"One of the depressing truths about social media is that the popularity of an image is not necessarily an indication of its quality. It’s easy to find hugely popular content of dubious quality. But it’s much harder to find unpopular content of high quality.
That’s largely because popularity is governed by a power law: a small proportion of content receives a large proportion of attention while the vast majority of content shares the rest. Take the picture-sharing website Flickr, which hosts some 200 million pictures. Of these, 166 million have five favorites or less.
That’s a large number of unpopular pictures! It’s easy to imagine that there must be many photographic gems hidden within this long tail of unpopularity. But how to reveal it?
Today, we get and answer thanks to the work of Rossano Schifanella at the University of Turin in Italy and Miriam Redi and Luca Maria Aiello at Yahoo Labs in Barcelona. These guys have taught a machine vision algorithm to recognize beauty and then allowed it to trawl through the long tail of unpopular Flickr images looking for gems that nobody has noticed. And the results are impressive."