SentimentAnalysis (version 1.1-0)

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)

Arguments

words

is collection (vector) of different words as strings

scores

are the corresponding socres 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)

Value

Returns a new object of type SentimentDictionaryWordlist

References

Pr\"ollochs and Feuerriegel (2015). Generating Domain-Specific Dictionaries Using Bayesian Learning. 23rd European Conference on Information Systems (ECIS 2015).

See Also

SentimentDictionary

Examples

# 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)