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.
Máximo Pirri is a second year PhD student at IMDEA Networks Institute, working on uncovering insights into the spatial, temporal, and service-level dynamics of mobile traffic. By modeling these dynamics, the research aims to optimize 5G networks, improving resource management and enhancing user experience. Before his PhD, Máximo earned an Engineering degree from Facultad de Ingeniería, Universidad de la República, where he also worked on a project addressing resource allocation issues among slices in 5G networks. Additionally, he collaborated in teaching courses related to data networks and information theory.
Este evento se impartirá en inglés