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: 1.3-3
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: 2019-03-26
Author: Stefan Feuerriegel [aut, cre], Nicolas Proellochs [aut]
Maintainer: Stefan Feuerriegel <sentiment at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: SentimentAnalysis results


Reference manual: SentimentAnalysis.pdf
Vignettes: Introduction to SentimentAnalysis
Package source: SentimentAnalysis_1.3-3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: SentimentAnalysis_1.3-3.tgz, r-oldrel: SentimentAnalysis_1.3-3.tgz
Old sources: SentimentAnalysis archive


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