The Dynamics of Urban Mobility Behavior

Mobile geolocation data provide new opportunities for near real-time understanding of local population activity, but raises significant social, ethical, and technical challenges. This project uses large-scale locational data to understand mobility behavior across the United States and develop privacy-preserving approaches to geolocational analytics. We are working to understand evacuation and recovery during natural disasters, public-space and park activity and utilization, neighborhood change and socioeconomic integration, and a real-time population census to supplement existing survey-based methods. 


Currently, our research is focused on the COVID-19 pandemic. We are developing computational models derived from these data to (1) estimate exposure density across a range of temporal and spatial scales, which will enable public health officials and researchers to evaluate and predict transmission rates in a particular area; (2) measure and evaluate the extent and effectiveness of social (physical) distancing efforts over time and comparatively within and across neighborhoods and cities, as well as understand the disparate impacts on vulnerable communities and populations; and (3) measure the extent of disease spread based on movement and travel patterns between neighborhoods and communities, which will support predictions of the spatial-temporal patterns of disease outbreak and identify at-risk locations based on aggregated mobility.

/ Apr 21,2021

Inequality in Resilience to Natural Disasters

Using Large-scale Mobility Data as Measurement 

by Constantine Kontokosta, Arpit Gupta, Bartosz Bończak, Boyeong Hong
/ Apr 06,2021

Up-and-Coming or Down-and-Out?

Social Media Popularity as an Indicator of Neighborhood Change 

by Constantine Kontokosta, Yuan Lai
/ Mar 31,2021

Exposure density and neighborhood disparities

in COVID-19 infection risk 

by Constantine Kontokosta, Boyeong Hong, Bartosz Bończak, Arpit Gupta
more on: density, mobility
/ Feb 24,2020

Validating the Use of Wi-Fi Signals

to Estimate Hyperlocal Urban Population 

by Nicholas Johnson, Pablo Mandiola, Cyrus Blankinship, Bartosz Bończak, Constantine Kontokosta
more on: data, mobility
/ Nov 30,2018

Digital footprints

Using WiFi probe and locational data to analyze mobility trajectories 

by Martin Traunmueller, Nicholas Johnson, Awais Malik, Constantine Kontokosta
more on: data, mobility

Featured Blog Posts

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/ Jan 20,2023

Constantine Kontokosta and Solly Angel

Receive Seed Funding to Study Mobility Patterns and Use of Space

more on: mobility
/ Apr 23,2021

Civic Analytics New Research on Resilience

Measuring Inequality in Community Resilience to Natural Disasters

more on: poverty

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