make.count.table: Count number of times documents have a given phrase.

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

Description

Given a list of phrases, count how many documents they appear in and subdivide by positive and negative appearance.

Usage

make.count.table(phrases, labeling, corpus)

Arguments

phrases	List of strings
labeling	Vector of +1/0/-1 labels
corpus	A corpus object from tm package

Details

This method does not consider multiple counts of phrases within documents. Phrases can have wildcards and stemming notation. See grab.fragments.

Value

a dataframe of statistics. per.pos is the percent of the documents with the phrase that are positively labeled. per.tag is the percent of the positively labeled documents that have the phrase.

See Also

grab.fragments

Other textregCounting: make.phrase.matrix, phrase.count

Examples

library( tm )
data( bathtub )
lbl = meta( bathtub )$meth.chl
make.count.table( c("bathtub","strip+", "vapor *"), lbl, bathtub )

textreg documentation built on May 2, 2019, 8:34 a.m.