{ "_id": "6a483e5be06c18f0a6532559", "Package": "SentimentAnalysis", "Type": "Package", "Title": "Dictionary-Based Sentiment Analysis", "Version": "1.3-5", "Date": "2023-08-23", "Authors@R": "c(person(\"Nicolas\", \"Proellochs\", email=\"nicolas@nproellochs.com\",\nrole=c(\"aut\", \"cre\")),\nperson(\"Stefan\", \"Feuerriegel\", email=\"sentiment@sfeuerriegel.com\",\nrole=c(\"aut\")))", "Description": "Performs a sentiment analysis of textual contents in R.\nThis implementation utilizes various existing dictionaries,\nsuch as Harvard IV, or finance-specific dictionaries.\nFurthermore, it can also create customized dictionaries. The\nlatter uses LASSO regularization as a statistical approach to\nselect relevant terms based on an exogenous response variable.", "License": "MIT + file LICENSE", "URL": "https://github.com/sfeuerriegel/SentimentAnalysis", "BugReports": "https://github.com/sfeuerriegel/SentimentAnalysis/issues", "LazyData": "true", "Encoding": "UTF-8", "RoxygenNote": "7.2.3", "VignetteBuilder": "knitr", "Config/pak/sysreqs": "libxml2-dev", "Repository": "https://sfeuerriegel.r-universe.dev", "Date/Publication": "2023-08-23 19:56:31 UTC", "RemoteUrl": "https://github.com/sfeuerriegel/sentimentanalysis", "RemoteRef": "HEAD", "RemoteSha": "279194dc86d1764be9181c12273087d8de8d75d6", "NeedsCompilation": "no", "Packaged": { "Date": "2026-07-03 22:54:10 UTC", "User": "root" }, "Author": "Nicolas Proellochs [aut, cre],\nStefan Feuerriegel [aut]", "Maintainer": "Nicolas Proellochs ", "_user": "sfeuerriegel", "_type": "src", "_file": "SentimentAnalysis_1.3-5.tar.gz", "_fileid": 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opinionated words from the Harvard-IV dictionary as used in the General Inquirer software", "object": "DictionaryGI", "class": [ "list" ], "fields": [], "table": false, "tojson": true }, { "name": "DictionaryHE", "title": "Dictionary with opinionated words from Henry's Financial dictionary", "object": "DictionaryHE", "class": [ "list" ], "fields": [], "table": false, "tojson": true }, { "name": "DictionaryLM", "title": "Dictionary with opinionated words from Loughran-McDonald Financial dictionary", "object": "DictionaryLM", "class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "analyzeSentiment", "title": "Sentiment analysis", "topics": [ "analyzeSentiment", "analyzeSentiment.character", "analyzeSentiment.Corpus", "analyzeSentiment.data.frame", "analyzeSentiment.DocumentTermMatrix", "analyzeSentiment.TermDocumentMatrix" ] }, { "page": "compareDictionaries", "title": "Compares two dictionaries", "topics": [ "compareDictionaries" ] }, { "page": "compareToResponse", "title": "Compare sentiment values to existing response variable", "topics": [ "compareToResponse", "compareToResponse.data.frame", "compareToResponse.factor", "compareToResponse.integer", "compareToResponse.logical", "compareToResponse.numeric" ] }, { "page": "convertToBinaryResponse", "title": "Convert continuous sentiment to direction", "topics": [ "convertToBinaryResponse" ] }, { "page": "convertToDirection", "title": "Convert continuous sentiment to direction", "topics": [ "convertToDirection" ] }, { "page": "countWords", "title": "Count words", "topics": [ "countWords", "countWords.character", "countWords.Corpus", "countWords.data.frame", "countWords.DocumentTermMatrix", "countWords.TermDocumentMatrix" ] }, { "page": "DictionaryGI", "title": "Dictionary with opinionated words from the Harvard-IV dictionary as used in the General Inquirer software", "topics": [ "DictionaryGI" ] }, { "page": "DictionaryHE", "title": "Dictionary with opinionated words from Henry's Financial dictionary", "topics": [ "DictionaryHE" ] }, { "page": "DictionaryLM", "title": "Dictionary with opinionated words from Loughran-McDonald Financial dictionary", "topics": [ "DictionaryLM" ] }, { "page": "enetEstimation", "title": "Elastic net estimation", "topics": [ "enetEstimation" ] }, { "page": "extractWords", "title": "Extract words from dictionary", "topics": [ "extractWords" ] }, { "page": "generateDictionary", "title": "Generates dictionary of decisive terms", "topics": [ "generateDictionary", "generateDictionary.character", "generateDictionary.Corpus", "generateDictionary.data.frame", "generateDictionary.DocumentTermMatrix", "generateDictionary.TermDocumentMatrix" ] }, { "page": "glmEstimation", "title": "Estimation via generalized least squares", "topics": [ "glmEstimation" ] }, { "page": "lassoEstimation", "title": "Lasso estimation", "topics": [ "lassoEstimation" ] }, { "page": "lmEstimation", "title": "Ordinary least squares estimation", "topics": [ "lmEstimation" ] }, { "page": "loadDictionaryGI", "title": "Loads Harvard-IV dictionary into object", "topics": [ "loadDictionaryGI" ] }, { "page": "loadDictionaryHE", "title": "Loads Henry's finance-specific dictionary into object", "topics": [ "loadDictionaryHE" ] }, { "page": "loadDictionaryLM", "title": "Loads Loughran-McDonald dictionary into object", "topics": [ "loadDictionaryLM" ] }, { "page": "loadDictionaryLM_Uncertainty", "title": "Loads uncertainty words from Loughran-McDonald into object", "topics": [ "loadDictionaryLM_Uncertainty" ] }, { "page": "loadDictionaryQDAP", "title": "Loads polarity words from qdap package into object", "topics": [ "loadDictionaryQDAP" ] }, { "page": "loadImdb", "title": "Retrieves IMDb dataset", "topics": [ "loadImdb" ] }, { "page": "lookupEstimationMethod", "title": "Estimation method", "topics": [ "lookupEstimationMethod" ] }, { "page": "ngram_tokenize", "title": "N-gram tokenizer", "topics": [ "ngram_tokenize" ] }, { "page": "numEntries", "title": "Number of words in dictionary", "topics": [ "numEntries" ] }, { "page": "numNegativeEntries", "title": "Number of negative words in dictionary", "topics": [ "numNegativeEntries" ] }, { "page": "numPositiveEntries", "title": "Number of positive words in dictionary", "topics": [ "numPositiveEntries" ] }, { "page": "plot.SentimentDictionaryWeighted", "title": "KDE plot of estimated coefficients", "topics": [ "plot.SentimentDictionaryWeighted" ] }, { "page": "plotSentiment", "title": "Line plot with sentiment scores", "topics": [ "plotSentiment" ] }, { "page": "plotSentimentResponse", "title": "Scatterplot with trend line between sentiment and response", "topics": [ "plotSentimentResponse" ] }, { "page": "predict.SentimentDictionaryWeighted", "title": "Prediction for given dictionary", "topics": [ "predict.SentimentDictionaryWeighted" ] }, { "page": "preprocessCorpus", "title": "Default preprocessing of corpus", "topics": [ "preprocessCorpus" ] }, { "page": "print", "title": "Output content of sentiment dictionary", "topics": [ "print.SentimentDictionaryBinary", "print.SentimentDictionaryWeighted", "print.SentimentDictionaryWordlist" ] }, { "page": "read", "title": "Read dictionary from text file", "topics": [ "read" ] }, { "page": "ridgeEstimation", "title": "Ridge estimation", "topics": [ "ridgeEstimation" ] }, { "page": "ruleLinearModel", "title": "Sentiment based on linear model", "topics": [ "ruleLinearModel" ] }, { "page": "ruleNegativity", "title": "Ratio of negative words", "topics": [ "ruleNegativity" ] }, { "page": "rulePositivity", "title": "Ratio of positive words", "topics": [ "rulePositivity" ] }, { "page": "ruleRatio", "title": "Ratio of dictionary words", "topics": [ "ruleRatio" ] }, { "page": "ruleSentiment", "title": "Sentiment score", "topics": [ "ruleSentiment" ] }, { "page": "ruleSentimentPolarity", "title": "Sentiment polarity score", "topics": [ "ruleSentimentPolarity" ] }, { "page": "ruleWordCount", "title": "Counts word 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