Analysis of tourist classification from cellular network data

Abstract We present and evaluate a classification method to estimate tourist presence in an area from cellular network data. Our approach is based on setting up a classifier to label users according to five main classes: residents, commuters, people in-transit, tourists and excursionists. We experiment the approach in some important tourist cities in Italy: Venice, Florence, Turin and Lecce. In the lack of sound groundtruth data, we analysed the composition of different classes obtaining results in line with domain knowledge. Moreover, these results are also supported by an analysis of the locations frequented by the tourists that well conforms with expectations. Finally, the number of users classified as tourists is strongly correlated with official statistics on tourist presence in the area.