suppose you have a file with two columns. The first column has, say, the name of the blog and the second column has a para of text from the blog. Suppose the second column is called myColumn, then you can get the common words into a separate dataframe with each column representing the frequency of a word with the following code:
myCorpus<-Corpus(VectorSource(myFile$myColumn)) #converts the relevant part of your file into a corpus
myCorpus = tm_map(myCorpus, PlainTextDocument) # an intermediate preprocessing step
myCorpus = tm_map(myCorpus, tolower) # converts all text to lower case
myCorpus = tm-map(myCorpus, removePunctuation) #removes punctuation
myCorpus = tm_map(myCorpus, removeWords, stopwords(“english”)) #removes common words like “a”, “the” etc
myCorpus = tm_map(myCorpus, stemDocument) # removes the last few letters of similar words such as get, getting, gets
dtm = DocumentTermMatrix(myCorpus) #turns the corpus into a document term matrix
notSparse = removeSparseTerms(dtm, 0.99) # extracts frequently occuring words
finalWords=as.data.frame(as.matrix(notSparse) # most frequent words remain in a dataframe, with one column per word