Buy 2 CleanX, Get 1 Free 98.01 Buy 3 CleanX, Get 2 Free 135.00. Therefore, putting your footwear in good condition help define your personal character and make you stand out in a crowd. Probably i will have to subtract my set of words from a dictionary of words. There is a saying that ‘you can know a person by their shoes’. Now, I only have to figure out how to remove the non proper english words. This cleaning process has worked for me quite well as opposed to the tm_map transforms.Īll that I am left with now is a set of proper words and a very few improper words. # Get rid of references to other screennamesīefore doing any of the above I collapsed the whole string into a single long character using the below. # Take out retweet header, there is only oneĬlean_tweet <- str_replace(clean_tweet,"RT ","")Ĭlean_tweet <- str_replace_all(clean_tweet,"#*","") I have figured out part of the solution for removing retweets, references to screen names, hashtags, spaces, numbers, punctuations, urls. (Note: The transformation commands in the tm package are only able to remove stop words, punctuation whitespaces and also conversion to lowercase) If a tweet is RT One man stands between us and annihilation: 3: OH HELL NO! - July 23 on Foxtel cleaning the tweet I want only proper complete english words to be left, i.e a sentence/phrase void of everything else (user names, shortened words, urls)Įxample: One man stands between us and annihilation oh hell no on (using mc.cores=1 and lazy=True as otherwise R on mac is running into errors) tdm<-TermDocumentMatrix(xx)īut this term document matrix has a lot of strange symbols, meaningless words and the like. Xx<-tm_map(xx,removeWords,stopwords(english), lazy=TRUE, 'mc.cores=1') Xx<-tm_map(xx,strip_retweets, lazy=TRUE, 'mc.cores=1') Xx<-tm_map(xx,removePunctuation, lazy=TRUE, 'mc.cores=1') Xx<-tm_map(xx,stripWhitespace, lazy=TRUE, 'mc.cores=1') I have carried out the following on the corpus xx<-tm_map(xx,removeNumbers, lazy=TRUE, 'mc.cores=1') I extracted tweets from twitter using the twitteR package and saved them into a text file.
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