sentimentr (version 2.6.1)

sentiment_attributes: Extract Sentiment Attributes from Text

Description

This function utilizes gofastr and termco to extract sentiment based attributes (attributes concerning polarized words and valence shifters) from a text. Attributes include the rate of polarized terms and valence shifters relative to number of words. Additionally, coocurrence rates for valence shifters are computed.

Usage

sentiment_attributes(text.var,
  polarity_dt = lexicon::hash_sentiment_jockers_rinker,
  valence_shifters_dt = lexicon::hash_valence_shifters, ...)

Arguments

text.var

The text variable.

polarity_dt

A data.table of positive/negative words and weights with x and y as column names.

valence_shifters_dt

A data.table of valence shifters that can alter a polarized word's meaning and an integer key for negators (1), amplifiers(2), de-amplifiers (3) and adversative conjunctions (4) with x and y as column names.

…

ignored.

Value

Returns a list of four items:

Meta

The number of words, sentences, and questions in the text

Attributes

The rate of sentiment attributes relative to the number of words

Polarized_Cooccurrences

The rate that valence shifters cooccur with a polarized word in the same sentence

Cooccurrences

A cooccurrence matrix of sentiment attributes; `polarized` is the sum of positive and negative

Examples

# NOT RUN {
sentiment_attributes(presidential_debates_2012$dialogue)
# }

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