Mark Newman, "Community structure in social, biological, and information networks" February 1, 2006

Thursday, February 2, 2006
Noon - 1 pm
411 West Hall

Our first speaker will be Prof. Mark Newman from the Department of
Physics and the Center for the Study of Complex Systems at the
University of Michigan, and he will talk about:

"Community structure in social, biological, and information networks"

Many networks show "community structure," meaning that they divide
naturally into tightly knit groups or communities, with many connections
between members of the same community and fewer connections between
members of different community. There is a long history, particularly in
the social sciences, of research on the problem of uncovering such
structure in real-world networks. This problem is also related to,
though distinct from, the problem of "graph partitioning" in computer
science. Using a selection of examples drawn from social,
informational, and biological networks, I will in this talk outline some
of the historical approaches to the community structure problem, and
then talk about some recent developments by my group and others that
show promise for the understanding of community structure in the large
network datasets that have started to appear in the last few years.

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Mark Newman received his Ph.D. in theoretical physics from the
University of Oxford in 1991. After doing postdoctoral work at Cornell
University, he joined the faculty of the Santa Fe Institute in New
Mexico, where he was a research professor until moving to the University
of Michigan in 2002. He is currently Associate Professor of Physics and
Complex Systems at Michigan, holding a joint appointment in the Physics
Department and the Center for the Study of Complex Systems. His
research focuses on the structure and dynamics of networked systems such
as social networks and computer networks.

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