get_stanford_sentiment

Call the Stanford Sentiment tagger with a
vector of strings. The Stanford tagger automatically
detects sentence boundaries and treats each sentence as a 
distinct instance to measure. As a result, the vector 
that gets returned will not be the same length as the
input vector.

Extracts sentiment and sentiment-derived plot arcs
from text using a variety of sentiment dictionaries conveniently
packaged for consumption by R users.  Implemented dictionaries include
"syuzhet" (default) developed in the Nebraska Literary Lab
"afinn" developed by Finn Årup Nielsen, "bing" developed by Minqing Hu
and Bing Liu, and "nrc" developed by Mohammad, Saif M. and Turney, Peter D.
Applicable references are available in README.md and in the documentation
for the "get_sentiment" function.  The package also provides a hack for
implementing Stanford's coreNLP sentiment parser. The package provides
several methods for plot arc normalization.

Matthew Jockers

syuzhet

Extracts Sentiment and Sentiment-Derived Plot Arcs from Text

get_stanford_sentiment function

<dl><dt>text_vector</dt>
<dd>A vector of strings</dd>
<dt>path_to_stanford_tagger</dt>
<dd>a local file path indicating 
where the coreNLP package is installed.</dd></dl>

Arguments

Get Sentiment from the Stanford Tagger — get_stanford_sentiment

<dl>

<dt>text_vector</dt>
<dd>A vector of strings</dd>


<dt>path_to_stanford_tagger</dt>
<dd>a local file path indicating 
where the coreNLP package is installed.</dd>

</dl>

get_stanford_sentiment: Get Sentiment from the Stanford Tagger

Description

Usage

Arguments