simple_plot

the raw sentiment values
calculated for each sentence

raw_values

title

legend_pos

size of the low pass filter. I.e. the number of low frequency components to retain

size of the rolling window for the rolling mean expressed as a percentage.

window

A simple function for comparing three smoothers

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

simple_plot function

<dl><dt>raw_values</dt>
<dd>the raw sentiment values
calculated for each sentence</dd>
<dt>title</dt>
<dd>for resulting image</dd>
<dt>legend_pos</dt>
<dd>position for legend</dd>
<dt>lps</dt>
<dd>size of the low pass filter. I.e. the number of low frequency components to retain</dd>
<dt>window</dt>
<dd>size of the rolling window for the rolling mean expressed as a percentage.</dd></dl>

Arguments

Plots simple and rolling shapes overlayed — simple_plot

<dl>

<dt>raw_values</dt>
<dd>the raw sentiment values
calculated for each sentence</dd>


<dt>title</dt>
<dd>for resulting image</dd>


<dt>legend_pos</dt>
<dd>position for legend</dd>


<dt>lps</dt>
<dd>size of the low pass filter. I.e. the number of low frequency components to retain</dd>


<dt>window</dt>
<dd>size of the rolling window for the rolling mean expressed as a percentage.</dd>

</dl>

simple_plot: Plots simple and rolling shapes overlayed

Description

Usage

Arguments