Package: SentimentAnalysis 1.3-5

Nicolas Proellochs

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.

Authors:Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]

SentimentAnalysis_1.3-5.tar.gz
SentimentAnalysis_1.3-5.zip(r-4.7)SentimentAnalysis_1.3-5.zip(r-4.6)SentimentAnalysis_1.3-5.zip(r-4.5)
SentimentAnalysis_1.3-5.tgz(r-4.6-any)SentimentAnalysis_1.3-5.tgz(r-4.5-any)
SentimentAnalysis_1.3-5.tar.gz(r-4.7-any)SentimentAnalysis_1.3-5.tar.gz(r-4.6-any)
SentimentAnalysis_1.3-5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SentimentAnalysis/json (API)
NEWS

# Install 'SentimentAnalysis' in R:

install.packages('SentimentAnalysis', repos = c('https://sfeuerriegel.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sfeuerriegel/sentimentanalysis/issues

Datasets:

DictionaryGI - Dictionary with opinionated words from the Harvard-IV dictionary as used in the General Inquirer software
DictionaryHE - Dictionary with opinionated words from Henry's Financial dictionary
DictionaryLM - Dictionary with opinionated words from Loughran-McDonald Financial dictionary

On CRAN:

8.53 score 154 stars 1 packages 370 scripts 704 downloads 4 mentions 43 exports 40 dependencies

Last updated from:279194dc86. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	159
source / vignettes	OK	262
linux-release-x86_64	NOTE	156
macos-release-arm64	NOTE	167
macos-oldrel-arm64	NOTE	235
windows-devel	NOTE	114
windows-release	NOTE	114
windows-oldrel	NOTE	102
wasm-release	OK	131

Exports:analyzeSentiment compareDictionaries compareToResponse convertToBinaryResponse convertToDirection countWords enetEstimation extractWords generateDictionary glmEstimation lassoEstimation lmEstimation loadDictionaryGI loadDictionaryHE loadDictionaryLM loadDictionaryLM_Uncertainty loadDictionaryQDAP loadImdb lookupEstimationMethod ngram_tokenize numEntries numNegativeEntries numPositiveEntries plotSentiment plotSentimentResponse preprocessCorpus read ridgeEstimation ruleLinearModel ruleNegativity rulePositivity ruleRatio ruleSentiment ruleSentimentPolarity ruleWordCount SentimentDictionary SentimentDictionaryBinary SentimentDictionaryWeighted SentimentDictionaryWordlist spikeslabEstimation toDocumentTermMatrix transformIntoCorpus write

Dependencies:BH cli codetools cpp11 farver foreach ggplot2 glmnet glue gtable isoband iterators labeling lars lattice lifecycle Matrix moments ngramrr NLP qdapDictionaries R6 randomForest RColorBrewer Rcpp RcppEigen rlang S7 scales shape slam spikeslab stringdist survival tau tm vctrs viridisLite withr xml2

SentimentAnalysis Vignette

Stefan Feuerriegel, Nicolas Proellochs

Rendered fromSentimentAnalysis.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2023-08-23
Started: 2016-06-18

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Sentiment analysis	analyzeSentiment analyzeSentiment.character analyzeSentiment.Corpus analyzeSentiment.data.frame analyzeSentiment.DocumentTermMatrix analyzeSentiment.TermDocumentMatrix
Compares two dictionaries	compareDictionaries
Compare sentiment values to existing response variable	compareToResponse compareToResponse.data.frame compareToResponse.factor compareToResponse.integer compareToResponse.logical compareToResponse.numeric
Convert continuous sentiment to direction	convertToBinaryResponse
Convert continuous sentiment to direction	convertToDirection
Count words	countWords countWords.character countWords.Corpus countWords.data.frame countWords.DocumentTermMatrix countWords.TermDocumentMatrix
Dictionary with opinionated words from the Harvard-IV dictionary as used in the General Inquirer software	DictionaryGI
Dictionary with opinionated words from Henry's Financial dictionary	DictionaryHE
Dictionary with opinionated words from Loughran-McDonald Financial dictionary	DictionaryLM
Elastic net estimation	enetEstimation
Extract words from dictionary	extractWords
Generates dictionary of decisive terms	generateDictionary generateDictionary.character generateDictionary.Corpus generateDictionary.data.frame generateDictionary.DocumentTermMatrix generateDictionary.TermDocumentMatrix
Estimation via generalized least squares	glmEstimation
Lasso estimation	lassoEstimation
Ordinary least squares estimation	lmEstimation
Loads Harvard-IV dictionary into object	loadDictionaryGI
Loads Henry's finance-specific dictionary into object	loadDictionaryHE
Loads Loughran-McDonald dictionary into object	loadDictionaryLM
Loads uncertainty words from Loughran-McDonald into object	loadDictionaryLM_Uncertainty
Loads polarity words from qdap package into object	loadDictionaryQDAP
Retrieves IMDb dataset	loadImdb
Estimation method	lookupEstimationMethod
N-gram tokenizer	ngram_tokenize
Number of words in dictionary	numEntries
Number of negative words in dictionary	numNegativeEntries
Number of positive words in dictionary	numPositiveEntries
KDE plot of estimated coefficients	plot.SentimentDictionaryWeighted
Line plot with sentiment scores	plotSentiment
Scatterplot with trend line between sentiment and response	plotSentimentResponse
Prediction for given dictionary	predict.SentimentDictionaryWeighted
Default preprocessing of corpus	preprocessCorpus
Output content of sentiment dictionary	print.SentimentDictionaryBinary print.SentimentDictionaryWeighted print.SentimentDictionaryWordlist
Read dictionary from text file	read
Ridge estimation	ridgeEstimation
Sentiment based on linear model	ruleLinearModel
Ratio of negative words	ruleNegativity
Ratio of positive words	rulePositivity
Ratio of dictionary words	ruleRatio
Sentiment score	ruleSentiment
Sentiment polarity score	ruleSentimentPolarity
Counts word frequencies	ruleWordCount
Create new sentiment dictionary based on input	SentimentDictionary
Create a sentiment dictionary of positive and negative words	SentimentDictionaryBinary
Create a sentiment dictionary of words linked to a score	SentimentDictionaryWeighted
Create a sentiment dictionary consisting of a simple wordlist	SentimentDictionaryWordlist
Spike-and-slab estimation	spikeslabEstimation
Output summary information on sentiment dictionary	summary.SentimentDictionaryBinary summary.SentimentDictionaryWeighted summary.SentimentDictionaryWordlist
Default preprocessing of corpus and conversion to document-term matrix	toDocumentTermMatrix
Transforms the input into a Corpus object	transformIntoCorpus
Write dictionary to text file	write write.SentimentDictionaryBinary write.SentimentDictionaryWeighted write.SentimentDictionaryWordlist