Speaker:
Date of Talk:
9/9/10
Affiliation:
Department of Computer Science, University of Colorado-Boulder
Title:
The Trouble with Community Detection
Abstract
Modular structures in complex networks can be extremely important for understanding the functional, dynamical and evolutionary 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 so-called "community detection" algorithms. These techniques, however, 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.
