Video Browsing - A Study of User Behavior in Online VoD Services

TLDR

Video traffic dominates the Internet, and prior work has modeled user browsing—including seeks—as a closed queueing network. This study aims to uncover the parameters and distributions of a stochastic user‑browsing model to improve VoD system design and management. Using a major VoD provider, the authors instrumented the client player to collect data from 540 million sessions with perfect QoE, enabling a detailed behavioral analysis. Users spend most of their time browsing, with only about 20 % of sessions watching a video to completion, and the data support a stochastic model of alternating short and long views.

Abstract

A big portion of Internet traffic nowadays is video. A good understanding of user behavior in online VoD systems can help us design, configure and manage video content distribution. With the help of a major video on demand (VoD) service provider, we conduct 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 focus on 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 towards 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. A purely abstract version of such user behavior model was proposed by Wu et al [1] as a closed queueing network formulation. Our study uncovers the parameters and distributions of such a stochastic behavior model based on observations in practice.