AI Article Synopsis

  • - The 2005 French riots began in a poor Paris suburb and spread across France for about three weeks, showcasing dramatic collective behavior and epidemic-like dynamics.
  • - Researchers utilized daily national police data to create a model that explained how the riots propagated, highlighting the significant influence of neighborhood deprivation and geographic proximity on the spread of unrest.
  • - This study represents the first comprehensive data-driven analysis of riot dynamics, providing a mathematical understanding of "waves of riots" and suggesting a new framework for modeling spontaneous collective uprisings.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5758762PMC
http://dx.doi.org/10.1038/s41598-017-18093-4DOI Listing

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