Uncovering the Spatio-temporal Structure of Social Networks Using Cell Phone Records

LUIS G. MOYANO; OSCAR MOLL THOMAE; ENRIQUE MARTINEZ-FRIAS

Bruselas

Workshop; The 12th IEEE International Conference on Data Mining; 2012

IEEE

Although research in the areas of human mobility and social networks is extensive, our knowledge of the relationship between the mobility and the social network of an individual is very limited, mainly due to the complexity of accessing adequate data to be able to capture both mobility and social interactions. In this paper we present and characterize some of the spatio-temporal features of social networks extracted from a large-scale dataset of cell phone records. Our goal is to measure to which extent individual mobility shapes the characteristics of a social network. Our results show a nontrivial dependence between social network structure and the spatial distribution of its elements. Additionally, we quantify with detail the probability of a contact to be at a certain distance, and find that it may be described in the framework of gravity models, with different decaying rates for urban and interurban scales.