UIUC Computer Science Department
University of Illinois at Urbana-Champaign
 A Framework for Analysis of Dynamic Social Networks
  
  Speaker  Tanya Berger-Wolf
    
 Date Sep 27, 2006
    
 Time 4:00 pm  
    
 Location SC 4403
    
 Sponsor DAIS
    
 Event type Seminar
    
 Original Calendar 
    
 Views 47
    
 
 
Abstract<br> Finding patterns of social interaction within a population has wide-ranging applications including: disease modeling, cultural and information transmission, phylogeography, conservation, and behavioral ecology. Social interactions are often modeled with networks. A key characteristics of social interactions is their continual change. However, most past analyses of social networks are essentially static in that all information about the time that social interactions take place is discarded. I will present a new mathematical and computational framework that enables analysis of dynamic social networks and that explicitly makes use of information about when social interactions occur. I will discuss several algorithms for obtaining information about the structure of dynamic social networks in this framework and pose many open questions. The research is joint work with J. Saia (UNM), D.I.Rubenstein, S. Sundaresan, and I. Fischoff (Princeton) <p> Bio: Dr. Tanya Berger-Wolf is an assistant professor at the Department of Computer Science at the University of Illinois at Chicago. Her research is in applications of algorithmic and data mining techniques to population biology, both human (epidemiology) and animal, from genetics to social interactions. Dr. Berger-Wolf has received her B.Sc. in Computer Science and Mathematics from Hebrew University (Jerusalem, Israel) in 1995 and her Ph.D. in Computer Science from University of Illinois at Urbana-Champaign in 2002. She has spent two years as a postdoctoral fellow at the University of New Mexico working in computational phylogenetics and a year at the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) doing research in computational epidemiology.
 
 
September 2006
S M T W T F S

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