Dynamic Areas of Interest Inside an Urban Destination Using Visitors’ Geolocation

Nowadays, travel experience tends to become entirely personal. The preparation of modern tourist packages requires a dynamic and personalized adaptation to the needs, capabilities and wishes of travellers. The components of these dynamic packages, consist not only of basic services, but also of other that are driven by the inherent curiosity of travellers to discover unknown destinations and cultures, as well as unprecedented experiences. Hence, the conclusive form of such packages is finalized immediately after the end of the trip, mainly, due to the continuous reformulation of their content by the travellers themselves. But this process is raising several questions: Can we determine these turning points attributed to the travellers’ intention to modify or reformulate their tourist package? And if so, can the reasons that led them to such deviation from their original plans be identified and explained? In this work, driven by the above questions and the assumption that travellers’ choices have an impact on their footprint, we propose an approximate spatio-temporal representation model to describe their decisions. This model is based on the implicit trace left by them, as it is captured in photo-sharing platforms and social networks. Initially, we use the travellers’ digital footprints to map the corresponding routes, and then we transform these into an approximation of the areas they have visited. Finally, a union on these areas is applied to map the actual visited areas inside a tourist destination. Furthermore, the study of these mappings can be used to reveal to policy and decision-makers a dynamic picture of the areas of interest inside destinations, as well as any other areas that can be further developed in the immediate future. Our proposed model is applied and tested in the city of Athens, an urban destination, using data from the photo-sharing platform Flickr.