Determining leaders and clusters in video consumption

In this paper we analyze a trace of a deployed VoD (video on demand) system. Users issue requests for content items in an online VoD catalogue at given moments in time. Based on this information alone we identify communities of users that have similar content preferences, which we refer to as implicit social communities. We find that there is evidence for a limited number of groups of similar users. Next we also determine lead users, i.e., users that consume popular content items consistently before other users do. We show that such users can be identified in the considered data set. We also explain how these two pieces of information could be used to improve recommendation systems and content distribution networks.