Tourists' digital footprint in cities: Comparing Big Data sources

Abstract

There is little knowledge available on the spatial behaviour of urban tourists, and yet tourists generate an enormous quantity of data when they visit cities. These data sources can be used to track their presence through their activities. The aim of this paper is to analyse the digital footprint of urban tourists through Big Data. Unlike other papers that use a single data source, this article examines three sources of data to reflect different tourism activities in cities: Panoramio (sightseeing), Foursquare (consumption), and Twitter (being connected-accommodation). The results show that the data from the three activities are partly spatially redundant and partly complementary, and allow the characterisation of multifunction tourist spaces and spaces specialising in one or various activities. The main conclusion is that it is not sufficient to use one data source to analyse the presence of tourists in cities; several must be used in a complementary manner.