Stochastic Models of Large-Scale Human Behavior on the Web

Kristina Lerman, Tad Hogg

We describe stochastic models of user-contributory web sites, where users create, rate and share the content. These models describe how aggregate measures of activity arise from simple models of individual users. This approach provides a tractable, approximate method to understand user activity on the web site and how this activity depends on web site design choices, such as what information on other users' behaviors is shown to each user. We illustrate this approach in the context of user-created content on the news rating site, Digg.

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