The proposed model is a mixture model with multinomial distributions as component models (i.e., models of topics), similar to Probabilistic Latent Semantic Analysis (Hofmann, 1999).
the main difference is that the component word distributions (i.e., component language models) are all assumed to be known in our model, and they are designed to model the two types of language used in a humorous text, including 1) the general background model estimated using all the reviews, and 2) the reference language models of all the topical aspects covered in the review that capture the typical words used when each of the covered aspects is discussed.