Label topics by top words (prob, FREX, lift, score)
Usage
label_topics(model, n = 7L, frexweight = 0.5)
Arguments
- model
A faSTM fit.
- n
Number of words per topic per metric.
- frexweight
FREX frequency/exclusivity weight.
Value
A faSTM_labels object: per-metric top-word matrices (prob,
frex, lift, score), each topics × n.