On the equivalence of the label propagation method of community detection and a Potts model approach

We show that the recently introduced label propagation method for detecting communities in complex networks is equivalent to finding the local minima of a simple Potts model. Applying to empirical data, the number of such local minima was found to be very high, much larger than the number of nodes in the graph. The aggregation method for combining information from more local minima shows a tendency to fragment the communities into very small pieces.