SPONGE: A generalized eigenproblem for clustering signed networks - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2019

SPONGE: A generalized eigenproblem for clustering signed networks


We introduce a principled and theoretically sound spectral method for k-way clustering in signed graphs, where the affinity measure between nodes takes either positive or negative values. Our approach is motivated by social balance theory, where the task of clustering aims to decompose the network into dis-joint groups, such that individuals within the same group are connected by as many positive edges as possible, while individuals from different groups are connected by as many negative edges as possible. Our algorithm relies on a generalized eigenproblem formulation inspired by recent work on constrained clustering. We provide theoretical guarantees for our approach in the setting of a signed stochastic block model, by leveraging tools from matrix perturbation theory and random matrix theory. An extensive set of numerical experiments on both synthetic and real data shows that our approach compares favorably with state-of-the-art methods for signed clustering , especially for large number of clusters and sparse measurement graphs.
Fichier principal
Vignette du fichier
418-supp.pdf (8.9 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02379505 , version 1 (25-11-2019)


  • HAL Id : hal-02379505 , version 1


Mihai Cucuringu, Peter Davies, Aldo Glielmo, Hemant Tyagi. SPONGE: A generalized eigenproblem for clustering signed networks. AISTATS, Apr 2019, Okinawa, Japan. ⟨hal-02379505⟩
39 View
51 Download


Gmail Facebook X LinkedIn More