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Abstract
Partisan sorting in residential environments is an enduring feature of contemporary American politics, but little research has examined partisan segregation individuals experience in activity spaces through their daily activities. Relying on advances in spatial computation and global positioning system data on everyday mobility flows collected from smartphones, we measure experienced partisan segregation in two ways: place-level partisan segregation based on the partisan composition of its daily visitors and community-level experienced partisan segregation based on the segregation level of places visited by its residents. We find that partisan segregation experienced in places varies across different geographic areas, location types, and time periods. Moreover, partisan segregation is distinct from experienced segregation by race and income. We also find that partisan segregation individuals experience is relatively lower when they visit places beyond their residential areas, but partisan segregation in residential space and activity space is strongly correlated. Residents living in predominantly black, liberal, low-income, non-immigrant, more public transit-dependent, and central city communities tend to experience a higher level of partisan segregation.
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Details
1 Stony Brook University, Department of Sociology and Institute for Advanced Computational Science, Stony Brook, USA (GRID:grid.36425.36) (ISNI:0000 0001 2216 9681)
2 New York University, Department of Sociology, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753)
3 New York University, Department of Sociology, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753); NYU Shanghai, Center for Applied Social and Economic Research, Shanghai, China (GRID:grid.449457.f) (ISNI:0000 0004 5376 0118)