Speaker
Prof.
Aaron Clauset
(University of Colorado)
Description
Modular structures in complex networks can be extremely
important for understanding the functional, dynamical,
evolutionary and robustness properties of networks, and are
widely believed to be ubiquitous in complex social,
biological and technological networks. Most of the empirical
evidence in support of the modular hypothesis, however, is
indirect and derived from "community" or module detection
algorithms. In general, however, these techniques do not
yield unambiguous results and their objective performance in
scientific contexts is not well understood. In this talk,
I'll discuss some of the problems with the existing popular
community detection frameworks and show that even in simple
contexts they can produce highly counter-intuitive results.
A consequence is that probably none of the existing claims
of modular structure in, for example, biological networks
should be trusted and there remains a great deal of work to
be done to test the modular-organization hypothesis in such
contexts. I'll conclude with some forward-looking thoughts
about the general problem of identifying network modules
from connectivity data alone, and the likelihood of
circumventing these problems using, for instance, notions of
functionality and robustness.
