Researchers from Pittsburgh-based Carnegie Mellon University and Stanford (Calif.) University assessed the reliability of the dataset SafeGraph by examining its demographic biases.
SafeGraph, which contains information from about 47 million mobile devices in the U.S., is a dataset policymakers have been using throughout the pandemic to analyze social distancing’s effectiveness, understand how people’s travel affects transmission rates and draw conclusions about how various economic sectors have been affected by social distancing.
The research team found that older and nonwhite people were less likely to be captured by SafeGraph’s mobility data, which could lead to the misallocation of resources and exacerbate the pandemic’s age, racial and economic disparities.
The study’s authors called for mobility data to be more representative and for firms collecting such data to be more transparent about how they source it, including identifying which smartphone applications were used to access the location data.
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