  This article presents the results of investigations using topic modeling of
the Voynich Manuscript (Beinecke MS408). Topic modeling is a set of
computational methods which are used to identify clusters of subjects within
text. We use latent dirichlet allocation, latent semantic analysis, and
nonnegative matrix factorization to cluster Voynich pages into `topics'. We
then compare the topics derived from the computational models to clusters
derived from the Voynich illustrations and from paleographic analysis. We find
that computationally derived clusters match closely to a conjunction of scribe
and subject matter (as per the illustrations), providing further evidence that
the Voynich Manuscript contains meaningful text.
