Impact of social network structure on content propagation: A study using YouTube data

We study how the size and structure of the local network around a node affects the aggregate diffusion of products seeded by it. We examine this in the context of YouTube, the popular video-sharing site. We address the endogeneity problems common to this setting by using a rich dataset and a careful estimation methodology. We empirically demonstrate that the size and structure of an author's local network is a significant driver of the popularity of videos seeded by her, even after controlling for observed and unobserved video characteristics, unobserved author characteristics, and endogenous network formation. Our findings are distinct from those in the peer effects literature, which examines neighborhood effects on individual behavior, since we document the causal relationship between a node's local network position and the global diffusion of products seeded by it. Our results provide guidelines for identifying seeds that provide the best return on investment, thereby aiding managers conducting buzz marketing campaigns on social media forums. Further, our study sheds light on the other substantive factors that affect video consumption on YouTube.