Topic modeling looks at patterns of keywords that frequently occur together in a set of documents. They trained and compared topic models using "Latent Dirichlet Allocation," "Correlated Topic Models," "Hierarchical Dirichlet Process," and a range of other topics between five and fifty.

They found similar results in topic contents and Wikipedia coverage of these topics across models and multiple runs.