SentimentDictionaryWeighted: Create a sentiment dictionary of words linked to a score

Description

This routine creates a new object of type SentimentDictionaryWeighted that contains a number of words, each linked to a continuous score (i.e. weight) for specifying its polarity. The scores can later be interpreted as a linear model

Usage

SentimentDictionaryWeighted(
  words,
  scores,
  idf = rep(1, length(words)),
  intercept = 0
)

Value

Returns a new object of type SentimentDictionaryWordlist

Arguments

words: is collection (vector) of different words as strings
scores: are the corresponding scores or weights denoting the word's polarity
idf: provide further details on the frequency of words in the corpus as an additional source for normalization
intercept: is an optional parameter for shifting the zero level (default: 0)

References

Pr\"ollochs and Feuerriegel (2018). Statistical inferences for Polarity Identification in Natural Language, PloS One 13(12).

Examples

Run this code

# generate dictionary (based on linear model)
d <- SentimentDictionaryWeighted(c("increase", "decrease", "exit"),
                                 c(+1, -1, -10),
                                 rep(NA, 3))
summary(d)
# alternative call
d <- SentimentDictionaryWeighted(c("increase", "decrease", "exit"),
                                 c(+1, -1, -10))
summary(d)
# alternative call
d <- SentimentDictionary(c("increase", "decrease", "exit"),
                         c(+1, -1, -10),
                         rep(NA, 3))
summary(d)

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