Video sharing in online social network: Measurement and analysis

Online social networks (OSNs) have become popular desti-nations for connecting friends and sharing information. Re-cent statistics suggest that OSN users regularly share con-tents from video sites, and a significant amount of requests of the video sites are indeed from them nowadays. These behaviors have substantially changed the workload of on-line video services. To better understand this paradigm shift, we conduct a long-term and extensive measurement of video sharing in RenRen, the largest Facebook-like OSN in China. In this paper, we focus on the video popular-ity distribution and evolution. In particular, we find that the video popularity distribution exhibits perfect power-law feature (while videos in YouTube exhibit a power-law waist with a long truncated tail). Moreover, we observe that the requests for the new published videos generally experience two or three days latency to reach the peak value, and then change dynamically with a series of unpredictable bursts (while in YouTube, videos reach the global peak immedi-ately after introduction to the system, and then the accesses generally decrease overtime, except possibly on some special days). These differences can raise new challenges to con-tent providers. For example, the video popularity is now hard to predict based on their historical requests. We fur-ther develop a simple yet effective model to simulate user requests process across videos in OSNs. Trace-based simu-lation shows that it can well capture the observed features