Activity clocks: spreading dynamics on temporal networks of human contact

Laetitia Gauvin (1) , André Panisson (1) , Ciro Cattuto (1) , Alain Barrat (2, 1, 3, 4)

1 ISI - Data Science Laboratory
2 CPT - E5 Physique statistique et systèmes complexes
3 CPT - Centre de Physique Théorique - UMR 6207
4 CPT - Centre de Physique Théorique - UMR 7332

Dynamical processes on time-varying complex networks are key to un- derstanding and modeling a broad variety of processes in socio-technical systems. Here we focus on empirical temporal networks of human proxim- ity and we aim at understanding the factors that, in simulation, shape the arrival time distribution of simple spreading processes. Abandoning the notion of wall-clock time in favour of node-specific clocks based on activ- ity exposes robust statistical patterns in the arrival times across different social contexts. Using randomization strategies and generative models constrained by data, we show that these patterns can be understood in terms of heterogeneous inter-event time distributions coupled with hetero- geneous numbers of events per edge. We also show, both empirically and by using a synthetic dataset, that significant deviations from the above behavior can be caused by the presence of edge classes with strong activity correlations.

Domaines: Adaptation et Systèmes auto-organisés [nlin.AO]; Physique et Société [physics.soc-ph]

Laetitia Gauvin, André Panisson, Ciro Cattuto, Alain Barrat. Activity clocks: spreading dynamics on temporal networks of human contact. Scientific Reports, 2013, 3, pp.3099. ⟨10.1038/srep03099⟩. ⟨hal-00836266⟩