Understanding the pulse of the online video viewing behavior on smart TVs

Abstract

In recent years, millions of households have shifted from traditional TVs to smart TVs for the purpose of viewing online videos on TV screens. In this paper, we examine a large-scale online video viewing log on smart TVs over an extended period of time. Our aim is to understand the pulse of the collective behavior along the temporal dimension. We identify eight interpretable daily patterns whose peak hours align well to different dayparts. There also exists a holiday effect in the collective behavior. In addition, we detect three types of temporal habits which characterize the differences between different households. Furthermore, we observe that the popularities of different video categories vary depending on the dayparts. The obtained findings may provide guidance on how to divide a day into several parts when developing time-aware personalized video recommendation algorithms for smart TV viewers.