GitHub - matteoredaelli/twitter-r-utils: Twitter R utils

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Twitter R utils

Twitter utils written in R: hclust, wordcloud,..

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Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
output		output
web		web
README		README
negative-words.txt		negative-words.txt
positive-words.txt		positive-words.txt
tweets-cluster.R		tweets-cluster.R
tweets-fetch.R		tweets-fetch.R
tweets-normalize.R		tweets-normalize.R
tweets-wordcloud.R		tweets-wordcloud.R
twitter-sentiments.R		twitter-sentiments.R
twitter-util.R		twitter-util.R

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Matteo DOT Redaelli AT gmail DOT com
http://www.redaelli.org/matteo/

Code and suggestions from http://www.inside-r.org/howto/mining-twitter-airline-consumer-sentiment

Hu and Liu’s “opinion lexicon” categorizes nearly 6,800 words as positive or negative and were downloaded from Bing Liu’s web site: http://www.cs.uic.edu/~liub/FBS/opinion-lexicon-English.rar