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 sfeuerriegel.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: |
Introduction to SentimentAnalysis |
| Package source: | SentimentAnalysis_1.3-3.tar.gz |
| Windows binaries: | r-devel: SentimentAnalysis_1.3-3.zip, r-release: SentimentAnalysis_1.3-3.zip, r-oldrel: SentimentAnalysis_1.3-3.zip |
| macOS binaries: | r-release: SentimentAnalysis_1.3-3.tgz, r-oldrel: SentimentAnalysis_1.3-3.tgz |
| Old sources: | SentimentAnalysis archive |
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