Virality over YouTube: an empirical analysis

Purpose: The purpose of this research is to seek reasons for some videos going viral over YouTube (a type of social media platform). Methodology:Using YouTube APIs (Application Programming Interface) and Webometrics analyst tool, we collected data on about 100 all-time-most-viewed YouTube videos and information about the users associated with the videos. We constructed and tested an empirical model to understand the relationship among users‘ social and non-social capital—user age, gender, view count, subscriber, join date, total videos posted, video characteristics—postdate, 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 (PLS) and Webometric analysis was used to explore the association among the constructs. Main findings: Among other findings, our results showed that popularity of the videos was not only the function of YouTube system per se, 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. Originality: We for the first time constructed and tested an empirical model to find out the determinants of viral phenomenon over YouTube.