sentiment_stanford_by: Polarity Score (Sentiment Analysis) By Groups

In trinker/stansent: Wrapper of Stanford's coreNLP Sentiment Tagger

Description

Approximate the sentiment (polarity) of text by grouping variable(s).

Usage

sentiment_stanford_by(text.var, by = NULL,
  averaging.function = stansent::average_downweighted_zero, group.names, ...)

Arguments

text.var	The text variable.
by	The grouping variable(s). Default NULL uses the original row/element indices; if you used a column of 12 rows for text.var these 12 rows will be used as the grouping variable. Also takes a single grouping variable or a list of 1 or more grouping variables.
averaging.function	A function for performing the group by averaging. The default, average_downweighted_zero, downweights zero values in the averaging. Note that the function must handle NAs. The sentimentr functions average_weighted_mixed_sentiment and average_mean are also available. The former upweights negative when the analysts suspects the speaker is likely to surround negatives with positives (mixed) as a polite social convention but still the affective state is negative. The later is a standard mean average.
group.names	A vector of names that corresponds to group. Generally for internal use.
...	Other arguments passed to sentiment_stanford.

Details

Note that the coreNLP is expensive with regard to time. Typically it is better to use sentiment_stanford and do the merging and aggregation/summarization yourself.

Value

Returns a data.table with grouping variables plus:

• element_id - The id number of the original vector passed to sentiment

• sentence_id - The id number of the sentences within each element_id

• word_count - Word count summed by grouping variable

• sd - Standard deviation (sd) of the sentiment/polarity score by grouping variable

• ave_sentiment - Sentiment/polarity score mean average by grouping variable

trinker/stansent documentation built on Oct. 12, 2021, 11:19 a.m.