Stochastic Models of User-Contributory Web Sites

TL;DR

This paper introduces a stochastic modeling framework for user-contributory websites, capturing how individual user behaviors aggregate to influence overall activity and how design choices impact engagement.

Contribution

It presents a novel stochastic process-based approach to model and analyze user activity and design effects on contributory web sites.

Findings

Model effectively captures aggregate user activity.

Design choices significantly influence user engagement.

Applicable to platforms like Digg.

Abstract

We 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. This approach provides a tractable method to understand user activity on the web site and how this activity depends on web site design choices, especially the choice of what information about other users' behaviors is shown to each user. We illustrate this modeling approach in the context of user-created content on the news rating site Digg.