meanr: Sentiment Analysis Scorer

Sentiment analysis is a popular technique in text mining that attempts to determine the emotional state of some text. We provide a new implementation of a common method for computing sentiment, whereby words are scored as positive or negative according to a dictionary lookup. Then the sum of those scores is returned for the document. We use the 'Hu' and 'Liu' sentiment dictionary ('Hu' and 'Liu', 2004) <doi:10.1145/1014052.1014073> for determining sentiment. The scoring function is 'vectorized' by document, and scores for multiple documents are computed in parallel via 'OpenMP'.

Version:	0.1-4
Depends:	R (≥ 3.0.0)
Published:	2022-03-05
Author:	Drew Schmidt [aut, cre]
Maintainer:	Drew Schmidt <wrathematics at gmail.com>
BugReports:	https://github.com/wrathematics/meanr/issues
License:	BSD 2-clause License + file LICENSE
URL:	https://github.com/wrathematics/meanr
NeedsCompilation:	yes
Citation:	meanr citation info
Materials:	README ChangeLog
CRAN checks:	meanr results

Documentation:

Reference manual:

meanr.pdf

Downloads:

Package source:	meanr_0.1-4.tar.gz
Windows binaries:	r-devel: meanr_0.1-4.zip, r-release: meanr_0.1-4.zip, r-oldrel: meanr_0.1-4.zip
macOS binaries:	r-release (arm64): meanr_0.1-4.tgz, r-oldrel (arm64): meanr_0.1-4.tgz, r-release (x86_64): meanr_0.1-4.tgz, r-oldrel (x86_64): meanr_0.1-4.tgz
Old sources:	meanr archive

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