Top terms per topic, with their numeric scores (tidy)

Like label_topics() but returns the values behind the ranking, not just the words — e.g. the numeric FREX score per top term (stm issue #265).

Usage

topic_terms(
  model,
  n = 7L,
  by = c("prob", "frex", "lift", "score"),
  frexweight = 0.5
)

Arguments

model

A faSTM fit.

n

Terms per topic.

by

Ranking measure: "prob", "frex", "lift", or "score".

frexweight

FREX frequency/exclusivity weight (used when by = "frex").

Value

A tidy data.frame with topic, rank, term, score, measure.