Is access frequency adequate for video popularity ranking in P2P streaming systems?

Video popularity ranking is commonly used in various streaming systems. Existing popularity ranking systems usually rank videos from the perspective of access frequency and ignore other implicit feedback, due to the belief that popularity rankings with different implicit metrics are highly consistent. Based on a large collection of real-world system trace data, this paper systematically compares video popularity rankings with four different implicit metrics: access frequency, access user frequency, watching time, normalized watching time. We not only analyze the temporal dynamics of videos' popularities ranking with different metrics, but also examine the correlation between them. We have two main findings. 1) The popularities rankings with access frequency and watching time have strong correlation, but the other pairs have low consistency. 2) The temporal dynamics of daily rankings are similar, while the popularity rankings by access frequency and user number frequency are more stable than others. This paper also proposes a new top-N rank correlation coefficient and proves its efficiency. Our analysis results indicate that the implicit metric of popularity ranking needs to be carefully chosen according to specific applications.