown, 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 Jacob Brown Line = papers co-authored together Jacob Brown links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1
The measurement of partisan sorting for 180 million voters
Hit paper breakdown →
2021121
2 202224
3 202124
4 201310
5 20216
6 20242
7 20241
8 20251
9 20201
10 20250
11 20250

About Jacob Brown

Jacob Brown is a scholar working on Modeling and Simulation, Political Science and International Relations, Sociology and Political Science, Transportation and Communication, having authored 11 papers that have together received 190 indexed citations. Recurring topics across this work include Electoral Systems and Political Participation (5 papers), Urban, Neighborhood, and Segregation Studies (4 papers), Crime Patterns and Interventions (2 papers), Social and Cultural Dynamics (2 papers), Social and Intergroup Psychology (2 papers), Social Media and Politics (1 paper), Game Theory and Voting Systems (1 paper) and Names, Identity, and Discrimination Research (1 paper). The work is most often cited by research in Communication (44 citations), Political Science and International Relations (73 citations), Sociology and Political Science (126 citations), Urban Studies (8 citations) and Transportation (9 citations). Jacob Brown has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Ryan Enos, Soumyajit Mazumder, James Feigenbaum, Michael Leo Owens, Arash Naeim, Lynn Vavreck, Michael Zoorob, David Sutton, Kosuke Imai and Matthew Blackwell. Their work appears in journals such as British Journal of Political Science, The Journal of Politics, American Political Science Review, Political Behavior and Political Analysis.

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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