compute_sent_summ: Compute sentiment scores.

In tonyelhabr/tetext: Tony's Personal Package for Text Analysis

Description

Compute sentiment scores given tokens.

Usage

compute_sent_summ_facet_at(data = NULL, token = NULL, feature = NULL,
  facet = NULL, lexicon = "bing", ...)

compute_sent_summ_facet(..., token, feature, facet)

compute_sent_summ_at(data = NULL, facet = NULL, ...)

compute_sent_summ(..., token, feature, facet)

Arguments

data	data.frame. Must already be in 'tidy' format.
token	bare for NSE; character for SE. Name of column in data whose values are scored.
feature	bare for NSE; character for SE. Name of column in data whose values serve as entity across which 'token' values are scored. Probably something like 'sentence', or, in the case of Twitter data, 'status_id'.
facet	bare for NSE; character for SE. Name of column in data used for grouping in the case that there are more than one entitiy.
lexicon	character. Specifies lexicon to use. Must be a lexicon available in the tidytext::package.
...	dots. Parameters to pass to get_sents() internally.

Details

Heavily influenced by Text Mining with R. Creates output columns 'sentiment' and 'score'.

Value

data.frame.

See Also

Don't have an explicit url.

tonyelhabr/tetext documentation built on May 14, 2019, 8:03 a.m.