This paper examines social learning and network effects that are particularly important for online videos, considering the limited marketing campaigns of user-generated content. Rather than combining both social learning and network effects under the umbrella of social contagion or peer influence, we develop a theoretical model and empirically identify social learning and network effects separately. Using a unique data set from YouTube, we find that both mechanisms have statistically and economically significant effects on video views, and which mechanism dominates depends on the specific video type.
Social Learning, Network Effects, User-Generated Content, Social Contagion, Social Media
Communication Technology and New Media | Databases and Information Systems
Data Management and Analytics
Workshop on Information Systems and Economics, 19-20 December, Milan
City or Country
QIU, Liangfei; TANG, Qian; and Whinston, Andrew B..
Two Formulas for Success in Social Media: Social Learning and Network Effects. (2013). Workshop on Information Systems and Economics, 19-20 December, Milan. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2195
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.