R/sentomeasures_methods.R
scale.sento_measures.Rd
Scales and centers the sentiment measures from a sento_measures
object, column-per-column. By default,
the measures are normalized. NA
s are removed first.
# S3 method for sento_measures scale(x, center = TRUE, scale = TRUE)
x | a |
---|---|
center | a |
scale | a |
A modified sento_measures
object, with the measures replaced by the scaled measures as well as updated
statistics.
If one of the arguments center
or scale
is a matrix
, this operation will be applied first,
and eventual other centering or scaling is computed on that data.
Samuel Borms
data("usnews", package = "sentometrics") data("list_lexicons", package = "sentometrics") data("list_valence_shifters", package = "sentometrics") set.seed(505) # construct a sento_measures object to start with corpus <- sento_corpus(corpusdf = usnews) corpusSample <- quanteda::corpus_sample(corpus, size = 500) l <- sento_lexicons(list_lexicons[c("LM_en", "HENRY_en")]) ctr <- ctr_agg(howTime = c("equal_weight", "linear"), by = "year", lag = 3) sento_measures <- sento_measures(corpusSample, l, ctr) # scale sentiment measures to zero mean and unit standard deviation sc1 <- scale(sento_measures) n <- nobs(sento_measures) m <- nmeasures(sento_measures) # subtract a matrix sc2 <- scale(sento_measures, center = matrix(runif(n * m), n, m), scale = FALSE) # divide every row observation based on a one-column matrix, then center sc3 <- scale(sento_measures, center = TRUE, scale = matrix(runif(n)))