plotArea: Plotting topics over time as stacked areas below plotted lines.

Description

Creates a stacked area plot of all or selected topics.

Usage

plotArea(
  ldaresult,
  ldaID,
  select = NULL,
  tnames = NULL,
  threshold = NULL,
  meta,
  unit = "quarter",
  xunit = "year",
  color = NULL,
  sort = TRUE,
  legend = NULL,
  legendLimit = 0,
  peak = 0,
  file
)

Value

List of two matrices. rel contains the topic proportions over time, relcum contains the cumulated topic proportions

Arguments

ldaresult: LDA result object
ldaID: Character vector including IDs of the texts
select: Selects all topics if parameter is null. Otherwise vector of integers or topic label. Only topics belonging to that numbers, and labels respectively would be plotted.
tnames: Character vector of topic labels. It must have same length than number of topics in the model.
threshold: Numeric: Treshold between 0 and 1. Topics would only be used if at least one time unit exist with a topic proportion above the treshold
meta: The meta data for the texts or a date-string.
unit: Time unit for x-axis. Possible units are "bimonth", "quarter", "season", "halfyear", "year", for more units see round_date
xunit: Time unit for tiks on the x-axis. For possible units see round_date
color: Color vector. Color vector would be replicated if the number of plotted topics is bigger than length of the vector.
sort: Logical: Should the topics be sorted by topic proportion?
legend: Position of legend. If NULL (default), no legend will be plotted
legendLimit: Numeric between 0 (default) and 1. Only Topics with proportions above this limit appear in the legend.
peak: Numeric between 0 (default) and 1. Label peaks above peak. For each Topic every area which are at least once above peak will e labeled. An area ends if the topic proportion is under 1 percent.
file: Character: File path if a pdf should be created

Details

This function is useful to visualize the volume of topics and to show trends over time.

Examples

Run this code

if (FALSE) {
data(politics)
poliClean <- cleanTexts(politics)
words10 <- makeWordlist(text=poliClean$text)
words10 <- words10$words[words10$wordtable > 10]
poliLDA <- LDAprep(text=poliClean$text, vocab=words10)
LDAresult <- LDAgen(documents=poliLDA, K=10, vocab=words10)
plotArea(ldaresult=LDAresult, ldaID=names(poliLDA), meta=politics$meta)

plotArea(ldaresult=LDAresult, ldaID=names(poliLDA), meta=politics$meta, select=c(1,3,5))
}