The Social Web (a.k.a. Web 2.0) has transformed the Web into a dynamic medium and potentially a powerful new computational tool. As people interact online, their collective activity is becoming increasingly more complex and dynamic, often resulting in qualitatively new behaviors.
While the behavior of individuals is exceedingly complex and unpredictable, the combined activities of many people often lead to remarkably robust aggregate behaviors. I describe a general stochastic processes-based approach to modeling user-contributory web sites, where users create, rate and share content. These models describe aggregate measures of activity and how they arise from simple models of individual users. I illustrate this modeling approach in the context of user-created content on the news portal Digg.