Human mobility patterns are associated with experienced partisan segregation in US metropolitan areas

被引:5
|
作者
Zhang, Yongjun [1 ,2 ]
Cheng, Siwei [3 ]
Li, Zhi [3 ,4 ]
Jiang, Wenhao [3 ]
机构
[1] SUNY Stony Brook, Dept Sociol, Stony Brook, NY USA
[2] SUNY Stony Brook, Inst Adv Computat Sci, Stony Brook, NY USA
[3] NYU, Dept Sociol, New York, NY USA
[4] NYU Shanghai, Ctr Appl Social & Econ Res, Shanghai, Peoples R China
来源
SCIENTIFIC REPORTS | 2023年 / 13卷 / 01期
关键词
INEQUALITY;
D O I
10.1038/s41598-023-36946-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:9
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