Facebook scientists want to know more about what vacation snaps could reveal about travel behavior and the world’s most popular locations — and they’ve trained an A.I. trained on some 58,000 geo-tagged photos to help do so.
The concept is an interesting one. Tourist destinations frequently become popular because they are shared in the form of online images. That, in turn, can have a big effect on influencing where people travel (in a time when such a thing is possible) and even the kinds of photos they take once they are there. To explore this phenomenon, Facebook A.I. researchers used artificial intelligence algorithms to analyze a massive archive of Flickr images, taken between 2004 and 2019, to uncover some of these details and unique insights.
In the study, Facebook’s scientists looked at aggregated tourist movements across travel sites to uncover the popularity of each one, how often it is photographed, and factors possibly influenced by conservation and policy efforts, like entry regulations and the number of tourist passes that are sold. Using visual clustering algorithms, they were able to determine the most popular locations photographed at sites, and more. For this paper, they focused on Cuzco, Peru. However, the same technique could be used for any historical site.
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