{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T16:54:19Z","timestamp":1732035259677},"reference-count":48,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2014,9,30]],"date-time":"2014-09-30T00:00:00Z","timestamp":1412035200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,9,30]]},"abstract":"Purpose<\/jats:title>\u2013 The purpose of this paper is to seek reasons for some videos going viral over YouTube (a type of social media platform).<\/jats:p><\/jats:sec>Design\/methodology\/approach<\/jats:title>\u2013 Using YouTube APIs (Application Programming Interface) and Webometrics analyst tool, the authors collected data on about 100 all-time-most-viewed YouTube videos and information about the users associated with the videos. The authors constructed and tested an empirical model to understand the relationship among users\u2019 social and non-social capital (e.g. User Age, Gender, View Count, Subscriber, Join Date, Total Videos Posted), video characteristics (Post Date, Duration, and Video Category), external network capital (in-links and hit counts), and Virality (Likes, Dislikes, Favorite Count, View Count, and Comment Count). Partial least square and Webometric analysis was used to explore the association among the constructs.<\/jats:p><\/jats:sec>Findings<\/jats:title>\u2013 Among other findings, the results showed that popularity of the videos was not only the function of YouTube systemper se<\/jats:italic>, but that network dynamics (e.g. in-links and hits counts) and offline social capital (e.g. fan base and fame) play crucial roles in the viral phenomenon, particularly view count.<\/jats:p><\/jats:sec>Originality\/value<\/jats:title>\u2013 The authors for the first time constructed and tested an empirical model to find out the determinants of viral phenomenon over YouTube.<\/jats:p><\/jats:sec>","DOI":"10.1108\/intr-05-2013-0085","type":"journal-article","created":{"date-parts":[[2014,9,25]],"date-time":"2014-09-25T11:48:14Z","timestamp":1411645694000},"page":"629-647","source":"Crossref","is-referenced-by-count":85,"title":["Virality over YouTube: an empirical analysis"],"prefix":"10.1108","volume":"24","author":[{"given":"Gohar","family":"Feroz Khan","sequence":"first","affiliation":[]},{"given":"Sokha","family":"Vong","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020122903171718500_b1","doi-asserted-by":"crossref","unstructured":"Adler, P.S. and Kwon, S.-W. 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