Getting The Top Terms for each Topic in LDA in R

Question

I am implementing LDA for some simple data Sets , I am able to do the topic modelling but the issue is when i am trying to organise the top 6 terms according to their Topics , I am getting some numerical values ( maybe their indexes )

# docs is the dataset formatted and cleaned properly    
dtm<- TermDocumentMatrix(docs, control = list(removePunctuation = TRUE, stopwords=TRUE))
ldaOut<-LDA(dtm,k,method="Gibbs",control=list(nstart=nstart,seed=seed,best=best,burnin=burnin,iter=iter,thin=thin))

# 6 top terms in each topic 
ldaOut.terms<-as.matrix(terms(ldaOut,6))    

write.csv(ldaOut.terms,file=paste("LDAGibbs",k,"TopicsToTerms.csv"))    

The TopicsToTerms file is Generated like ,

    Topic 1 Topic 2 Topic 3 
1   1        5       3  
2   2        1       4  
3   3        2       1  
4   4        3       2  
5   5        4       5  

While I want The Terms (top words for each topic) In the tables , like the following -

    Topic 1   Topic 2     Topic 3   
1     Hat       Cat        Food 

Answer 1

You just need one line of code to fix your problem:

> text = read.csv("~/Desktop/your_data.csv") #your initial dataset
> docs = Corpus(VectorSource(text)) #converting to corpus
> docs = tm_map(docs, content_transformer(tolower)) #cleaning
> ... #cleaning
> dtm = DocumentTermMatrix(docs) #creating a document term matrix
> rownames(dtm) = text

After adding that last line, you can proceed with the remaining code, and you'll get the Terms, and not their indexes. Hope that helped.