Seeded Topic Models as a Yard Stick: Implement them in R with keyATM

Modelling geopolitical risk based on UK parliament transcripts

In text analysis, topic models are a prominent approach to extract overall themes from large collections of documents. Maybe the most widely used model in this domain is the Latent Dirichlet Allocation (LDA).

LDA is a probabilistic topic model, and exists in many variations. Today we will look at one of these: The seeded LDA model.

A seeded topic model allows the researcher to pass a collection …

data science lda semi-supervised learning text-mining topic modeling