Alternative Title

Social Learning and Network Effects in Social Media: Evidence from YouTube

Publication Type

Journal Article

Publication Date

10-2015

Abstract

Recent years have witnessed an unprecedented explosion in information technology that enables dynamic diffusion of user-generated content in social networks. Online videos, in particular, have changed the landscape of marketing and entertainment, competing with premium content and spurring business innovations. In the present study, we examine how learning and network effects drive the diffusion of online videos. While learning happens through informational externalities, network effects are direct payoff externalities. Using a unique data set from YouTube, we empirically identify learning and network effects separately, and find that both mechanisms have statistically and economically significant effects on video views; furthermore, the mechanism that dominates depends on the specific video type. Specifically, although learning primarily drives the popularity of quality-oriented content, network effects make it also possible for attention-grabbing content to go viral. Theoretically, we show that, unlike the diffusion of movies, it is the combination of both learning and network effects that generate the multiplier effect for the diffusion of online videos. From a managerial perspective, providers can adopt different strategies to promote their videos accordingly, that is, signaling the quality or featuring the viewer base depending on the video type. Our results also suggest that YouTube can play a much greater role in encouraging the creation of original content by leveraging the multiplier effect.

Keywords

Learning, Network Effects, User-Generated Content, Social Contagion, Social Media

Discipline

Computer Sciences | Databases and Information Systems | Social Media

Research Areas

Information Systems and Management

Publication

Journal of Management Information Systems

Volume

32

Issue

4

First Page

78

Last Page

108

ISSN

0742-1222

Identifier

10.1080/07421222.2015.1138368

Publisher

Taylor & Francis (Routledge): SSH Titles

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1080/07421222.2015.1138368

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