Shakeri, HemanPoggi-Corradini, PietroAlbin, NathanScoglio, Caterina2017-11-302017-11-302017-01-17http://hdl.handle.net/2097/38365Citation: Shakeri, H., Poggi-Corradini, P., Albin, N., & Scoglio, C. (2017). Network clustering and community detection using modulus of families of loops. Physical Review E, 95(1), 7. doi:10.1103/PhysRevE.95.012316We study the structure of loops in networks using the notion of modulus of loop families. We introduce an alternate measure of network clustering by quantifying the richness of families of (simple) loops. Modulus tries to minimize the expected overlap among loops by spreading the expected link usage optimally. We propose weighting networks using these expected link usages to improve classical community detection algorithms. We show that the proposed method enhances the performance of certain algorithms, such as spectral partitioning and modularity maximization heuristics, on standard benchmarks.This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).Complex NetworksModelPhysicsText