Tracking social and governmental responses to COVID-19 using geospatial big data

Communities react differently to the outbreak of COVID-19, leading to unequal health and
socioeconomic impacts. However, real-time data describing disparities in community responses
are challenging to obtain. Emerging geospatial big data collected from social media, news websites,
and web applications provide timely and innovative sources to track the spatial-temporal
disparities in community responses. The proposed project seeks to collect time-sensitive Twitter,
Facebook, news website, and online data hubs to analyze the changing social and governmental
responses to the spread of COVID-19 in the U.S. and examine its differential health and
socioeconomic impacts.

The research team consists of:
Lei Zou (PI), Department of Geography
Jian Tao (Co-PI), Texas A&M Engineering Experiment Station
Ali Mostafavi (Co-PI), Departmental of Civil and Environmental Engineering
Nick Duffield (Consultant), the Texas A&M Institute of Data Science
The project is one of the inaugural awardees of the TAMIDS Data Resource Development Program.