How is Attention Allocated?: Data-Driven Studies of Popularity and Engagement in Online Videos

Abstract

The share of videos on Internet traffic has been growing, e.g., people are now spending a billion hours watching YouTube videos every day. Therefore, understanding how videos capture attention on a global scale is also of growing importance for both research and practice. In online platforms, people can interact with videos in different ways -- there are behaviors of active participation (watching, commenting, and sharing) and that of passive consumption (viewing). In this paper, we take a data-driven approach to studying how human attention is allocated in online videos with respect to both active and passive behaviors. We first investigate the active interaction behaviors by proposing a novel metric to represent the aggregate user engagement on YouTube videos. We show this metric is correlated with video quality, stable over lifetime, and predictable before video's upload. Next, we extend the line of work on modelling video view counts by disentangling the effects of two dominant traffic sources -- related videos and YouTube search. Findings from this work can help content producers to create engaging videos and hosting platforms to optimize advertising strategies, recommender systems, and many more applications.