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: 1.3-4
Depends: R (≥ 2.10)
Imports: tm (≥ 0.6), qdapDictionaries, ngramrr (≥ 0.1), moments, stringdist, glmnet, spikeslab (≥ 1.1), ggplot2
Suggests: testthat, knitr, rmarkdown, SnowballC, XML, mgcv
Published: 2021-02-18
Author: Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]
Maintainer: Nicolas Proellochs <nicolas at nproellochs.com>
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

Documentation:

Reference manual: SentimentAnalysis.pdf
Vignettes: SentimentAnalysis Vignette

Downloads:

Package source: SentimentAnalysis_1.3-4.tar.gz
Windows binaries: r-devel: SentimentAnalysis_1.3-4.zip, r-release: SentimentAnalysis_1.3-4.zip, r-oldrel: SentimentAnalysis_1.3-4.zip
macOS binaries: r-release (arm64): SentimentAnalysis_1.3-4.tgz, r-release (x86_64): SentimentAnalysis_1.3-4.tgz, r-oldrel: SentimentAnalysis_1.3-4.tgz
Old sources: SentimentAnalysis archive

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