Estimating experienced racial-ethnic segregation based on social media data: A case study in Los Angeles-Long Beach-Anaheim
Topics:
Keywords: Experienced Segregation, Spatial Segregation Measurement, Social Media Data, Human Mobility, User Profiling, Distance Decay
Abstract Type: Paper Abstract
Authors:
Meiliu Wu, University of Wisconsin-Madison
Qunying Huang, University of Wisconsin-Madison
Xinyi Liu, University of Wisconsin-Madison
Yuehan Qin, University of Southern California
,
,
,
,
,
,
Abstract
While recent studies started to measure experienced racial-ethnic segregation across activity space (beyond “residential”), insufficient efforts were devoted to revealing experienced segregation levels of racial-ethnic minorities (e.g., Asian, Hispanic, Native, and Multi-races), mainly due to the lack of a comprehensive probe into various individual-level datasets. This issue leads to an unnoted deficiency – neglecting the “directed” interactions between any pair of two groups. To bridge these gaps, this work proposed a unified framework of using social media data to infer both individual mobility patterns and user profiles (i.e., race-ethnicity and economic status), to include more racial-ethnic minorities for estimating experienced segregation. With the inferred information, we derived two spatial segregation indices, i.e., individual experienced exposure index (EEI) to each race-ethnicity and individual experienced diversity index (EDI), by considering spatial proximity of activity locations based on distance-decay functions. Using Los Angeles-Long Beach-Anaheim as the study case, we discovered: (1) experienced segregation is spatially clustered based on home locations; (2) experienced isolation (i.e., mainly intra-group interaction) still generally persists; (3) Asian group is most diverse in interacting with other groups; (4) EEI to White exhibits a significantly negative correlation with EEI to Hispanic, the same as EEI to Black and EEI to Hispanic, while a significant positive correlation between EEI to Asian and EDI is observed; and (5) EEIs to White, Black, and Hispanic are markedly influenced by individual economic status, in which both EEIs to White and to Black increase when the economic status is higher, while EEIs to Hispanic decreases.
Estimating experienced racial-ethnic segregation based on social media data: A case study in Los Angeles-Long Beach-Anaheim
Category
Paper Abstract
