sample.fragments: Sample fragments of text to contextualize a phrase.

In textreg: n-Gram Text Regression, aka Concise Comparative Summarization

Sample fragments of text to contextualize a phrase.

Description

Take a phrase, a labeling and a corpus and return text fragments containing that phrase.

Grab all phrases and then give sample of N from positive class and N from negative class. Sampling is to first sample from documents and then sample a random phrase from each of those documents.

Usage

sample.fragments(
  phrases,
  labeling,
  corp,
  N = 10,
  char.before = 80,
  char.after = char.before,
  metainfo = NULL
)

Arguments

phrases	Phrases to examine (a list of strings)
labeling	– a vector of the same length as the corpus
corp	Corpus object (tm package Corpus object)
N	size of sample to make.
char.before	Number of characters of document to pull before phrase to give context.
char.after	As above, but trailing characters. Defaults to char.before value.
metainfo	– extra string to add to the printout for clarity if many such printouts are being generated.

See Also

Other sample.fragments: is.fragment.sample(), print.fragment.sample()

Examples

library( tm )
data( bathtub )
sample.fragments( "bathtub", meta(bathtub)$meth.chl, bathtub )

textreg documentation built on Sept. 17, 2026, 1:07 a.m.