Online Community and User-Generated Content: Understanding the Role of Social Networks

Models of user generated content (UGC) creation such as Facebook, MySpace, and YouTube are facing robust growth accelerated by the adoption of Web 2.0 technologies and standards. These business models offer a fascinating avenue for exploring the role of social influence online. This dissertation is motivated by the success of YouTube, which is attractive to content creators as well as corporations for its potential to rapidly disseminate digital content. The networked structure of interactions on YouTube and the tremendous variation in the success of videos posted online lends itself to an inquiry of the role of social influence. Using a unique data set of video information and user information collected from YouTube, I find that social interactions are influential not only in determining which videos become successful, but also on the magnitude of that impact.;Also found is the evidence for a number of mechanisms by which social influence is transmitted, such as (i) a preference for conformity, and (ii) the role of social networks in guiding opinion formation and directing content search and discovery. Econometrically, the problem in identifying social influence is that individuals' choices depend on the choices of other individuals, referred to as the 'reflection problem'. Another problem in identification is to distinguish between social contagion and user heterogeneity in the diffusion process. The results are in sharp contrast to earlier models of diffusion such as the Bass model that do not distinguish between different social processes that are responsible for the process of diffusion.;The research in this dissertation also attempts to quantify the impact of interactions structured through a social network in triggering cascades. Social network structures on YouTube could influence the formation and propagation of informational cascades that lead to the phenomenal popularity of some videos. In particular, I examine the informational cascade created by conversations structured through a social network early in the life of a video. The mechanism by which cascades are initiated and propagated is through word of mouth among cohesive groups. In other words, network structure impacts not only the formation but also the magnitude of online informational cascades.