Generate Topic Labels Using OpenAI's API

This function generates descriptive labels for each topic based on their top terms using OpenAI's ChatCompletion API.

Usage

generate_topic_labels(
  top_topic_terms,
  model = "gpt-3.5-turbo",
  system = NULL,
  user = NULL,
  temperature = 0.5,
  openai_api_key = NULL,
  verbose = TRUE
)

Arguments

top_topic_terms

A data frame containing the top terms for each topic.

model

A character string specifying which OpenAI model to use (default: "gpt-3.5-turbo").

system

A character string containing the system prompt for the OpenAI API. If NULL, the function uses the default system prompt.

user

A character string containing the user prompt for the OpenAI API. If NULL, the function uses the default user prompt.

temperature

A numeric value controlling the randomness of the output (default: 0.5).

openai_api_key

A character string containing the OpenAI API key. If NULL, the function attempts to load the key from the OPENAI_API_KEY environment variable or the .env file in the working directory.

verbose

Logical, if TRUE, prints progress messages.

Value

A data frame containing the top terms for each topic along with their generated labels.

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)

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

top_labeled_topic_terms <- TextAnalysisR::generate_topic_labels(
  top_topic_terms,
  model = "gpt-3.5-turbo",
  temperature = 0.5,
  openai_api_key = "your_openai_api_key",
  verbose = TRUE)
print(top_labeled_topic_terms)

# You can also load the Open AI API key from the .env file in the working directory as follows:
# OPENAI_API_KEY=your_openai_api_key

top_labeled_topic_terms <- TextAnalysisR::generate_topic_labels(
  top_topic_terms,
  model = "gpt-3.5-turbo",
  temperature = 0.5,
  verbose = TRUE)
print(top_labeled_topic_terms)
}