  The number of people who decide to share their photographs publicly increases
every day, consequently making available new almost real-time insights of human
behavior while traveling. Rather than having this statistic once a month or
yearly, urban planners and touristic workers now can make decisions almost
simultaneously with the emergence of new events. Moreover, these datasets can
be used not only to compare how popular different touristic places are, but
also predict how popular they should be taking into an account their
characteristics. In this paper we investigate how country attractiveness scales
with its population and size using number of foreign users taking photographs,
which is observed from Flickr dataset, as a proxy for attractiveness. The
results showed two things: to a certain extent country attractiveness scales
with population, but does not with its size; and unlike in case of Spanish
cities, country attractiveness scales sublinearly with population, and not
superlinearly.
