tm_term_score: Compute Score for Matching Terms

In tm: Text Mining Package

Description

Compute a score based on the number of matching terms.

Usage

## S3 method for class 'DocumentTermMatrix'
tm_term_score(x, terms, FUN = row_sums)
## S3 method for class 'PlainTextDocument'
tm_term_score(x, terms, FUN = function(x) sum(x, na.rm = TRUE))
## S3 method for class 'term_frequency'
tm_term_score(x, terms, FUN = function(x) sum(x, na.rm = TRUE))
## S3 method for class 'TermDocumentMatrix'
tm_term_score(x, terms, FUN = col_sums)

Arguments

x	Either a PlainTextDocument, a term frequency as returned by termFreq, or a TermDocumentMatrix.
terms	A character vector of terms to be matched.
FUN	A function computing a score from the number of terms matching in x.

Value

A score as computed by FUN from the number of matching terms in x.

Examples

data("acq")
tm_term_score(acq[[1]], c("company", "change"))
## Not run: ## Test for positive and negative sentiments
## install.packages("tm.lexicon.GeneralInquirer", repos="http://datacube.wu.ac.at", type="source")
require("tm.lexicon.GeneralInquirer")
sapply(acq[1:10], tm_term_score, terms_in_General_Inquirer_categories("Positiv"))
sapply(acq[1:10], tm_term_score, terms_in_General_Inquirer_categories("Negativ"))
tm_term_score(TermDocumentMatrix(acq[1:10],
                                control = list(removePunctuation = TRUE)),
             terms_in_General_Inquirer_categories("Positiv"))
## End(Not run)

tm documentation built on April 7, 2021, 3:01 a.m.