corpus

How do you print a small sample, or first line, of a corpus in R using the tm package? I have a very large corpus ( > 1 GB) and am doing some text cleaning. I would like to test as I apply cleaning procedures. Printing just the first line, or first few lines of a corpus would be ideal. # Load Libraries library(tm) # Read in Corpus corp <- SimpleCorpus( DirSource( "C:/TextDocument")) # Remove puncuation corp <- removePunctuation(corp, preserve_intra_word_contractions = TRUE, preserve_intra_word_dashes = TRUE) I have tried accessing the corpus several ways: # Print first line of first element of

actually I am trying to do a sentiment analysis based on twitter data using the naive bayes algorithm. I have a look on 2000 Tweets. After getting the data into R studio I split and preprocess the date as follows: train_size = floor(0.75 * nrow(Tweets_Model_Input)) set.seed(123) train_sub = sample(seq_len(nrow(Tweets_Model_Input)), size = train_size) Tweets_Model_Input_Train = Tweets_Model_Input[train_sub, ] Tweets_Model_Input_Test = Tweets_Model_Input[-train_sub, ] myCorpus = Corpus(VectorSource(Tweets_Model_Input_Train$SentimentText)) myCorpus <- tm_map(myCorpus, removeWords, stopwords(

I came across several methods for measuring semantic similarity that use the structure and hierarchy of WordNet, e.g. Jiang and Conrath measure (JNC), Resnik measure(RES), Lin measure (LIN) etc. The way they are measured using NLTK is: sim2=wn.jcn_similarity(entry1,entry2,brown_ic) sim3=entry1.res_similarity(entry2, brown_ic) sim4=entry1.lin_similarity(entry2,brown_ic) If WordNet is the basis of calculating semantic similarity, what is the use of Brown Corpus here? arturomp Take a look at the explanation at the NLTK howto for wordnet. Specifically, the *_ic notation is information content .

I have a 1,500-row vector created from a Twitter search using the XML package. I have then converted it to a Corpus to be used with the tm package. I want to ultimately create a wordcloud with some (the most frequent) of those words, so I converted it to a TermDocumentMatrix to be able to find terms with a minimum frequency. I create the object "a", which is a list of those terms. a <- findFreqTerms(mydata.dtm, 10) The wordcloud package does not work on document matrices. So now, I want to filter the original vector to include only the words included in the "a" object (If I use the object

There are datasets with usual mail spam in the Internet, but I need datasets with fake reviews to conduct some research and I can't find any of them. Can anybody give me advices on where fake reviews datasets can be obtained? Myle Ott Our dataset is available on my Cornell homepage: http://www.cs.cornell.edu/~myleott/ A recent ACL paper, where the authors compiled such a data set: Finding Deceptive Opinion Spam by Any Stretch of the Imagination Myle Ott, Yejin Choi, Claire Cardie, Jeffrey T. Hancock You might be able to find something in the references. Alternatively, you can mail the authors