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 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:
Downloads:
Reverse dependencies:
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