Prediction limits of mobile phone activity modelling. Issue 2 (February 2017)

• Record Type: Journal Article
• Authors: Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo
• Is Part Of: Royal Society open science. Volume 4:Issue 2(2017)
• Publication Date: 2017-02
• Subjects: mobile phone network -- urban spatial structure -- activity prediction -- event detection; Science -- Periodicals; 500
• DOI: 10.1098/rsos.160900
• Languages: English
• ISSNs: 2054-5703

Abstract

Abstract : Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.