Will This Video Go Viral? Explaining and Predicting the Popularity of Youtube Videos

Kong, Q; Rizoiu, M-A; Wu, S; Xie, L

Will This Video Go Viral? Explaining and Predicting the Popularity of Youtube Videos

Kong, Q Rizoiu, M-A

Wu, S Xie, L

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Publication Type:: Conference Proceeding
Citation:: Proceedings of WWW 2018

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Field	Value	Language
dc.contributor.author	Kong, Q	en_US
dc.contributor.author	Rizoiu, M-A https://orcid.org/0000-0003-0381-669X	en_US
dc.contributor.author	Wu, S	en_US
dc.contributor.author	Xie, L	en_US
dc.date.accessioned	2020-04-16T23:21:22Z
dc.date.available	2020-04-16T23:21:22Z
dc.identifier.citation	Proceedings of WWW 2018	en_US
dc.identifier.uri	http://hdl.handle.net/10453/140053
dc.description.abstract	What makes content go viral? Which videos become popular and why others don't? Such questions have elicited significant attention from both researchers and industry, particularly in the context of online media. A range of models have been recently proposed to explain and predict popularity; however, there is a short supply of practical tools, accessible for regular users, that leverage these theoretical results. HIPie -- an interactive visualization system -- is created to fill this gap, by enabling users to reason about the virality and the popularity of online videos. It retrieves the metadata and the past popularity series of Youtube videos, it employs Hawkes Intensity Process, a state-of-the-art online popularity model for explaining and predicting video popularity, and it presents videos comparatively in a series of interactive plots. This system will help both content consumers and content producers in a range of data-driven inquiries, such as to comparatively analyze videos and channels, to explain and predict future popularity, to identify viral videos, and to estimate response to online promotion.	en_US
dc.relation.ispartof	Proceedings of WWW 2018	en_US
dc.relation.isbasedon	10.1145/3184558.3186972	en_US
dc.rights	"© ACM 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of WWW 2018, } https://dl.acm.org/doi/10.1145/3184558.3186972 "
dc.title	Will This Video Go Viral? Explaining and Predicting the Popularity of Youtube Videos	en_US
dc.type	Conference Proceeding
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access

Abstract:

What makes content go viral? Which videos become popular and why others don't? Such questions have elicited significant attention from both researchers and industry, particularly in the context of online media. A range of models have been recently proposed to explain and predict popularity; however, there is a short supply of practical tools, accessible for regular users, that leverage these theoretical results. HIPie -- an interactive visualization system -- is created to fill this gap, by enabling users to reason about the virality and the popularity of online videos. It retrieves the metadata and the past popularity series of Youtube videos, it employs Hawkes Intensity Process, a state-of-the-art online popularity model for explaining and predicting video popularity, and it presents videos comparatively in a series of interactive plots. This system will help both content consumers and content producers in a range of data-driven inquiries, such as to comparatively analyze videos and channels, to explain and predict future popularity, to identify viral videos, and to estimate response to online promotion.

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http://hdl.handle.net/10453/140053