  Tourism is becoming a significant contributor to medium and long range
travels in an increasingly globalized world. Leisure traveling has an important
impact on the local and global economy as well as on the environment. The study
of touristic trips is thus raising a considerable interest. In this work, we
apply a method to assess the attractiveness of 20 of the most popular touristic
sites worldwide using geolocated tweets as a proxy for human mobility. We first
rank the touristic sites based on the spatial distribution of the visitors'
place of residence. The Taj Mahal, the Pisa Tower and the Eiffel Tower appear
consistently in the top 5 in these rankings. We then pass to a coarser scale
and classify the travelers by country of residence. Touristic site's visiting
figures are then studied by country of residence showing that the Eiffel Tower,
Times Square and the London Tower welcome the majority of the visitors of each
country. Finally, we build a network linking sites whenever a user has been
detected in more than one site. This allow us to unveil relations between
touristic sites and find which ones are more tightly interconnected.
