Mirjam Wattenhofer
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The YouTube Social Network
Roger Wattenhofer
Zack Zhu
Sixth International AAAI Conference on Weblogs and Social Media (ICWSM 2012)
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Today, YouTube is the largest user-driven video content provider in the world; it has become a major platform for disseminating multimedia information. A major contribution to its success comes from the user-to-user social experience that differentiates it from traditional content broadcasters. This work examines the social network aspect of YouTube by measuring the fullscale YouTube subscription graph, comment graph, and
video content corpus. We find YouTube to deviate significantly from network characteristics that mark traditional online social networks, such as homophily, reciprocative linking, and assortativity. However, comparing to reported characteristics of another content-driven
online social network, Twitter, YouTube is remarkably
similar. Examining the social and content facets of user
popularity, we find a stronger correlation between a
user’s social popularity and his/her most popular content as opposed to typical content popularity. Finally,
we demonstrate an application of our measurements for
classifying YouTube Partners, who are selected users
that share YouTube’s advertisement revenue. Results
are motivating despite the highly imbalanced nature of
the classification proble
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YouTube around the world: geographic popularity of videos
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Anders Brodersen
Salvatore Scellato
Proceedings of the 21st international conference on World Wide Web, ACM, New York, NY, USA (2012), pp. 241-250
Catching a viral video
Tom Broxton
Yannet Interian
Journal of Intelligent Information Systems (2011), pp. 1-19
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The sharing and re-sharing of videos on social sites, blogs e-mail, and other means has given rise to the phenomenon of viral videos—videos that become popular through internet sharing. In this paper we seek to better understand viral videos on YouTube by analyzing sharing and its relationship to video popularity using millions of YouTube videos. The socialness of a video is quantified by classifying the referrer sources for video views as social (e.g. an emailed link, Facebook referral) or non-social (e.g. a link from related videos). We find that viewership patterns of highly social videos are very different from less social videos. For example, the highly social videos rise to, and fall from, their peak popularity more quickly than less social videos. We also find that not all highly social videos become popular, and not all popular videos are highly social. By using our insights on viral videos we are able develop a method for ranking blogs and websites on their ability to spread viral videos.
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The sharing and re-sharing of videos on social sites, blogs e-mail, and other means has given rise to the phenomenon of viral videos – videos that become popular through internet sharing. In this paper we seek to better understand viral videos on YouTube by analyzing sharing and its relationship to video popularity using 1.5 million YouTube videos. The socialness of a video is quantified by classifying the
referrer sources for video views as social (e.g. an emailed link) or non-social (e.g. a link from related videos). By segmenting videos according to their fraction of social views, we find that viewership patterns of highly social videos is very different than less social videos. For example, the highly social videos rise to, and fall from, their peak popularity more quickly than less social videos. We also find that not all highly social videos become popular, and not all popular videos are highly social. And, despite their ability to generate large volumes of views over a short period of time, only 21% of the most popular videos (in terms of 30-day views) can be classified as viral. The observations made here lay the ground work for future work related to the creation of classification and predictive models for online videos.
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