topTexts: Get The IDs Of The Most Representive Texts

In tosca: Tools for Statistical Content Analysis

Description

The function extracts the text IDs belonging to the texts with the highest relative or absolute number of words per topic.

Usage

topTexts(
  ldaresult,
  ldaID,
  limit = 20L,
  rel = TRUE,
  select = 1:nrow(ldaresult$document_sums),
  tnames,
  minlength = 30L
)

Arguments

ldaresult	LDA result
ldaID	Vector of text IDs
limit	Integer: Number of text IDs per topic.
rel	Logical: Should be the relative frequency be used?
select	Which topics should be returned?
tnames	Names of the selected topics
minlength	Minimal total number of words a text must have to be included

Value

Matrix of text IDs.

Examples

texts <- list(A="Give a Man a Fish, and You Feed Him for a Day.
Teach a Man To Fish, and You Feed Him for a Lifetime",
B="So Long, and Thanks for All the Fish",
C="A very able manipulative mathematician, Fisher enjoys a real mastery
in evaluating complicated multiple integrals.")

corpus <- textmeta(meta=data.frame(id=c("A", "B", "C", "D"),
title=c("Fishing", "Don't panic!", "Sir Ronald", "Berlin"),
date=c("1885-01-02", "1979-03-04", "1951-05-06", "1967-06-02"),
additionalVariable=1:4, stringsAsFactors=FALSE), text=texts)

corpus <- cleanTexts(corpus)
wordlist <- makeWordlist(corpus$text)
ldaPrep <- LDAprep(text=corpus$text, vocab=wordlist$words)

LDA <- LDAgen(documents=ldaPrep, K = 3L, vocab=wordlist$words, num.words=3)
topTexts(ldaresult=LDA, ldaID=c("A","B","C"), limit = 1L, minlength=2)

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