Identifying communities of practice through mobile phone data

Abstract

This paper focuses on the potentialities offered by mobile phone data to a reading of the site practices and rhythms of usage of the contemporary city by identifying the principal mobile practices of different urban populations. Beginning with the results of a research carried out in the Italian region of Lombardy, utilising mobile phone data provided by Telecom Italia, the paper will demonstrate how new maps, based on mobile phone data and better tailored to the dynamic processes taking place, can represent spatialized urban practices, provide new insights into the analysis of space-time patterns of mobility practices and be employed to recognise different "communities of practice". Mobile traf ic data were treated as the effect of individual behaviours and habits that become aggregates, offering information about the features of usage of urban spaces that vary in time. The outcomes permit a visualisation of the spatial distribution of mobility lows, in addition to describing the experiential dimensions of commuting rhythms. It is possible to argue that commuting can be conceived as a mobile practice that exploits a rich variety of places of use in accordance with the temporal organisation of a day. The processing of mobile phone data, by offering new maps of site practices in Lombardy and information on temporary populations and city usage patterns (daily/nightly practices, non-systematic mobility), made it possible to trace'fuzzy boundaries' as perimeters of practice. These practices are proposed as a tool for supporting and increasing the ef iciency of urban policies and mobility services.

Toward a Systemic Use of Manifold Cell Phone Network Data for Urban Analysis and Planning

“…These data, then, offer the potential of identifying different urban populations. The identification of temporary urban populations through mobile phone data is not has only a heuristic purpose, focused on describing new urban dynamics and time-dependent patterns in the use of urban spaces, but also can be seen as a tool for learning about new claims and urban demands, in favor of more efficient and less costly urban policies (Pucci, 2014).…”