Social network dynamics of face-to-face interactions

TL;DR

This paper introduces a flexible model for short-term face-to-face social interactions, capturing bursty behaviors and heterogeneities, and demonstrates its ability to replicate empirical social network data.

Contribution

It presents a novel analytical and numerical model for social interactions at short time scales, incorporating heterogeneity and dynamic group sizes.

Findings

Model reproduces key features of empirical face-to-face interaction data.

Heterogeneity and dynamic group sizes significantly affect social interaction patterns.

Framework can be extended to study social processes on networks.

Abstract

The recent availability of data describing social networks is changing our understanding of the "microscopic structure" of a social tie. A social tie indeed is an aggregated outcome of many social interactions such as face-to-face conversations or phone-calls. Analysis of data on face-to-face interactions shows that such events, as many other human activities, are bursty, with very heterogeneous durations. In this paper we present a model for social interactions at short time scales, aimed at describing contexts such as conference venues in which individuals interact in small groups. We present a detailed anayltical and numerical study of the model's dynamical properties, and show that it reproduces important features of empirical data. The model allows for many generalizations toward an increasingly realistic description of social interactions. In particular in this paper we investigate the case where the agents have intrinsic heterogeneities in their social behavior, or where dynamic variations of the local number of individuals are included. Finally we propose this model as a very flexible framework to investigate how dynamical processes unfold in social networks.