Title :
Uncovering the Spatio-temporal Structure of Social Networks Using Cell Phone Records
Author :
Moyano, L.G. ; Thomae, O.R.M. ; Frias-Martinez, Enrique
Author_Institution :
Telefonica Res., Madrid, Spain
Abstract :
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.
Keywords :
computational complexity; feature extraction; mobile computing; mobility management (mobile radio); probability; social aspects of automation; social networking (online); spatiotemporal phenomena; cell phone records; data accessing complexity; human mobility; large-scale dataset; social interactions; social network structure; spatial distribution; spatio-temporal structure uncovering; spatiotemporal feature extraction; Cellular phones; Cities and towns; Gravity; Humans; Poles and towers; Probability distribution; Social network services; CDR; Gravity Model; Human Mobility; Social Networks;
Conference_Titel :
Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4673-5164-5
DOI :
10.1109/ICDMW.2012.132