A Study of the Spatio-Temporal Correlations in Mobile Calls Networks

TL;DR

This paper analyzes large mobile call data to identify spatial and temporal patterns in inhabitants' behavior across France, using clustering and temporal segmentation methods to reveal behavioral dynamics over five months.

Contribution

It introduces a two-stage analysis combining spatial clustering of antennas with temporal segmentation to characterize behavioral patterns in mobile telephony data.

Findings

Identification of spatial clusters of antennas with similar call distributions

Detection of temporal changes in call behavior across regions

Visualization of behavioral patterns on a geographic map

Abstract

For the last few years, the amount of data has significantly increased in the companies. It is the reason why data analysis methods have to evolve to meet new demands. In this article, we introduce a practical analysis of a large database from a telecommunication operator. The problem is to segment a territory and characterize the retrieved areas owing to their inhabitant behavior in terms of mobile telephony. We have call detail records collected during five months in France. We propose a two stages analysis. The first one aims at grouping source antennas which originating calls are similarly distributed on target antennas and conversely for target antenna w.r.t. source antenna. A geographic projection of the data is used to display the results on a map of France. The second stage discretizes the time into periods between which we note changes in distributions of calls emerging from the clusters of source antennas. This enables an analysis of temporal changes of inhabitants behavior in every area of the country.