I have a graph instance with weighted directed edges which values can be in range [-1,1]. I need to do clustering on this graph, in order to find out groups in which vertices are more correlated.
I searched for several clustering or community detection graph based algorithms, but most of them don't work because the negative weights. Up to now I have applied spinglass (it is so called in igraph library, it is an algorithm based on Potts model) algorithm which seems to work with both positive and negative weights.
Are there any other algorithms for doing clustering or community detection on graphs which have negative and positive edge weights?
Update: the edge weights represent correlations, 1 means that two vertices are strongly correlated, -1 that are inversely correlated and 0 means that are indipendent.