  We introduce the identity labeling problem - given an individual in a social
situation, can we predict what identity(ies) they will be labeled with by
someone else? This problem remains a theoretical gap and methodological
challenge, evidenced by the fact that models of social-cognition often sidestep
the issue by treating identities as already known. We build on insights from
existing models to develop a new framework, entitled Latent Cognitive Social
Spaces, that can incorporate multiple social cues including sentiment
information, socio-demographic characteristics, and institutional associations
to estimate the most culturally expected identity. We apply our model to data
collected in two vignette experiments, finding that it predicts identity
labeling choices of participants with a mean absolute error of 10.9%, a 100%
improvement over previous models based on parallel constraint satisfaction and
affect control theory.
