R/optimal_topics.R

In williamcsevier/textclass: Analytical Tool for Automated Text Analysis with Interpretable Graphical Output

#' @title Determine Optimal Topics
#'
#' @description This function allows you to analyze document term matrix for latent structures
#' @param dtm document-term matrix
#' @keywords optimal lda topics
#' @export
#' @examples
#' optimal_topics(dtm)

optimal_topics <- function(dtm){
  result <- FindTopicsNumber(
    dtm,
    topics = seq(from = 2, to = 30, by = 1),
    metrics = c("CaoJuan2009", "Deveaud2014"),
    method = "Gibbs",
    control = list(seed = 1234),
    mc.cores = 2L, #make sure this is appropriate number of cores you wish to use
    verbose = TRUE
  )
  values <- results
  # normalize to [0,1]
  columns <- base::subset(values, select = 2:ncol(values))
  values <- base::data.frame(
    values["topics"],
    base::apply(columns, 2, function(column) {
      scales::rescale(column, to = c(0, 1), from = range(column))
    })
  )
  return(values)
}