Unveiling patterns of international communities in a global city using mobile phone data


We analyse a large mobile phone activity dataset provided by Telecom Italia for the Telecom Big Data Challenge contest. The dataset reports the international country codes of every call/SMS made and received by mobile phone users in Milan, Italy, between November and December 2013, with a spatial resolution of about 200 meters. We first show that the observed spatial distribution of international codes well matches the distribution of international communities reported by official statistics, confirming the value of mobile phone data for demographic research. Next, we define an entropy function to measure the heterogeneity of the international phone activity in space and time. By comparing the entropy function to empirical data, we show that it can be used to identify the city’s hotspots, defined by the presence of points of interests. Eventually, we use the entropy function to characterize the spatial distribution of international communities in the city. Adopting a topological data analysis approach, we find that international mobile phone users exhibit some robust clustering patterns that correlate with basic socio-economic variables. Our results suggest that mobile phone records can be used in conjunction with topological data analysis tools to study the geography of migrant communities in a global city.

In EPJ Data Science