Ich bin auf folgenden Code gestoßen.
Code: Alles auswählen
#function to calculate number of words in each category within a sentence
sentimentScore <- function(sentences, vNegTerms, negTerms, posTerms, vPosTerms){
final_scores <- matrix('', 0, 5)
scores <- laply(sentences, function(sentence, vNegTerms, negTerms, posTerms, vPosTerms){
initial_sentence <- sentence
#remove unnecessary characters and split up by word
sentence <- gsub('[[:punct:]]', '', sentence)
sentence <- gsub('[[:cntrl:]]', '', sentence)
sentence <- gsub('\\d+', '', sentence)
sentence <- tolower(sentence)
wordList <- str_split(sentence, '\\s+')
words <- unlist(wordList)
#build vector with matches between sentence and each category
vPosMatches <- match(words, vPosTerms)
posMatches <- match(words, posTerms)
vNegMatches <- match(words, vNegTerms)
negMatches <- match(words, negTerms)
#sum up number of words in each category
vPosMatches <- sum(!is.na(vPosMatches))
posMatches <- sum(!is.na(posMatches))
vNegMatches <- sum(!is.na(vNegMatches))
negMatches <- sum(!is.na(negMatches))
score <- c(vNegMatches, negMatches, posMatches, vPosMatches)
#add row to scores table
newrow <- c(initial_sentence, score)
final_scores <- rbind(final_scores, newrow)
return(final_scores)
}, vNegTerms, negTerms, posTerms, vPosTerms)
return(scores)
}
#build tables of positive and negative sentences with scores
posResult <- as.data.frame(sentimentScore(posText, vNegTerms, negTerms, posTerms, vPosTerms))
negResult <- as.data.frame(sentimentScore(negText, vNegTerms, negTerms, posTerms, vPosTerms))
posResult <- cbind(posResult, 'positive')
colnames(posResult) <- c('sentence', 'vNeg', 'neg', 'pos', 'vPos', 'sentiment')
negResult <- cbind(negResult, 'negative')
colnames(negResult) <- c('sentence', 'vNeg', 'neg', 'pos', 'vPos', 'sentiment')
#combine the positive and negative tables
results <- rbind(posResult, negResult)
Danke schon mal!