Calling Dunbar's Numbers

TL;DR

This study investigates whether call frequency data from mobile phones can reveal layered social structures consistent with Dunbar's numbers, supporting the social brain hypothesis through clustering analysis.

Contribution

It demonstrates that call frequency clustering can identify layered social structures, aligning with Dunbar's numbers, and explores variability in intermediate layers.

Findings

Strong evidence for layered social structure in call data

Clustering results match Dunbar's layers at the innermost and outermost levels

Significant variability observed in intermediate layers

Abstract

The social brain hypothesis predicts that humans have an average of about 150 relationships at any given time. Within this 150, there are layers of friends of an ego, where the number of friends in a layer increases as the emotional closeness decreases. Here we analyse a mobile phone dataset, firstly, to ascertain whether layers of friends can be identified based on call frequency. We then apply different clustering algorithms to break the call frequency of egos into clusters and compare the number of alters in each cluster with the layer size predicted by the social brain hypothesis. In this dataset we find strong evidence for the existence of a layered structure. The clustering yields results that match well with previous studies for the innermost and outermost layers, but for layers in between we observe large variability.