Data-Driven Profiling of Inland Areas: Studying Changes in Mobile Users Presence After Covid-19

Cellular networks worldwide are facing a significant increase of services demand, that has forced operators to focus on accurate modelling of network dynamics as a key task to target efficiency. Besides being useful for optimizing the functioning of the network, mobile data analytics have unleashed unexpected opportunities to address several social and urban issues at large scales. In this work, we take such opportunity and envision a framework able to profile urban settlements according to the relationship between their attractiveness and the characteristics of the built environment. Focusing on the effects that Covid-19 pandemic had on mobile users' habits, we take a representative case study in Italy and use real-world mobile radio access data to investigate the spatial variation of people visiting behaviour, providing insights about how such change relates to the social and urban context characterizing the reference area.