Calculate a topic model
Calculate a topic model using Latent Dirichlet Allocation (LDA) or Correlated Topic Models (CTM), using the topicmodels package.
run_topic_model(dtm, type = "lda", n_topics = 5, iterations = 2000)
dtm |
a Document Term Matrix (DTM) |
type |
string specififying the type of model to run. Either 'lda' (the default) or 'ctm'. |
n_topics |
Number of topics to calculate |
iterations |
The number of iterations. Only relevant for LDA. |
A topic model with the specified parameters.
This is a basic wrapper function designed to allow consistent specification of model parameters within shiny apps.
make_dtm for constructing data to pass to this function; screen_topics for interactive visualisation of topic model results.
# import data file_location <- system.file( "extdata", "avian_ecology_bibliography.ris", package = "revtools" ) x <- read_bibliography(file_location) # run a topic model based on these data # note: the following lines can take a very long time to run, especially for large datasets! x_dtm <- make_dtm(x$title) ## Not run: x_lda <- run_topic_model(x_dtm, "lda", 5, 5000)
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