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Mobility patterns predict increasing polarization between neighborhoods.

Karl Vachuska1, Meghann Norden-Bright1

  • 1Department of Sociology, University of Wisconsin-Madison, United States.

Social Science Research
|May 22, 2026
PubMed
Summary
This summary is machine-generated.

Neighborhood mobility patterns significantly predict political polarization. Mobility connections to disadvantaged areas increase Republican voting, widening the political divide.

Keywords:
Everyday mobilitymobility-based disadvantagepolarizationvoting

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Area of Science:

  • Social Sciences
  • Political Science
  • Urban Studies

Background:

  • Political polarization is a growing concern in the United States.
  • Understanding the drivers of political shifts is crucial for democratic health.
  • Traditional analyses often focus on residential characteristics, potentially overlooking dynamic factors.

Purpose of the Study:

  • To investigate the relationship between neighborhood mobility patterns and political polarization.
  • To examine how mobility ties to disadvantaged or advantaged neighborhoods influence voting shifts.
  • To assess the role of mobility-based disadvantage in predicting political alignment over time.

Main Methods:

  • Utilized everyday mobility data from SafeGraph.
  • Analyzed election results at the census block group level for the 2016 and 2020 presidential elections.
  • Measured neighborhood disadvantage through residential data and mobility connections.

Main Results:

  • Predominantly White neighborhoods with mobility links to disadvantaged areas showed increased Republican voting.
  • Conversely, neighborhoods connected to more advantaged areas saw decreased Republican support.
  • Mobility-based disadvantage increasingly explains variations in voting patterns, with the Republican vote gap expanding significantly by 2020.

Conclusions:

  • Neighborhood mobility patterns are strong predictors of political polarization, often surpassing static residential characteristics.
  • Mobility ties play a critical role in shaping political landscapes and contributing to widening political divides.
  • The findings highlight the dynamic nature of political alignment influenced by sociospatial connections.