期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：2
页码：1200
DOI：10.15680/IJIRCCE.2016.0402018
出版社：S&S Publications
摘要：The emergence and rapid proliferation of social media networks have reshaped the way how video contents are generated, distributed and consumed in traditional video sharing portals. Nowadays, online videos can be accessed from far beyond the internal mechanisms of the video sharing portals, such as internal search and front page highlight. Recent studies have fo und that external referrers, such as external search engines and other social media websites, arise to be the new and important portals to lead users to online videos. In this paper, a novel cross - network collaborative application is introduced to help dri ve the online traffic for given videos in traditional video portal YouTube by leveraging the high propagation efficiency of the popular Twitter followees. YouTube videos and Twitter followees distribute on heterogeneous spaces, and presenting a cross - netwo rk association - based solution framework. In this framework, first represent YouTube videos and Twitter followees in the corresponding topic spaces separately by employing generative topic models. Then, the cross - network topic spaces are associated from bot h semantic - based and network - based perspectives through the collective intelligence of the observed overlapped users. Based on the derived cross - network association, finally match the query YouTube videos and candidate Twitter followees in the same topic s pace with a unified ranking method
关键词：Video promotion; Cross-network analysis; Social media
