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Broadcast yourself on YouTube: really?

Published: 31 October 2008 Publication History

Abstract

One essential reason for people to publish on the web is to express themselves freely. YouTube facilitates this self-expression by allowing users to upload video content they generated. This paper investigates to what extent the videos on YouTube are self-generated content, instead of amalgamated content that was mainly professionally authored in the first place. Results show that most of the popular content on YouTube was professionally generated, even though a random sample shows that there is plenty of user-generated content available -- it just does not make the cut. As a result we propose that YouTube is more of a social filter, allowing anyone to share content they find interesting rather than a way for aspiring creative people to show their creative abilities to the world. The outcome is a set of requirements which describe better means for YouTube to support better authoring and presentation of video, where the core research direction is focused on the self-representation of humans in the realm of their creative possibilities on one side as well as the stimulation of new insights on existing material to stimulate new creative impulses.

References

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Lee Gomes. Will all of us get our 15 minutes on a YouTube video? Wall Street Journal, August 2006.
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Alexa. youtube.com - Traffic Details from Alexa, February 2008.
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Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, and Sue Moon. I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system. In IMC '07: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, pages 1--14, San Diego, California, USA, 2007. ACM.
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Scott Woolley. Video fixation. Forbes, 178:100--106, October 2006
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Lev Grossman. Time's person of the year: You. Time Magazine, pages 38--41, December 2006. http://www.time.com/time/magazine/article/0,9171,1569514,00.html
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Accenture. User-generated content is top threat to media and entertainment industry. Accenture Newsroom, April 2007.
[7]
Candace Lombardi. YouTube cuts three content deals. CNet News.com, October 2006.
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RIPE NCC. YouTube Hijacking: A RIPE NCC RIS case study. RIPE News, February 2008. http://www.ripe.net/news/study-youtubehijacking.html.
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Matt Preprost. I Found Your Camera CBC Radio Interview Promo, February 2008.
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Pat Aufderheide and Peter Jaszi. Recut, reframe, recycle: Quoting copyrighted material in user-generated video. http://www.centerforsocialmedia.org/recut, January 2008.
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fistofblog. Star Wars according to a 3 year old., February 2008.

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  • (2021)Social Media User-Influencer CongruityInternational Journal of Customer Relationship Marketing and Management10.4018/IJCRMM.28921313:1(1-26)Online publication date: 15-Oct-2021
  • (2021)Near Duplicate Video Detection Algorithm Based on Gray-scale Pyramid and Temporal Features2021 7th International Conference on Big Data and Information Analytics (BigDIA)10.1109/BigDIA53151.2021.9619706(261-265)Online publication date: 29-Oct-2021
  • (2021)Streaming physical activity via social networks in times of lockdown: Between a desire to share and a search for visibilityLoisir et Société / Society and Leisure10.1080/07053436.2021.1935428(1-12)Online publication date: 27-Jul-2021
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    cover image ACM Conferences
    HCC '08: Proceedings of the 3rd ACM international workshop on Human-centered computing
    October 2008
    84 pages
    ISBN:9781605583204
    DOI:10.1145/1462027
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 31 October 2008

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    Author Tags

    1. search for video content
    2. user-generated content
    3. youtube

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    MM08
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    MM08: ACM Multimedia Conference 2008
    October 31, 2008
    British Columbia, Vancouver, Canada

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    Overall Acceptance Rate 48 of 81 submissions, 59%

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    Cited By

    View all
    • (2021)Social Media User-Influencer CongruityInternational Journal of Customer Relationship Marketing and Management10.4018/IJCRMM.28921313:1(1-26)Online publication date: 15-Oct-2021
    • (2021)Near Duplicate Video Detection Algorithm Based on Gray-scale Pyramid and Temporal Features2021 7th International Conference on Big Data and Information Analytics (BigDIA)10.1109/BigDIA53151.2021.9619706(261-265)Online publication date: 29-Oct-2021
    • (2021)Streaming physical activity via social networks in times of lockdown: Between a desire to share and a search for visibilityLoisir et Société / Society and Leisure10.1080/07053436.2021.1935428(1-12)Online publication date: 27-Jul-2021
    • (2021)What makes people watch online TV clips? An empirical investigation of survey data and viewing logsInternational Journal of Information Management10.1016/j.ijinfomgt.2021.10232959(102329)Online publication date: Aug-2021
    • (2021)Lifelogging meets alternate and cross-realities: an investigation into broadcasting personal visual realities to remote audiencesMultimedia Tools and Applications10.1007/s11042-021-11310-383:15(46707-46730)Online publication date: 14-Aug-2021
    • (2020)Social Media and Online Brand CommunitiesGlobal Branding10.4018/978-1-5225-9282-2.ch035(709-735)Online publication date: 2020
    • (2019)Volume and control: the transition from information to powerJournal of Multicultural Discourses10.1080/17447143.2019.1662028(1-18)Online publication date: 5-Sep-2019
    • (2018)YouTube channels, uploads and viewsConvergence: The International Journal of Research into New Media Technologies10.1177/135485651773697924:1(16-32)Online publication date: 10-Jan-2018
    • (2018)Near-duplicate Video Detection Algorithm Based on Global GSP Feature and Local ScSIFT Feature FusionJournal of Physics: Conference Series10.1088/1742-6596/960/1/012034960(012034)Online publication date: 12-Feb-2018
    • (2017)Exploring “User,” “Video,” and (Pseudo) Multi-Mode Networks on YouTube with NodeXLSocial Media Data Extraction and Content Analysis10.4018/978-1-5225-0648-5.ch009(242-295)Online publication date: 2017
    • Show More Cited By

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