  As a large-scale instance of dramatic collective behaviour, the 2005 French
riots started in a poor suburb of Paris, then spread in all of France, lasting
about three weeks. Remarkably, although there were no displacements of rioters,
the riot activity did travel. Access to daily national police data has allowed
us to explore the dynamics of riot propagation. Here we show that an
epidemic-like model, with just a few parameters and a single sociological
variable characterizing neighbourhood deprivation, accounts quantitatively for
the full spatio-temporal dynamics of the riots. This is the first time that
such data-driven modelling involving contagion both within and between cities
(through geographic proximity or media) at the scale of a country, and on a
daily basis, is performed. Moreover, we give a precise mathematical
characterization to the expression "wave of riots", and provide a visualization
of the propagation around Paris, exhibiting the wave in a way not described
before. The remarkable agreement between model and data demonstrates that
geographic proximity played a major role in the propagation, even though
information was readily available everywhere through media. Finally, we argue
that our approach gives a general framework for the modelling of the dynamics
of spontaneous collective uprisings.
