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 |
Reference manual: | SentimentAnalysis.pdf |
Vignettes: |
SentimentAnalysis Vignette |
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: SentimentAnalysis_1.3-4.tgz, r-oldrel: SentimentAnalysis_1.3-4.tgz |
Old sources: | SentimentAnalysis archive |
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