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vader (version 0.2.1)

get_vader: Get a named vector of vader results for a single text document

Description

Use get_vader() to calculate the valence of a single text document.

Usage

get_vader(text, incl_nt = T, neu_set = T, rm_qm = T)

Arguments

text

to be analyzed; for get_vader(), the text should be a character string

incl_nt

defaults to T, indicates whether you wish to incl UNUSUAL n't contractions (e.g., yesn't) in negation analysis

neu_set

defaults to T, indicates whether you wish to count neutral words in calculations

rm_qm

defaults to T, indicates whether you wish to clean quotation marks from text (setting to F may result in errors)

Value

A named vector containing the valence score for each word; an overall, compound valence score for the text; the weighted percentage of positive, negative, and neutral words in the text; and the frequency of the word "but".

N.B.

In the examples below, "yesn't" is an internet neologism meaning "no", "maybe yes, maybe no", "didn't", etc.

References

For the original Python Code, please see:

  • https://github.com/cjhutto/vaderSentiment

  • https://github.com/cjhutto/vaderSentiment/blob/master/vaderSentiment/vaderSentiment.py

For the original R Code, please see:

  • https://github.com/nrguimaraes/sentimentSetsR/blob/master/R/ruleBasedSentimentFunctions.R

Modifications to the above scripts include, but are not limited to:

  • ALL CAPS fx: updated to account for non-alpha words; i.e. "I'M 100 PERCENT SURE" would previously have been counted as mixed case due to the use of numbers

  • IDIOMS fx: added capacity to check for idioms that do not contain any words found in the Vader Lexicon

  • WORDS+EMOT: strip punctuation while preserving ALL emoticons found in dictionary

  • Option to turn on/off neutral count

See Also

vader_df to get vader results for multiple text documents

Examples

Run this code
# NOT RUN {
get_vader("I yesn't like it")
get_vader("I yesn't like it", incl_nt = FALSE)
get_vader("I yesn't like it", neu_set = FALSE)
get_vader("I said \"I'm not happy\"", rm_qm = FALSE)
get_vader("I said \" I'm not happy \" ", rm_qm = FALSE)

# }

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