Using participatory sensing in the study of tourists behaviour

Abstract

Tourism has become a global economic force, being responsible for approximately 10% of total world GDP. For this reason, offer better services for tourists is indispensable. With this goal in mind, in this work we study how tourists move through time and space and the factors that influence their movements in four major cities: London, Rio de Janeiro, New York and Tokyo. To perform this study we use data from social networking platforms, which are being massively used, thanks to mobile devices with powerful networking and computing capabilities. We perform a large scale study of tourists mobility from several aspects. For instance, we use a spatio-temporal graph model to study urban mobility of tourists, identifying where and when places are more important to users in the studied cities. Our results have implications in several segments. In fact, we demonstrate possible uses of our results in a new itinerary recommendation system and how business owners could improve their services.