Identify semantic topics by clustering embeddings and extracting
representative keywords from each cluster.
Usage
hf_extract_topics(data, text_col = "text", k = 5, top_n = 10)
Arguments
- data
A data frame with text and embeddings.
- text_col
Character string. Name of text column.
- k
Integer. Number of topics/clusters. Default: 5.
- top_n
Integer. Number of top words per topic. Default: 10.
Value
A tibble with topics and their top terms.
Examples
if (FALSE) { # \dontrun{
library(tidytext)
# Extract topics
topics <- docs_embedded |>
hf_extract_topics(text_col = "text", k = 3, top_n = 5)
} # }
