Swarthmore College Department of Computer Science

Talk by Jennifer Neville of Purdue University

Modeling and Mining Social Networks
Wednesday, March 23, 2011
4:00 pm, Bryn Mawr College, Park 243

Abstract

In the past decade, we have witnessed an explosive growth in the use of the Web and online communities. This has lead to increased interest in mining the resulting social network data, both to advance understanding of human behavior and to exploit the underlying social processes for decision-making. In complex network domains (e.g., communication, friendship, and organizational networks), the relationships are a critical source of information that identify potential statistical dependencies among individuals. These dependencies among linked entities present an opportunity to improve predictions about the properties of individuals, as birds of a feather do indeed flock together. For example, when deciding how to market a product to people in Facebook or LinkedIn, it may be helpful to consider whether a person's friends are likely to purchase/adopt the product.

Bio: Jennifer Neville is an assistant professor at Purdue University with a joint appointment in the Departments of Computer Science and Statistics. She received her PhD from the University of Massachusetts Amherst in 2006. She received a DARPA IPTO Young Investigator Award in 2003 and was selected as a member of the DARPA Computer Science Study Group in 2007. In 2008, she was chosen by IEEE as one of "AI's 10 to watch." Her research focuses on developing data mining and machine learning techniques for relational domains, including citation analysis, fraud detection, and social network analysis.

This talk is presented by the FLICS Program: Fantastic Lectures in Computer Science, jointly hosted by: Bryn Mawr College, Haverford College, Swarthmore College, and Villanova University.