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What Makes an Image Popular?







Hundreds of thousands of photographs are uploaded to the
internet every minute through various social networking and
photo sharing platforms. While some images get millions
of views, others are completely ignored. Even from the
same users, different photographs receive different number
of views. This begs the question: What makes a photograph
popular? Can we predict the number of views a photograph
will receive even before it is uploaded? These are some of the
questions we address in this work. We investigate two key
components of an image that affect its popularity, namely
the image content and social context. Using a dataset of
about 2
.3 million images from Flickr, we demonstrate that
we can reliably predict the normalized view count of images
with a rank correlation of 0
.81 using both image content and
social cues. In this paper, we show the importance of image
cues such as color, gradients, deep learning features and the
set of objects present, as well as the importance of various
social cues such as number of friends or number of photos
uploaded that lead to high or low popularity of images 



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