This paper resulted from an interdisciplinary research project at the University of Michigan focused on data sources and techniques for analyzing neighborhood effects on urban health. Here’s the abstract:
An established body of research has used secondary data sources (such as proprietary business databases) to demonstrate the importance of the neighborhood food environment for multiple health outcomes. However, documenting food availability using secondary sources in low-income urban neighborhoods can be particularly challenging since small businesses play a crucial role in food availability. These small businesses are typically underrepresented in national databases, which rely on secondary sources to develop data for marketing purposes. Using social media and other crowdsourced data to account for these smaller businesses holds promise, but the quality of these data remains unknown. This paper compares the quality of full-line grocery store information from Yelp, a crowdsourced content service, to a â€œground truthâ€ data set (Detroit Food Map) and a commercially-available dataset (Reference USA) for the greater Detroit area. Results suggest that Yelp is more accurate than Reference USA in identifying healthy food stores in urban areas. Researchers investigating the relationship between the nutrition environment and health may consider Yelp as a reliable and valid source for identifying sources of healthy food in urban environments.