Metrics in Sharing Video Relationship-Networks
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Graphical Abstract
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Abstract
At present the video sharing service has gradually became one of the Internet killer applications. It is crucial to the service providers that understand the intrinsic nature of Sharing video relationship-networks (SVRNs) formed by video related list. This paper investigates the relationships between sharing videos using complex networks theory. New metrics are introduced to model and characterize the SVRN from topological view. Through extensive study on YouTube, a set of key findings are revealed. The results show that the node indegree of SVRNs follows the power-law distribution and its entropy remains stable over time. The topology also exhibits an assortative property and obvious clustering phenomenon. But the rich-club phenomenon is not evident compared with the Internet AS-level topology. This research will enable the service providers to optimally plan and operate their video-based services.
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