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J R Soc Interface. 2015 Apr 6;12(105). pii: 20141128. doi: 10.1098/rsif.2014.1128.

Coupling human mobility and social ties.

Author information

1
Engineering Systems Division, MIT, Cambridge, MA 02144, USA jltoole@mit.edu.
2
Department of Civil and Environmental Engineering, MIT, Cambridge, MA 02144, USA Departamento de Matemática Aplicada a las Tecnologías de la Información, ETSI Telecomunicación, Universidad Politécnica de Madrid (UPM), Madrid, Spain.
3
Department of Civil and Environmental Engineering, MIT, Cambridge, MA 02144, USA.
4
Engineering Systems Division, MIT, Cambridge, MA 02144, USA Department of Civil and Environmental Engineering, MIT, Cambridge, MA 02144, USA.

Abstract

Studies using massive, passively collected data from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion and organizational dynamics. More recently, these data have come tagged with geographical information, enabling studies of human mobility patterns and the science of cities. We combine these two pursuits and uncover reproducible mobility patterns among social contacts. First, we introduce measures of mobility similarity and predictability and measure them for populations of users in three large urban areas. We find individuals' visitations patterns are far more similar to and predictable by social contacts than strangers and that these measures are positively correlated with tie strength. Unsupervised clustering of hourly variations in mobility similarity identifies three categories of social ties and suggests geography is an important feature to contextualize social relationships. We find that the composition of a user's ego network in terms of the type of contacts they keep is correlated with mobility behaviour. Finally, we extend a popular mobility model to include movement choices based on social contacts and compare its ability to reproduce empirical measurements with two additional models of mobility.

KEYWORDS:

city science; complex systems; human mobility; mobile phones; networks

PMID:
25716185
PMCID:
PMC4387518
DOI:
10.1098/rsif.2014.1128
[Indexed for MEDLINE]
Free PMC Article

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