plot.sento_measures: Plot sentiment measures

In sborms/sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

Description

Plotting method that shows all sentiment measures from the provided sento_measures object in one plot, or the average along one of the lexicons, features and time weighting dimensions.

Usage

## S3 method for class 'sento_measures'
plot(x, group = "all", ...)

Arguments

x	a sento_measures object created using sento_measures.
group	a value from c("lexicons", "features", "time", "all"). The first three choices display the average of all measures from the same group, in a different color. The choice "all" displays every single sentiment measure in a separate color, but this may look visually overwhelming very fast, and can be quite slow.
...	not used.

Value

Returns a simple ggplot object, which can be added onto (or to alter its default elements) by using the + operator (see example). By default, a legend is positioned at the top if there are at maximum twelve line graphs plotted and group is different from "all".

Author(s)

Samuel Borms

Examples

# construct a sento_measures object to start with
corpus <- sento_corpus(corpusdf = sentometrics::usnews)
corpusSample <- quanteda::corpus_sample(corpus, size = 500)
l <- sento_lexicons(sentometrics::list_lexicons[c("LM_en")],
                    sentometrics::list_valence_shifters[["en"]])
ctr <- ctr_agg(howTime = c("equal_weight", "linear"), by = "month", lag = 3)
sm <- sento_measures(corpusSample, l, ctr)

# plot sentiment measures
plot(sm, "features")

## Not run: 
# adjust appearance of plot
library("ggplot2")
p <- plot(sm)
p <- p +
  scale_x_date(name = "year", date_labels = "%Y") +
  scale_y_continuous(name = "newName")
p
## End(Not run)

sborms/sentometrics documentation built on Aug. 21, 2021, 6:40 a.m.