Uncovering individual and collective human dynamics from mobile phone records

TL;DR

This paper analyzes mobile phone records to uncover patterns in human social interactions and collective behavior, revealing heavy-tailed interevent times and applying percolation theory to understand anomalies.

Contribution

It introduces a novel analysis of large-scale mobile phone data to study human dynamics and social interactions, highlighting the application of percolation theory to anomalies.

Findings

Heavy-tailed interevent times in calling activity

Identification of spatiotemporal anomalies using percolation theory

Insights into collective human behavior patterns

Abstract

Novel aspects of human dynamics and social interactions are investigated by means of mobile phone data. Using extensive phone records resolved in both time and space, we study the mean collective behavior at large scales and focus on the occurrence of anomalous events. We discuss how these spatiotemporal anomalies can be described using standard percolation theory tools. We also investigate patterns of calling activity at the individual level and show that the interevent time of consecutive calls is heavy-tailed. This finding, which has implications for dynamics of spreading phenomena in social networks, agrees with results previously reported on other human activities.