I am trying to apply a sentiment analysis in R with the help of my DTM (document term matrix) or TDM (term document matrix). I could not find any similar topic in the forum and on google. Thus, I created a corpus and from that corpus I generated a dtm/tdm in R. My next step would be to apply the sentiment analysis which I need later for stock prediction via SVM. My give code is that:
dtm <- DocumentTermMatrix(docs)
dtm <- removeSparseTerms(dtm, 0.99)
dtm <- as.data.frame(as.matrix(dtm))
tdm <- TermDocumentMatrix(docs)
tdm <- removeSparseTerms(tdm, 0.99)
tdm <- as.data.frame(as.matrix(tdm))
I read that it is possible through the tidytext package with the help of the get_sentiments() function. But it was not possible to apply that with a DTM/TDM. How can I run a sentiment analysis for my cleaned filter words which are already stemmed, tokenized etc.? I saw that a lot of people did the sentiment analysis for a hole sentence, but I would like to apply it for my single words in order to see if they are positive, negative, score etc. Many thanks in advance!
SentimentAnalysis has good integration with tm.
library(tm)
library(SentimentAnalysis)
documents <- c("Wow, I really like the new light sabers!",
"That book was excellent.",
"R is a fantastic language.",
"The service in this restaurant was miserable.",
"This is neither positive or negative.",
"The waiter forget about my dessert -- what poor service!")
vc <- VCorpus(VectorSource(documents))
dtm <- DocumentTermMatrix(vc)
analyzeSentiment(dtm,
rules=list(
"SentimentLM"=list(
ruleSentiment, loadDictionaryLM()
),
"SentimentQDAP"=list(
ruleSentiment, loadDictionaryQDAP()
)
)
)
# SentimentLM SentimentQDAP
# 1 0.000 0.1428571
# 2 0.000 0.0000000
# 3 0.000 0.0000000
# 4 0.000 0.0000000
# 5 0.000 0.0000000
# 6 -0.125 -0.2500000