plotWordSub: Plotting Counts/Proportion of Words/Docs in LDA-generated...

In tosca: Tools for Statistical Content Analysis

Description

Creates a plot of the counts/proportion of words/docs in corpora which are generated by a ldaresult. Therefore an article is allocated to a topic - and then to the topics corpus - if there are enough (see limit and alloc) allocations of words in the article to the corresponding topic. Additionally the corpora are reduced by filterWord and a search-argument. The plot shows counts of subcorpora or if rel = TRUE proportion of subcorpora to its corresponding whole corpus.

Usage

plotWordSub(
  object,
  ldaresult,
  ldaID,
  limit = 10,
  alloc = c("multi", "unique", "best"),
  select = 1:nrow(ldaresult$document_sums),
  tnames,
  search,
  ignore.case = TRUE,
  type = c("docs", "words"),
  rel = TRUE,
  mark = TRUE,
  unit = "month",
  curves = c("exact", "smooth", "both"),
  smooth = 0.05,
  main,
  xlab,
  ylab,
  ylim,
  both.lwd,
  both.lty,
  col,
  legend = "topright",
  natozero = TRUE,
  file,
  ...
)

Arguments

object	textmeta object with strictly tokenized text component (character vectors) - such as a result of cleanTexts
ldaresult	The result of a function call LDAgen
ldaID	Character vector of IDs of the documents in ldaresult
limit	Integer/numeric: How often a word must be allocated to a topic to count these article as belonging to this topic - if 0<limit<1 proportion is used (default: 10)?
alloc	Character: Should every article be allocated to multiple topics ("multi"), or maximum one topic ("unique"), or the most represantative - exactly one - topic ("best") (default: "multi")? If alloc = "best" limit has no effect.
select	Integer vector: Which topics of ldaresult should be plotted (default: all topics)?
tnames	Character vector of same length as select - labels for the topics (default are the first returned words of top.topic.words from the lda package for each topic)
search	See filterWord
ignore.case	See filterWord
type	Character: Should counts/proportion of documents, where every "docs" or words "words" be plotted (default: "docs")?
rel	Logical. Should counts (FALSE) or proportion (TRUE) be plotted (default: TRUE)?
mark	Logical: Should years be marked by vertical lines (default: TRUE)?
unit	Character: To which unit should dates be floored (default: "month")? Other possible units are "bimonth", "quarter", "season", "halfyear", "year", for more units see round_date
curves	Character: Should "exact", "smooth" curve or "both" be plotted (default: "exact")?
smooth	Numeric: Smoothing parameter which is handed over to lowess as f (default: 0.05)
main	Character: Graphical parameter
xlab	Character: Graphical parameter
ylab	Character: Graphical parameter
ylim	Graphical parameter (default if rel = TRUE: c(0, 1))
both.lwd	Graphical parameter for smoothed values if curves = "both"
both.lty	Graphical parameter for smoothed values if curves = "both"
col	Graphical parameter, could be a vector. If curves = "both" the function will for every wordgroup plot at first the exact and then the smoothed curve - this is important for your col order.
legend	Character: Value(s) to specify the legend coordinates (default: "topright"). If "none" no legend is plotted.
natozero	Logical. Should NAs be coerced to zeros (default: TRUE)? Only has effect if rel = TRUE.
file	Character: File path if a pdf should be created
...	Additional graphical parameters

Value

A plot. Invisible: A dataframe with columns date and tnames with the counts/proportion of the selected topics.

Examples

## Not run: 
data(politics)
poliClean <- cleanTexts(politics)
poliPraesidents <- filterWord(object=poliClean, search=c("bush", "obama"))
words10 <- makeWordlist(text=poliPraesidents$text)
words10 <- words10$words[words10$wordtable > 10]
poliLDA <- LDAprep(text=poliPraesidents$text, vocab=words10)
LDAresult <- LDAgen(documents=poliLDA, K=5, vocab=words10)
plotWordSub(object=poliClean, ldaresult=LDAresult, ldaID=names(poliLDA), search="obama")

## End(Not run)

tosca documentation built on Oct. 28, 2021, 5:07 p.m.