Jacob Brown

466 citations
11 papers · 215 · 1 hit paper · h-index 5

Impact in

Papers in

Jacob Brown

10 papers receiving 204 citations

Jacob Brown's Hit Papers

The measurement of partisan sorting for 180 million voters 2021 · 140 citations
1400+1+3Years since publication4080120

Peers

Jacob Brown
Comparison fields: 5 of 49
  • Communication 45
  • Political Science and International Relations 80
  • Sociology and Political Science 131
  • Statistical and Nonlinear Physics 18
  • Transportation 9
Replace Jeffrey Lyons with:
Jeffrey Lyons United States
Pedro López-Roldán Spain
Jeremy Pressman United States
Sol Gamsu United Kingdom
Joep Schaper Netherlands
Ayman Zohry United States
Omer Yair Israel
Nicholas DeMaria Harney Australia
Sono Shah United States
Davide Morisi Italy
Jacob Brown relative to Jeffrey Lyons United States Jeffrey Lyons's profile →
Citations per field
00.5×
Jeffrey Lyons · 1×
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 13 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 →
2021140
2 202227
3 202126
4 201310
5 20216
6 20242
7 20251
8 20251
9 20201
10 20241
11 20250

About Jacob Brown

Jacob Brown is a scholar working on Sociology and Political Science, Political Science and International Relations, Economics and Econometrics, Communication and Health, having authored 11 papers that have together received 215 indexed citations. Recurring topics across this work include Electoral Systems and Political Participation (5 papers), Urban, Neighborhood, and Segregation Studies (4 papers), Social and Cultural Dynamics (2 papers), Social and Intergroup Psychology (2 papers), Crime Patterns and Interventions (2 papers), Advanced Causal Inference Techniques (1 paper), COVID-19 epidemiological studies (1 paper) and Names, Identity, and Discrimination Research (1 paper). The work is most often cited by research in Communication (45 citations), Political Science and International Relations (80 citations), Sociology and Political Science (131 citations), Statistical and Nonlinear Physics (18 citations) and Transportation (9 citations). Jacob Brown has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Ryan Enos, Soumyajit Mazumder, James Feigenbaum, Lynn Vavreck, Arash Naeim, Michael Leo Owens, Hanno Hilbig, Kosuke Imai, Michael Zoorob and David Sutton. Their work appears in journals such as Nature Human Behaviour, Perspectives on Politics, Political Behavior, American Political Science Review and Journal of Urban Affairs.

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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