An evaluation of geo-located Twitter data for measuring human migration
Year: 2022
Type: article
Abstract: This study evaluates the spatial patterns of flows generated from geo-located Twitter data to measure human migration. Using geo-located tweets continuously collected in the U.S. from 2013 to 2015, we identified Twitter users who migrated per changes in county-of-residence every two years and compared the Twitter-estimated county-to-county migration flows with the ones from the U.S. Internal Revenue Service (IRS). To evaluate the spatial patterns of Twitter migration flows when representing the IRS counterparts, we developed a normalized difference representation index to visualize and identify those counties of over-/under-representations in the Twitter estimates. Further, we applied a multidimensional spatial scan statistic approach based on a Poisson process model to detect pairs of origin and destination regions where the over-/under-representativeness occurred. The results suggest that Twitter migration flows tend to under-represent the IRS estimates in regions with a large population and over-represent them in metropolitan regions adjacent to tourist attractions. This study demonstrated that geo-located Twitter data could be a sound statistical proxy for measuring human migration. Given that the spatial patterns of Twitter-estimated migration flows vary significantly across the geographic space, related studies will benefit from our approach by identifying those regions where data calibration is necessary.
Authors: Junjun Yin, Yizhao Gao, Guangqing Chi
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
Awards: RR: The Generalizability and Replicability of Twitter Data for Population Research, CRISP Type 1/Collaborative Research: Population-Infrastructure Nexus: A Heterogeneous Flow-based Approach for Responding to Disruptions in Interdependent Infrastructure Systems, NNA Track 1: Pursuing Opportunities for Long-term Arctic Resilience for Infrastructure and Society (POLARIS), G7100165650, Population Research Institute, G8633677211, The Population Research Institute
OpenAlex ID: W4282969436