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: 1.3-5
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: 2023-08-23
DOI: 10.32614/CRAN.package.SentimentAnalysis
Author: Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]
Maintainer: Nicolas Proellochs <nicolas at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: SentimentAnalysis results


Reference manual: SentimentAnalysis.pdf
Vignettes: SentimentAnalysis Vignette


Package source: SentimentAnalysis_1.3-5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SentimentAnalysis_1.3-5.tgz, r-oldrel (arm64): SentimentAnalysis_1.3-5.tgz, r-release (x86_64): SentimentAnalysis_1.3-5.tgz, r-oldrel (x86_64): SentimentAnalysis_1.3-5.tgz
Old sources: SentimentAnalysis archive

Reverse dependencies:

Reverse imports: disclosuR


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