Lifetime popularity prediction for online videos

The popularity of online content is unequally distributed. It has been observed that the top 20% most popular content account for about 80% of the network traffic. Inspired by the above observation, dynamic broadcast is designed to delivery popular content over broadcast networks to reduce the load of broadband network. Thus, identifying popular content is critically important. In this paper, we propose a new metric called Lifetime Popularity Score (LPS) to measure the popularity of online videos. The value of LPS is computed with a learned stochastic model, which establishes the relationship between video´s historic view counts and its lifetime view counts. We validate the proposed approach on a real world data set of IPTV´s VOD watch record and the experimental results have demonstrated the effectiveness of the proposed metric.