Social Media Advertisement Outreach: Learning the Role of Aesthetics
This work addresses the challenge for corporations to increase social media advertisement effectiveness, though it appears incremental as it builds on existing aesthetic analysis methods by adapting them to advertisements.
The paper tackles the problem of evaluating and improving the outreach of promotional images on Twitter by analyzing describable aesthetic attributes, proposing a method to normalize biases and score images, and finds that optimizing these features can significantly enhance user engagement.
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.