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:
Linking:
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