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
Published: 2023年08月23日
Author: Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]
Maintainer: Nicolas Proellochs <nicolas at nproellochs.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README, NEWS

Documentation:

Downloads:

Windows binaries: r-devel: SentimentAnalysis_1.3-5.zip, r-release: SentimentAnalysis_1.3-5.zip, r-oldrel: SentimentAnalysis_1.3-5.zip
macOS binaries: r-release (arm64): SentimentAnalysis_1.3-5.tgz, r-oldrel (arm64): SentimentAnalysis_1.3-5.tgz, r-release (x86_64): SentimentAnalysis_1.3-5.tgz, r-oldrel (x86_64): SentimentAnalysis_1.3-5.tgz

Reverse dependencies:

Reverse imports: disclosuR

Linking:

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