Dynamical clustering methods to find community structures

We introduce an efficient method for the detection and identification of community structures in complex networks, based on the cluster de-synchronization properties of phase oscillators. The performance of the algorithm is tested on computer generated and real-world networks whose community structure is already known or has been studied by means of other methods. The algorithm attains a high level of precision, especially when the communities are very mixed and hardly detectable by the other methods, with a computational effort ${\cal O}(KN)$ on a generic graph with $N$ nodes and $K$ links.