Compute a score based on the number of matching terms.

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

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`

.

A score as computed by `FUN`

from the number of matching
`terms`

in `x`

.

# NOT RUN { 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")) # }