Leveraging explicitly disclosed location information to understand tourist dynamics: a case study

The approach to collect and analyse the history of physical presence of tourists from the digital footprints they publicly disclose on the web is described and initial results provide insights on the density of tourists, the points of interests they visit as well as the most common trajectories they follow.

Abstract

In recent years, the large deployment of mobile devices has led to a massive increase in the volume of records of where people have been and when they were there. The analysis of these spatio-temporal data can supply high-level human behavior information valuable to urban planners, local authorities, and designer of location-based services. In this paper, we describe our approach to collect and analyze the history of physical presence of tourists from the digital footprints they publicly disclose on the web. Our work takes place in the Province of Florence in Italy, where the insights on the visitors’ flows and on the nationalities of the tourists who do not sleep in town has been limited to information from survey-based hotel and museums frequentation. In fact, most local authorities in the world must face this dearth of data on tourist dynamics. In this case study, we used a corpus of geographically referenced photos taken in the province by 4280 photographers over a period of 2 years. Based on the disclosure of the location of the photos, we design geovisualizations to reveal the tourist concentration and spatiotemporal flows. Our initial results provide insights on the density of tourists, the points of interests they visit as well as the most common trajectories they follow.