emoxicon_scores: Emoxicon Scores

Description

A bag-of-words approach for computing emotions in text data using the lexicon compiled by Araque, Gatti, Staiano, and Guerini (2018).

Usage

emoxicon_scores(text, lexicon, exclude)

Arguments

text: Matrix or data frame. A data frame containing texts to be scored (one text per row)
lexicon: The lexicon used to score the words. The default is the emotions dataset, a modification of the lexicon developed by Araque, Gatti, Staiano, and Guerini (2018). To use the raw lexicon from Araque et. al (2018) containing the original probability weights, use the weights dataset. If another custom lexicon is used, the first column of the lexicon should contain the terms and the subsequent columns contain the scoring categories.
exclude: A vector listing terms that should be excluded from the lexicon. Words specified in exclude will not influence document scoring. Users should consider excluding 'red herring' words that are more closely related to the topics of the documents, rather than the documents' emotional content. For example, the words "clinton" and "trump" are present in the lexicon and are both associated with the emotion 'AMUSED'. Excluding these words when analyzing political opinions may produce more accurate results.

Author

Tara Valladares <tls8vx at virginia.edu> and Hudson F. Golino <hfg9s at virginia.edu>

References

Araque, O., Gatti, L., Staiano, J., and Guerini, M. (2018). DepecheMood++: A bilingual emotion lexicon built through simple yet powerful techniques. ArXiv

Examples

Run this code


# Obtain "emotions" data
data("emotions")

# Obtain "tinytrolls" data
data("tinytrolls")

if (FALSE) {
# Obtain emoxicon scores for first 10 tweets
emotions_tinytrolls <- emoxicon_scores(text = tinytrolls$content, lexicon = emotions)
}