  This paper introduces a novel approach for modeling a set of directed, binary
networks in the context of cognitive social structures (CSSs) data. We adopt a
relativist approach in which no assumption is made about the existence of an
underlying true network. More specifically, we rely on a generalized linear
model that incorporates a bilinear structure to model transitivity effects
within networks, and a hierarchical specification on the bilinear effects to
borrow information across networks. This is a spatial model, in which the
perception of each individual about the strength of the relationships can be
explained by the perceived position of the actors (themselves and others) on a
latent social space. A key goal of the model is to provide a mechanism to
formally assess the agreement between each actors' perception of their own
social roles with that of the rest of the group. Our experiments with both real
and simulated data show that the capabilities of our model are comparable with
or, even superior to, other models for CSS data reported in the literature.
