What makes an image popular?

Aditya Khosla
Atish Das Sarma
Raffay Hamid
eBay Research Labs


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.

[paper] [bibtex] [slides]

Popularity Demo

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Popularity API

Usage: http://popularity.csail.mit.edu/cgi-bin/image.py?url=IMG_URL


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Please cite the following paper if you use this service:
What makes an image popular?
A. Khosla, A. Das Sarma and R. Hamid
International World Wide Web Conference (WWW), 2014


Aditya Khosla would like to thank Facebook for their generous fellowship. We would also like to thank Adam Conner-Simons for the media outreach. To keep up to date on other CSAIL research, be sure to find CSAIL on Facebook and Twitter.