Plot Per-Document Per-Topic Probabilities

This function generates a bar plot showing the prevalence of each topic across all documents.

Usage

topic_probability_plot(
  stm_model,
  top_n = 10,
  height = 800,
  width = 1000,
  verbose = TRUE,
  ...
)

Arguments

stm_model

A fitted STM model object. where stm_model is a fitted Structural Topic Model created using stm::stm().

top_n

The number of topics to display, ordered by their mean prevalence.

height

The height of the resulting Plotly plot, in pixels (default: 800).

width

The width of the resulting Plotly plot, in pixels (default: 1000).

verbose

Logical, if TRUE, prints progress messages.

...

Further arguments passed to tidytext::tidy.

Value

A ggplot object showing a bar plot of topic prevalence. Topics are ordered by their mean gamma value (average prevalence across documents).

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)

 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)

topic_probability_plot <- TextAnalysisR::topic_probability_plot(
 stm_model= stm_15,
 top_n = 10,
 height = 800,
 width = 1000,
 verbose = TRUE)

print(topic_probability_plot)
}