Influence of sociodemographic characteristics on human mobility

TL;DR

This study analyzes geolocated credit-card transaction data from Barcelona and Madrid to reveal how sociodemographic factors like age, gender, and occupation influence human mobility patterns, emphasizing their importance in modeling mobility and disease spread.

Contribution

It provides new insights into how sociodemographic attributes affect mobility, using detailed credit-card data, which was lacking in previous studies relying on less detailed sources.

Findings

Mobility patterns differ by age and occupation.

Gender differences in mobility are minimal when age is similar.

Sociodemographic factors significantly impact travel behavior.

Abstract

Human mobility has been traditionally studied using surveys that deliver snapshots of population displacement patterns. The growing accessibility to ICT information from portable digital media has recently opened the possibility of exploring human behavior at high spatio-temporal resolutions. Mobile phone records, geolocated tweets, check-ins from Foursquare or geotagged photos, have contributed to this purpose at different scales, from cities to countries, in different world areas. Many previous works lacked, however, details on the individuals' attributes such as age or gender. In this work, we analyze credit-card records from Barcelona and Madrid and by examining the geolocated credit-card transactions of individuals living in the two provinces, we find that the mobility patterns vary according to gender, age and occupation. Differences in distance traveled and travel purpose are observed between younger and older people, but, curiously, either between males and females of similar age. While mobility displays some generic features, here we show that sociodemographic characteristics play a relevant role and must be taken into account for mobility and epidemiological modelization.