Select Top Terms for Each Topic — select_top_topic

This function selects the top terms for each topic based on their word probability distribution (beta).

Usage

select_top_topic_terms(stm_model, top_term_n = 10, verbose = TRUE, ...)

Arguments

stm_model: An STM model object.
top_term_n: The number of top terms to display for each topic (default: 10).
verbose: Logical, if TRUE, prints progress messages.
...: Further arguments passed to tidytext::tidy.

Value

A data frame containing the top terms for each topic.

Examples

if (interactive()) {
  df <- TextAnalysisR::SpecialEduTech

  united_tbl <- TextAnalysisR::unite_text_cols(df, listed_vars = c("title", "keyword", "abstract"))

  tokens <- TextAnalysisR::preprocess_texts(united_tbl, text_field = "united_texts")

  dfm_object <- quanteda::dfm(tokens)

  stm_15 <- TextAnalysisR::create_stm_model(
  dfm_object,
  topic_n = 15,
  max.em.its = 75,
  categorical_var = "reference_type",
  continuous_var = "year",
  verbose = TRUE
  )

  out <- quanteda::convert(dfm_object, to = "stm")

stm_15 <- stm::stm(
  data = out$meta,
  documents = out$documents,
  vocab = out$vocab,
  max.em.its = 75,
  init.type = "Spectral",
  K = 15,
  prevalence = ~ reference_type + s(year),
  verbose = TRUE)

top_topic_terms <- TextAnalysisR::select_top_topic_terms(
  stm_model = stm_15,
  top_term_n = 10,
  verbose = TRUE
  )
print(top_topic_terms)
}