SentimentAnalysis: Dictionary-Based Sentiment Analysis

Performs a sentiment analysis of textual contents in R. This implementation utilizes various existing dictionaries, such as Harvard IV, or finance-specific dictionaries. Furthermore, it can also create customized dictionaries. The latter uses LASSO regularization as a statistical approach to select relevant terms based on an exogenous response variable.

Version: 1.2-0
Depends: R (≥ 2.10)
Imports: tm (≥ 0.6), qdapDictionaries, ngramrr (≥ 0.1), moments, stringdist, SnowballC, XML, glmnet, spikeslab (≥ 1.1), ggplot2, mgcv
Suggests: testthat, knitr, rmarkdown
Published: 2017-06-02
Author: Stefan Feuerriegel [aut, cre], Nicolas Proellochs [aut]
Maintainer: Stefan Feuerriegel <stefan.feuerriegel at is.uni-freiburg.de>
BugReports: https://github.com/sfeuerriegel/SentimentAnalysis/issues
License: MIT + file LICENSE
URL: https://github.com/sfeuerriegel/SentimentAnalysis
NeedsCompilation: no
Materials: README NEWS
CRAN checks: SentimentAnalysis results

Downloads:

Reference manual: SentimentAnalysis.pdf
Vignettes: Introduction to SentimentAnalysis
Package source: SentimentAnalysis_1.2-0.tar.gz
Windows binaries: r-devel: SentimentAnalysis_1.2-0.zip, r-release: SentimentAnalysis_1.2-0.zip, r-oldrel: SentimentAnalysis_1.2-0.zip
OS X El Capitan binaries: r-release: SentimentAnalysis_1.2-0.tgz
OS X Mavericks binaries: r-oldrel: SentimentAnalysis_1.2-0.tgz

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