Virality over YouTube: an empirical analysis. Issue 5 (30th September 2014)

• Record Type: Journal Article
• Authors: Feroz Khan, Gohar; Vong, Sokha
• Is Part Of: Internet research. Volume 24:Issue 5(2014)
• Page Start: 629
• Page End: 647
• Publication Date: 2014-09-30
• Subjects: Internet -- Periodicals; Computer networks -- Periodicals; 004.678
• DOI: 10.1108/IntR-05-2013-0085
• Languages: English
• ISSNs: 1066-2243

Abstract

<abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – The purpose of this paper is to seek reasons for some videos going viral over YouTube (a type of social media platform). </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – 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' 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. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – Among other findings, the results showed that popularity of the videos was not only the function of YouTube system <italic>per se</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. </p> </sec> <sec> <title content-type="abstract-heading">Originality/value</title> <p> – The authors for the first time constructed and tested an empirical model to find out the determinants of viral phenomenon over YouTube.</p> </sec> </abstract>