Virality of content on social media

Abstract

Virality of online content on social networking websites is an important but esoteric phenomenon often studied in elds like marketing, psychology and data mining. In this project, I have studied viral content from a computer vision and natural language perspective. I have introduced a new dataset from Twitter for studying virality and de ned an annotation score using Twitter metadata. I have also trained a deep learning Siamese model to predict virality of individual posts using relative virality in pairs of posts.