Characterizing, Modeling and Exploiting the Mobile Demand Footprint of Large Public Protests

Abstract

Smartphones and mobile applications are staple tools in the operation of current-age public demonstrations, where they support organizers and participants in, e.g., scaling the management of the events or communicating live about their objectives and traction. The widespread use of mobile services during protests also presents interesting opportunities to observe the dynamics of these manifestations from a digital perspective. Previous studies in that direction have focused on the analysis of content posted in selected social media so as to forecast, survey or ascertain the success of public protests. In this paper, we take a different viewpoint and present a holistic characterization of the consumption of the whole spectrum of mobile applications during social protests. Hinging upon pervasive measurements in the production network of the incumbent network operator and focusing on the 2023 French pension reform strikes, we unveil how large masses of protesters generate a clearly recognizable footprint on mobile service demands in the examined events. In fact, the footprint is so strong that it lets us develop models informed by the usage of selected mobile applications that are capable of (i) tracking the spatiotemporal evolution of the target demonstrations and (ii) estimate the time-varying number of attendees from aggregate network operator data only. We demonstrate the utility of such privacy-preserving models to perform a-posteriori analyses of the public protests that reveal, e.g., the precise progression of the marches, alternate minor routes taken by participants or their dispersal at the end of the events.