Using Google Street View and Yelp to identify ethnic enclaves and examine association between ethnic enclave status and Hispanic health outcomes

Authors: Xiaohui Liu*, National Institutions of Health, Jiue-An Yang, University of California San Diego, Marta Jankowska, University of California San Diego, Francisco Montiel Ishino, National Institute on Minority Health and Health Disparities, National Institutes of Health, Quynh Nguyen, University of Maryland School of Public Health, Pallavi Dwivedi, University of Maryland School of Public Health, Faustine Williams, National Institute on Minority Health and Health Disparities, National Institutes of Health
Topics: Medical and Health Geography, Spatial Analysis & Modeling, Human-Environment Geography
Keywords: Hispanic ethnic enclaves, environment exposure, immigrant health, big data analytics
Session Type: Virtual Paper
Day: 4/10/2021
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 8
Presentation File: No File Uploaded


Residency in ethnic enclave neighborhoods is found to have a mixed impact on immigrants’ health. Ethnic enclaves are defined as linguistically isolated groups categorized by the percent of English used within the population of a given area. Our study proposed a novel method to define Hispanic ethnic enclaves. We then explored the associations of living in ethnic enclaves with health outcomes. We used two main data sources for our study: Google Street View (GSV) images and Yelp business reviews. To achieve our study goals, we used Google computer vision tools to automatically extract Hispanic related business signs from GSV images and Google language detection tools to automatically identify Spanish language from Yelp business reviews.

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