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Leveraging the characteristics of YouTube video id space and exploiting a unique property of YouTube search API, in this paper we develop a random prefix sampling method to estimate the total number of videos hosted by YouTube. Through theoretical modeling and analysis, we demonstrate that the estimator based on this method is unbiased, and provide bounds on its variance and confidence interval. These bounds enable us to judiciously select sample sizes to control estimation errors. We evaluatedoi:10.1145/2068816.2068851 dblp:conf/imc/ZhouLAZ11 fatcat:rkgdk3nrkfbwngglv2uetxalae