paper: DeltaLDA

DeltaLDA is a modification of the Latent Dirichlet Allocation (LDA) model which uses two different topic mixing weight priors to jointly model two corpora with a shared set of topics, where one topic mixing weight prior to model the normal pattern and the other for the abnormal pattern.
The graphical model:

An illustration of topic mixture weights in two scenarios:

This looks like quite similar to the Adapted Vocabularies for Generic Visual Categorization, ECCV 2006 in the way they split the topic/vocabulary into two sets, though there are fundamental difference in their underneath mechanism.