On the influence propagation of web videos

Liu, Jiajun, Yang, Yi, Huang, Zi, Yang, Yang and Shen, Heng Tao (2013) On the influence propagation of web videos. IEEE Transactions on Knowledge and Data Engineering, 26 99: 1961-1973. doi:10.1109/TKDE.2013.142

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Author Liu, Jiajun
Yang, Yi
Huang, Zi
Yang, Yang
Shen, Heng Tao
Title On the influence propagation of web videos
Journal name IEEE Transactions on Knowledge and Data Engineering   Check publisher's open access policy
ISSN 1041-4347
Publication date 2013-08-20
Sub-type Article (original research)
DOI 10.1109/TKDE.2013.142
Open Access Status
Volume 26
Issue 99
Start page 1961
End page 1973
Total pages 13
Place of publication Piscataway, NJ, United States
Publisher IEEE
Collection year 2014
Language eng
Abstract We propose a novel approach to analyze how a popular video is propagated in the cyberspace, to identify if it originated from a certain sharing-site, and to identify how it reached the current popularity in its propagation. In addition, we also estimate their influences across different websites outside the major hosting website. Existing study regarding the flow of influence is lacking. In this article we introduce a novel framework to identify the propagation of popular videos from its major hosting site's perspective, and to estimate its influence. We define a Unified Virtual Community Space (UVCS) to model the propagation and influence of a video, and devise a novel learning method called Noise-reductive Local-and-Global Learning (NLGL) to effectively estimate a video's origin and influence. Without losing generality, we conduct experiments on annotated dataset collected from a major video sharing site to evaluate the effectiveness of the framework. Surrounding the collected videos and their ranks, some interesting discussions regarding the propagation and influence of videos as well as user behavior are also presented.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Rank A journal

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 2 times in Scopus Article | Citations
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Created: Fri, 22 Nov 2013, 09:46:45 EST by Dr Heng Tao Shen on behalf of School of Information Technol and Elec Engineering