Time allocation in social networks: correlation between social structure and human communication dynamics

TL;DR

This paper investigates how the structure of social networks influences human communication dynamics, revealing that highly connected individuals exhibit weaker communication patterns, which impacts information spread.

Contribution

It demonstrates the correlation between social network topology and communication burstiness, highlighting the importance of temporal patterns in social network analysis.

Findings

Hubs have weaker communication dynamics than less connected individuals.

Temporal communication patterns significantly affect information diffusion.

Social structure influences the strength of human interactions.

Abstract

Recent research has shown the deep impact of the dynamics of human interactions (or temporal social networks) on the spreading of information, opinion formation, etc. In general, the bursty nature of human interactions lowers the interaction between people to the extent that both the speed and reach of information diffusion are diminished. Using a large database of 20 million users of mobile phone calls we show evidence this effect is not homogeneous in the social network but in fact, there is a large correlation between this effect and the social topological structure around a given individual. In particular, we show that social relations of hubs in a network are relatively weaker from the dynamical point than those that are poorer connected in the information diffusion process. Our results show the importance of the temporal patterns of communication when analyzing and modeling dynamical process on social networks.