Catching a Viral Video

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 You Tube by analyzing sharing and its relationship to...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Broxton, T, Interian, Y, Vaver, J, Wattenhofer, M
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 304
container_issue
container_start_page 296
container_title
container_volume
creator Broxton, T
Interian, Y
Vaver, J
Wattenhofer, M
description 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 You Tube by analyzing sharing and its relationship to video popularity using 1.5 million You Tube videos. The social ness 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 highly social videos behave differently 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.
doi_str_mv 10.1109/ICDMW.2010.160
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5693313</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5693313</ieee_id><sourcerecordid>5693313</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-59685ae000da021273fe1d9f1287b29b553d5b0c93e9fa8fbdbae2ca55b6bcaf3</originalsourceid><addsrcrecordid>eNo9jEtPwzAQhM1Loiq59sKlfyDF3s16s0cUKFQq4lLBsVrHNgSVh5Je-PeEhxhpZjT6pDFm5uzCOSsXq-bq7nEB9nt7e2AK4dqyF6qAmA_NBJCpFCA5-mGugqqS0XD8zxBOTTEML3YUATPTxMwa3bfP3dvTXOcPXa-7MWN6PzMnWXdDKv56ajbL601zW67vb1bN5brsxO5LEl-TpvEuqgUHjDm5KNlBzQEkEGGkYFvBJFnrHGLQBK0SBR9azTg157-3XUpp-9F3r9p_bskLokP8AtGePoU</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Catching a Viral Video</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Broxton, T ; Interian, Y ; Vaver, J ; Wattenhofer, M</creator><creatorcontrib>Broxton, T ; Interian, Y ; Vaver, J ; Wattenhofer, M</creatorcontrib><description>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 You Tube by analyzing sharing and its relationship to video popularity using 1.5 million You Tube videos. The social ness 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 highly social videos behave differently 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.</description><identifier>ISSN: 2375-9232</identifier><identifier>ISBN: 9781424492442</identifier><identifier>ISBN: 1424492440</identifier><identifier>EISSN: 2375-9259</identifier><identifier>EISBN: 9780769542577</identifier><identifier>EISBN: 0769542573</identifier><identifier>DOI: 10.1109/ICDMW.2010.160</identifier><language>eng</language><publisher>IEEE</publisher><subject>Blogs ; Facebook ; Media ; Twitter ; viral videos ; Watches ; YouTube</subject><ispartof>2010 IEEE International Conference on Data Mining Workshops, 2010, p.296-304</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5693313$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,27916,54911</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5693313$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Broxton, T</creatorcontrib><creatorcontrib>Interian, Y</creatorcontrib><creatorcontrib>Vaver, J</creatorcontrib><creatorcontrib>Wattenhofer, M</creatorcontrib><title>Catching a Viral Video</title><title>2010 IEEE International Conference on Data Mining Workshops</title><addtitle>icdmw</addtitle><description>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 You Tube by analyzing sharing and its relationship to video popularity using 1.5 million You Tube videos. The social ness 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 highly social videos behave differently 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.</description><subject>Blogs</subject><subject>Facebook</subject><subject>Media</subject><subject>Twitter</subject><subject>viral videos</subject><subject>Watches</subject><subject>YouTube</subject><issn>2375-9232</issn><issn>2375-9259</issn><isbn>9781424492442</isbn><isbn>1424492440</isbn><isbn>9780769542577</isbn><isbn>0769542573</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9jEtPwzAQhM1Loiq59sKlfyDF3s16s0cUKFQq4lLBsVrHNgSVh5Je-PeEhxhpZjT6pDFm5uzCOSsXq-bq7nEB9nt7e2AK4dqyF6qAmA_NBJCpFCA5-mGugqqS0XD8zxBOTTEML3YUATPTxMwa3bfP3dvTXOcPXa-7MWN6PzMnWXdDKv56ajbL601zW67vb1bN5brsxO5LEl-TpvEuqgUHjDm5KNlBzQEkEGGkYFvBJFnrHGLQBK0SBR9azTg157-3XUpp-9F3r9p_bskLokP8AtGePoU</recordid><startdate>201012</startdate><enddate>201012</enddate><creator>Broxton, T</creator><creator>Interian, Y</creator><creator>Vaver, J</creator><creator>Wattenhofer, M</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201012</creationdate><title>Catching a Viral Video</title><author>Broxton, T ; Interian, Y ; Vaver, J ; Wattenhofer, M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-59685ae000da021273fe1d9f1287b29b553d5b0c93e9fa8fbdbae2ca55b6bcaf3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Blogs</topic><topic>Facebook</topic><topic>Media</topic><topic>Twitter</topic><topic>viral videos</topic><topic>Watches</topic><topic>YouTube</topic><toplevel>online_resources</toplevel><creatorcontrib>Broxton, T</creatorcontrib><creatorcontrib>Interian, Y</creatorcontrib><creatorcontrib>Vaver, J</creatorcontrib><creatorcontrib>Wattenhofer, M</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Broxton, T</au><au>Interian, Y</au><au>Vaver, J</au><au>Wattenhofer, M</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Catching a Viral Video</atitle><btitle>2010 IEEE International Conference on Data Mining Workshops</btitle><stitle>icdmw</stitle><date>2010-12</date><risdate>2010</risdate><spage>296</spage><epage>304</epage><pages>296-304</pages><issn>2375-9232</issn><eissn>2375-9259</eissn><isbn>9781424492442</isbn><isbn>1424492440</isbn><eisbn>9780769542577</eisbn><eisbn>0769542573</eisbn><abstract>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 You Tube by analyzing sharing and its relationship to video popularity using 1.5 million You Tube videos. The social ness 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 highly social videos behave differently 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.</abstract><pub>IEEE</pub><doi>10.1109/ICDMW.2010.160</doi><tpages>9</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 2375-9232
ispartof 2010 IEEE International Conference on Data Mining Workshops, 2010, p.296-304
issn 2375-9232
2375-9259
language eng
recordid cdi_ieee_primary_5693313
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Blogs
Facebook
Media
Twitter
viral videos
Watches
YouTube
title Catching a Viral Video
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T01%3A57%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Catching%20a%20Viral%20Video&rft.btitle=2010%20IEEE%20International%20Conference%20on%20Data%20Mining%20Workshops&rft.au=Broxton,%20T&rft.date=2010-12&rft.spage=296&rft.epage=304&rft.pages=296-304&rft.issn=2375-9232&rft.eissn=2375-9259&rft.isbn=9781424492442&rft.isbn_list=1424492440&rft_id=info:doi/10.1109/ICDMW.2010.160&rft_dat=%3Cieee_6IE%3E5693313%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9780769542577&rft.eisbn_list=0769542573&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5693313&rfr_iscdi=true