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Video requests from Online Social Networks: Characterization, analysis and generation

机译:来自在线社交网络的视频请求:表征,分析和生成

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The deep penetration of Online Social Networks (OSNs) have made them major portals for video content sharing. It is known that a significant portion of the accesses to video sharing sites are now coming from OSN users. Yet the unique features of video sharing over OSNs and their impact remain largely unknown. In this paper, we present a measurement study towards understanding the video requests from OSNs. We closely collaborated with a large-scale Facebook-like OSN to analyze its user access logs spanning over four months. Our measurement reveals a number of distinctive features on the popularity distribution of videos shared over the OSN. In particular, we observe that the OSN amplifies the skewness of video popularity so largely that about 2% most popular videos account for 90% of total views; the video requests distribution also exhibits perfect power-law feature; video popularity evolution shows more dynamics. All these noticeably differ from that of conventional videos, such as YouTube videos. To further understand the characteristics, we model the video viewing and sharing behaviors in OSNs, leading to the development of a practical emulator. It reveals the gap between the sharing rate and the viewing rate, and generates user requests that well capture the video popularity distribution and dynamics as observed in our empirical data.
机译:在线社交网络(OSN)的深入渗透使其成为视频内容共享的主要门户。众所周知,对视频共享站点的访问现在有很大一部分来自OSN用户。然而,通过OSN共享视频的独特功能及其影响仍然未知。在本文中,我们针对了解OSN的视频请求进行了一项测量研究。我们与类似Facebook的大型OSN密切合作,分析了四个月以来的用户访问日志。我们的测量结果揭示了在OSN上共享的视频的受欢迎程度分布中的许多独特功能。特别是,我们观察到OSN极大地放大了视频流行度的偏斜度,以至于大约2%的最受欢迎视频占据了总观看次数的90%;视频请求分配还具有完善的幂律功能;视频受欢迎程度的演变显示出更多动态。所有这些都与传统视频(例如YouTube视频)明显不同。为了进一步了解这些特性,我们对OSN中的视频观看和共享行为进行了建模,从而开发了实用的模拟器。它揭示了分享率和观看率之间的差距,并生成了可以很好地捕获视频受欢迎程度分布和动态的用户请求,如我们的经验数据所观察到的那样。

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