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dc.contributor.authorSiu, Wan Chien_US
dc.contributor.otherWu, J.-
dc.contributor.otherZhou, Y.-
dc.description.abstractVideo popularity is an essential reference for optimizing resource allocation and video recommendation in online video services. However, there is still no convincing model that can accurately depict a video's popularity evolution. In this paper, we propose a dynamic popularity model by modeling the video information diffusion process driven by various forms of recommendation. Through fitting the model with real traces collected from a practical system, we can quantify the strengths of the recommendation forces. Such quantification can lead to characterizing video popularity patterns, user behaviors and recommendation strategies, which is illustrated by a case study of TV episodes.en_US
dc.titleModeling and quantifying the forces driving online video popularity evolutionen_US
dc.typejournal articleen_US
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
item.openairetypejournal article-
item.fulltextWith Fulltext-
item.languageiso639-1en- of Computing and Information Sciences-
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