Rossetto, Luca and Schuldt, Heiko. (2018) The Long Tail of Web Video. In: MultiMedia Modeling. MMM 2018., 10705.
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Abstract
Web Video continues to gain importance not only in many areas of computer science but in society in general. With the growth in numbers, both of videos, viewers, and views, there arise several technical challenges. In order to address them effectively, the properties of Web Video in general need to be known. There is however comparatively little analysis of these properties. In this paper, we present insights gained from the analysis of a data set containing the meta data of over 100 million videos from YouTube. We were able to confirm common wisdom about the relationship between video duration and user engagement and show the extreme long tail of the distribution of video views overall. Such data can be beneficial in making informed decisions regarding strategies for large scale video storage, delivery, processing and retrieval.
| Faculties and Departments: | 05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Databases and Information Systems (Schuldt) |
|---|---|
| UniBasel Contributors: | Schuldt, Heiko and Rossetto, Luca |
| Item Type: | Conference or Workshop Item, refereed |
| Conference or workshop item Subtype: | Conference Paper |
| Publisher: | Springer |
| ISBN: | 978-3-319-73599-3 |
| e-ISBN: | 978-3-319-73600-6 |
| Series Name: | Lecture Notes in Computer Science |
| ISSN: | 0302-9743 |
| Note: | Publication type according to Uni Basel Research Database: Conference paper -- The final publication is available at Springer, see DOI link. |
| Language: | English |
| Identification Number: | |
| edoc DOI: | |
| Last Modified: | 11 Feb 2022 18:45 |
| Deposited On: | 09 Mar 2018 15:38 |
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