Information-theoretic approach to network modularity.
Exploiting recent developments in information theory, we propose, illustrate, and validate a principled information-theoretic algorithm for module discovery and the resulting measure of network modularity. This measure is an order parameter (a dimensionless number between 0 and 1). Comparison is made with other approaches to module discovery and to quantifying network modularity (using Monte Carlo generated Erdös-like modular networks). Finally, the network information bottleneck (NIB) algorithm is applied to a number of real world networks, including the "social" network of co-authors at the 2004 APS March Meeting.
Ziv
Etay
E
College of Physicians & Surgeons, Department of Biomedical Engineering, Columbia University, New York, New York 10027, USA.
Middendorf
Manuel
M
Wiggins
Chris H
CH
D000465:Algorithms; D018407:Bacterial Physiological Phenomena; D001703:Biophysics / Q000379:methods*; D003198:Computer Simulation; D004926:Escherichia coli / Q000502:physiology; D015233:Models, Statistical; D009010:Monte Carlo Method; D016571:Neural Networks, Computer; D013597:Systems Analysis; D013598:Systems Theory; D014158:Transcription, Genetic