From seconds to months: multi-scale dynamics of mobile telephone calls

TL;DR

This paper reviews multi-scale social dynamics derived from mobile phone call data, analyzing patterns from seconds to months to understand human communication and social network evolution.

Contribution

It provides a comprehensive overview of empirical findings on the multi-scale temporal and structural dynamics of social interactions inferred from CDR data.

Findings

Call sequences exhibit burstiness at short timescales

Temporal motifs reveal correlated calling patterns among groups

Long-term social group dynamics can be inferred from call data

Abstract

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.