A big portion of Internet traffic nowadays is video. A good understanding of user behavior in online Video-on-Demand (VoD) systems can help us design, configure and manage video content distribution. With the help of a major VoD service provider, we conducted a detailed study of user behavior watching streamed videos over the Internet. We engineered the video player at the client side to collect user behavior reports for over 540 million sessions. In order to isolate the possible effect of session quality of experience (QoE) on user behavior, we use only the sessions with perfect QoE, and leave out those sessions with QoE impairments (such as freezes). Our main finding is that users spend a lot of time browsing: viewing part of one video after another, and only occasionally (around 20% of the time) watching a video to its completion. We consider seek (jump to a new position of the video) as a special form of browsing – repeating partial viewing of the same video. Our analysis leads to a user behavior model in which a user transitions through a random number of short views before a longer view, and repeats the process a random number of times. This model can be considered an extension, and a more detailed alternative to the closed queueing network formulation introduced by Wu et al. (2009) [1]. As an application of our user behavior model, we use it to measure video popularity. We study the similarity of our approach to subjective evaluation and simple view count based metric, and conclude our approach gives results closer to subjective evaluation. 
A study of user behavior in online VoD services