  Corporations spend millions of dollars on developing creative image-based
promotional content to advertise to their user-base on platforms like Twitter.
Our paper is an initial study, where we propose a novel method to evaluate and
improve outreach of promotional images from corporations on Twitter, based
purely on their describable aesthetic attributes. Existing works in aesthetic
based image analysis exclusively focus on the attributes of digital
photographs, and are not applicable to advertisements due to the influences of
inherent content and context based biases on outreach.
  Our paper identifies broad categories of biases affecting such images,
describes a method for normalization to eliminate effects of those biases and
score images based on their outreach, and examines the effects of certain
handcrafted describable aesthetic features on image outreach. Optimizing on the
describable aesthetic features resulting from this research is a simple method
for corporations to complement their existing marketing strategy to gain
significant improvement in user engagement on social media for promotional
images.
