Understanding the bias of mobile location data across spatial scales and over time: A comprehensive analysis of SafeGraph data in the United States.

ABSTRACT: Mobile location data has emerged as a valuable data source for studying human mobility patterns in various contexts, including virus spreading, urban planning, and hazard evacuation. However, these data are often anonymized overviews derived from a panel of traced mobile devices, and the representativeness of these panels is not well documented. Without a clear understanding of the data representativeness, the interpretations of research based on mobile location data may be questionable. This article presents a comprehensive examination of the potential biases associated with mobile location data using SafeGraph Patterns data in the United States as a case study. The research rigorously scrutinizes and documents the bias from multiple dimensions, including spatial, temporal, urbanization,

SUBMITTER: Li Z 

PROVIDER: S-EPMC10798630 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature