Identifying community structure can be used as a potent tool in the analysis and understanding of the structure of complex networks. Up to now, methods for evaluating the performance of identification algorithms have used ad hoc networks with communities of equal size. We show that inhomogeneities in community sizes can and do affect the performance of algorithms considerably, and propose an alternative method which takes these factors into account. Furthermore, we propose a simple modification of the algorithm proposed by Newman for community detection (2004 Phys. Rev. E 69 066133) which treats communities of different sizes on an equal footing, and show that it outperforms the original algorithm while retaining its speed.
|Journal||Journal of Statistical Mechanics: Theory and Experiment|
|Publication status||Published - 1 Nov 2006|
- Analysis of algorithms
- Network dynamics