EPJ Data Sci. (2020) 9: 20
https://doi.org/10.1140/epjds/s13688-020-00238-7

Regular article

Segregated interactions in urban and online space

¹ Department of Engineering Science, University of Oxford, Oxford, UK
² Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
³ New England Complex Systems Institute, Cambridge, MA, USA
⁴ Institute for Data, Systems and Society, Massachusetts Institute of Technology, Cambridge, MA, USA
⁵ Department of Mathematics and GISC, Universidad Carlos III de Madrid, Leganés, Spain
⁶ Mobile and Social Computing Lab, Fondazione Bruno Kessler, Trento, Italy
⁷ Behavioral Analytics & Visualization Lab, Sabancı University, Istanbul, Turkey
⁸ New College of Florida, Sarasota, FL, USA
⁹ Grandata Labs, Buenos Aires, Argentina

^* e-mail: xdong@robots.ox.ac.uk

Received: 10 November 2019
Accepted: 25 June 2020
Published online: 10 July 2020

Abstract

Urban income segregation is a widespread phenomenon that challenges societies across the globe. Classical studies on segregation have largely focused on the geographic distribution of residential neighborhoods rather than on patterns of social behaviors and interactions. In this study, we analyze segregation in economic and social interactions by observing credit card transactions and Twitter mentions among thousands of individuals in three culturally different metropolitan areas. We show that segregated interaction is amplified relative to the expected effects of geographic segregation in terms of both purchase activity and online communication. Furthermore, we find that segregation increases with difference in socio-economic status but is asymmetric for purchase activity, i.e., the amount of interaction from poorer to wealthier neighborhoods is larger than vice versa. Our results provide novel insights into the understanding of behavioral segregation in human interactions with significant socio-political and economic implications.