Community detection with node attributes in multilayer networks.

ABSTRACT: Community detection in networks is commonly performed using information about interactions between nodes. Recent advances have been made to incorporate multiple types of interactions, thus generalizing standard methods to multilayer networks. Often, though, one can access additional information regarding individual nodes, attributes, or covariates. A relevant question is thus how to properly incorporate this extra information in such frameworks. Here we develop a method that incorporates both the topology of interactions and node attributes to extract communities in multilayer networks. We propose a principled probabilistic method that does not assume any a priori correlation structure between attributes and communities but rather infers this from data. This leads to an efficient algorithm

SUBMITTER: Contisciani M 

PROVIDER: S-EPMC7519123 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature