Contrasting social and non-social sources of predictability in human mobility

Zexun Chen, Sean Kelty, Alexandre G. Evsukoff, Brooke Foucault Welles, James Bagrow, Ronaldo Menezes () and Gourab Ghoshal ()
Additional contact information
Zexun Chen: University of Exeter
Sean Kelty: University of Rochester
Alexandre G. Evsukoff: DCOPPE, Federal University of Rio de Janeiro
Brooke Foucault Welles: Northeastern University
James Bagrow: University of Vermont
Ronaldo Menezes: University of Exeter
Gourab Ghoshal: University of Rochester

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: Abstract Social structures influence human behavior, including their movement patterns. Indeed, latent information about an individual’s movement can be present in the mobility patterns of both acquaintances and strangers. We develop a “colocation” network to distinguish the mobility patterns of an ego’s social ties from those not socially connected to the ego but who arrive at a location at a similar time as the ego. Using entropic measures, we analyze and bound the predictive information of an individual’s mobility pattern and its flow to both types of ties. While the former generically provide more information, replacing up to 94% of an ego’s predictability, significant information is also present in the aggregation of unknown colocators, that contain up to 85% of an ego’s predictive information. Such information flow raises privacy concerns: individuals sharing data via mobile applications may be providing actionable information on themselves as well as others whose data are absent.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-022-29592-y Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29592-y

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-022-29592-y

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().