  To choose restaurants and coffee shops, people are increasingly relying on
social-networking sites. In a popular site such as Foursquare or Yelp, a place
comes with descriptions and reviews, and with profile pictures of people who
frequent them. Descriptions and reviews have been widely explored in the
research area of data mining. By contrast, profile pictures have received
little attention. Previous work showed that people are able to partly guess a
place's ambiance, clientele, and activities not only by observing the place
itself but also by observing the profile pictures of its visitors. Here we
further that work by determining which visual cues people may have relied upon
to make their guesses; showing that a state-of-the-art algorithm could make
predictions more accurately than humans at times; and demonstrating that the
visual cues people relied upon partly differ from those of the algorithm.
