Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network

Several attempts have already been made to use telecommunications networks for urban research, but the datasets employed have typically been neither dynamic nor fine grained. Against this research backdrop the mobile phone network offers a compelling compromise between these extremes: it is both highly mobile and yet still localisable in space. Moreover, the mobile phone's enormous and enthusiastic adoption across most socioeconomic strata makes it a uniquely useful tool for conducting large-scale, representative behavioural research. In this paper we attempt to connect telecoms usage data from Telecom Italia Mobile (TIM) to a geography of human activity derived from data on commercial premises advertised through Pagine Gialle, the Italian ‘Yellow Pages’. We then employ eigendecomposition—a process similar to factoring but suitable for this complex dataset—to identify and extract recurring patterns of mobile phone usage. The resulting eigenplaces support the computational and comparative analysis of space through the lens of telecommuniations usage and enhance our understanding of the city as a ‘space of flows’.