fit_term_usage: Computes speakers' term usage rates
In stylest: Estimating Speaker Style Distinctiveness

Computes speakers' term usage rates

fit_term_usage(
  x,
  speaker,
  terms,
  smooth,
  term_weights,
  fill_method,
  fill_weight,
  weight_varname
)

`x`	Text vector. May be a `corpus_frame` object
`speaker`	Vector of speaker labels. Should be the same length as `x`
`terms`	Vocabulary for document term matrix
`smooth`	Numeric value used smooth term frequencies
`term_weights`	Dataframe of distances (or any weights) per word in the vocab. This dataframe should have one column $word and a second column $weight_var containing the weight for the word
`fill_method`	if `"value"` (default), `fill_weight` is used to fill any terms with `NA` weight. If `"mean"`, the mean term_weight should be used as the fill value
`fill_weight`	numeric value to fill in as weight for any term which does not have a weight specified in `term_weights`
`weight_varname`	Name of the column in term_weights containing the weights

named list of: terms, vector of num tokens uttered by each speaker, smoothing value, term weights (NULL if no weights), terms whose weights were imputed (NULL if no term_weights=NULL), fill_weight used to fill missing weights (NULL if no term_weights=NULL), and (smoothed) term usage rate matrix

stylest documentation built on March 5, 2021, 1:05 a.m.