Segregated interactions in urban and online space
November 11, 2019 Β· Declared Dead Β· π EPJ Data Science
"No code URL or promise found in abstract"
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Authors
Xiaowen Dong, Alfredo J. Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burcin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland
arXiv ID
1911.04027
Category
cs.SI: Social & Info Networks
Cross-listed
physics.soc-ph
Citations
61
Venue
EPJ Data Science
Last Checked
5 months ago
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.
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