Hello,

I'm new to R, and I'm trying to run the tm package to obtain clusters of words that I can group together.

I wanted to understand if there was a way in which I could run the "findAssocs" function multiple times to obtain a series of word correlation tables, based on words that occur (say more than 50) times, and then export these tables to a spreadsheet.

Any help would be much appreciated. Thank you so much!

the current code I'm using is pasted below
#create corpus
docs<- Corpus(DirSource("C:\Users\bhatterp\Desktop\Corpus"))

#create the toSpace content transformer
toSpace <- content_transformer(function(x, pattern) {return (gsub(pattern, " ", x))})

#remove punctuations
docs <- tm_map(docs,toSpace,"-")
docs <- tm_map(docs,toSpace,",")
docs <- tm_map(docs,toSpace,";")
docs <- tm_map(docs,toSpace,":")
docs <- tm_map(docs,toSpace,"\.")

#Transform to lower case (need to wrap in content_transformer)
docs <- tm_map(docs,content_transformer(tolower))

#Strip digits (std transformation, so no need for content_transformer)
docs <- tm_map(docs, removeNumbers)

#remove stopwords using the standard list in tm
docs <- tm_map(docs, removeWords,stopwords ("english"))

#Strip whitespace (cosmetic?)
docs <- tm_map(docs, stripWhitespace)

#load library - stemming to aggregate words with common root
library(SnowballC)
#Stem document
docs <- tm_map(docs,stemDocument)

#creating document Matrix from existing corpus
dtm <- DocumentTermMatrix(docs)

#transpose of TDM
tdm <- TermDocumentMatrix(docs)
tdm

inspect(dtm)

#counting word frequency in DTM
freq <- colSums(as.matrix(dtm))

#length should be total number of terms
length(freq)

##create sort order (descending)
ord <- order(freq,decreasing=TRUE)

#inspect most frequently occurring terms
freq[head(ord)]

#Remove sparse terms
dtms <- removeSparseTerms(dtm, 0.15)

checking frequency

freq <- colSums(as.matrix(dtm))
head(table(freq), 20)

#view table of selected terms
freq <- colSums(as.matrix(dtms))
freq <- sort(colSums(as.matrix(dtm)), decreasing=TRUE)
head(freq, 14)

#plotting frequently occuring words
library(ggplot2)
wf <- data.frame(word=names(freq), freq=freq)
p <- ggplot(subset(wf, freq>300), aes(word, freq))
p <- p + geom_bar(stat="identity")
p <- p + theme(axis.text.x=element_text(angle=45, hjust=1))
p

findAssocs(dtm, c("xx" , "yy"), corlimit=0.85)
findAssocs(dtms, "word", corlimit=0.60)