Why some content go viral on social media? (Under Review)

Khan, G.F., & Sokha, V.

Abstract
In this research, we sought reasons for some content (mainly videos) going viral on social media. Using YouTube APIs 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 network characteristics (e.g. user age, gender, location, view count, subscriber, join date, total videos posted), video characteristics (post date, duration, and type), external network capital (in-links and hit counts), and viral constructs (likes, dislikes, favorite count, view count, and comment count) . SPSS correlations, multiple regression analysis, and Webometric analysis were used to explore the association among the constructs. Among other findings, our results show that popularity of the videos was not only the function of YouTube system par 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.