Disentangling Simultaneous Spatiotemporal Events in Mobile Network Traffic Data: The Case of the 2025 UEFA Champions League Final

Abstract

Large-scale social gatherings often generate distinctive patterns of activity in mobile networks due to the concentration of a substantial amount of users. While prior work has shown that specific individual events leave clear identifiable signatures in aggregate network traffic, disentangling the effects generated on mobile data usage by concurrent and co-located happenings entails significant added complexity. In this paper, we present a methodology to detect different but coinciding mass manifestations by unraveling distinct traffic signatures associated with the coexisting behaviors, thus allowing to monitor the spatiotemporal evolution of each event in isolation. We demonstrate the effectiveness of our approach in a practical use case, i.e. the combination of cheerful celebrations and social unrest episodes that accompanied Paris Saint-Germain’s 2025 UEFA Champions League victory in the city of Paris, France. Using mobile network traffic measurements collected by a leading network operator, we successfully separate the mobile traffic consumption patterns of peaceful partying crowds from those of rioters that confronted local police forces, and reconstruct the directional flows of the different groups across the city.