SoCS: A Mathematical Framework for Modeling Behavior of Diverse Groups

University Of Southern California, Los Angeles CA

Investigators

Abstract

The Social Web has become an important medium for social interaction and potentially a powerful new computational tool. As people create and share information online, their collective activity shapes the structure and usefulness of the Social Web and can even be used to address a range of problems from collective decision-making to trend prediction. Understanding how the aggregate activity of many interconnected people evolves is crucial to our ability to transform the Social Web into a platform for social computing. Mathematical modeling is a powerful tool for studying collective human activity. In previous work, the PI and collaborators developed a framework for mathematically modeling emergent behavior of groups of users on the Social Web. This framework allowed the modeler to relate aggregate behavior of a group of users to simple descriptions of their individual behavior. However, it failed to take into account key aspects of the Social Web: user diversity and the extent to which social links indicate a commonality of users' interests. The goal of this project is to develop a methodology for modeling diverse groups of users on the Social Web and to understand how user heterogeneity affects group behavior. Mathematical modeling and analysis will lead to better, more effective Web sites by identifying productive ways to display information to users, as well as techniques for promoting collaboration and enhancing participation. Analysis will also lead to new insights into how to use human activity for computation, and eventually a programming toolkit for social computing.