1. A computer-implemented method to identify groups in large networks, the method comprising: receiving a plurality of edges associated with the large networks; splitting the plurality of edges into a collection of fractions; generating, while refractioning and reclustering, one or more clusters from each fraction in the collection of fractions based on a similarity metric, wherein the similarity metric, ω(n 1 , n 2 ), between nodes or clusters n 1 and n 2 is ω ⁡ ( n ⁢ ⁢ 1 , n ⁢ ⁢ 2 ) = w n ⁢ ⁢ 1 ⁢ w n ⁢ ⁢ 2 + P 2 2 , wherein P 2 is the number of paths of length two between the two nodes or cluster n 1 and n 2 , w n1 is the weight of a first node or cluster, w n2 is the weight of a second node or cluster, and the weight is a count of the nodes in n 1 or n 2 ; and identifying a set of groups across the one or more clusters having nodes corresponding to a subset of the plurality of edges associated with the large networks.