LATENT SPACE MODELS FOR MULTIVIEW NETWORK DATA.

ABSTRACT: Social relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (e.g., an individual will not trust all of his/her acquaintances). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper, we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks [see, e.g., J. Amer. Statist. Assoc.97</

SUBMITTER: Salter-Townshend M 

PROVIDER: S-EPMC5927604 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature