Take a tweet, extract a TON of information out of a short bit of text. Let's do this.
######(from beginrescueend.com)
bash -s stable < <(curl -s https://raw.github.com/wayneeseguin/rvm/master/binscripts/rvm-installer)
source ~/.bash_profile####Linux Users
rvm install 1.9.3####Mac Users Install XCode from the App Store if you haven't already (it's free).
rvm install 1.9.3 --with-gcc=clangOS X users may be interested in Jewelry Box, a Cocoa UI for RVM.
####Windows users Install Ruby from RubyInstaller
The DevKit is also required to install some of the gems described below
gem install bundler
bundle installbundle exec ./app.rblib/ is where the bulk of the code lies. It is all of the library files used by our app.rb.
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twitter-sentiment/: libraries in our namespace.-
input/: libraries that contact the outside world via APIs (generally). -
output/: libraries that send data outward. -
parser/: libraries that get data form inputs, parse them, and give weights to be aggregated. -
prefs/: preferences and constants to be used by any of the aforementioned libraries/files.
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dict/ contains the collection of dictionaries (bag of words, or BoW) being used for sentiment analysis.
research/ is a general placeholder for interesting papers and potential BoWs.
AFINN: A new word list for sentiment analysis
Simplest Sentiment Analysis in Python
ANEW Sentiment-Weighted Word Bank
Measuring User Influence in Twitter
Sentiment strength detection in short informal text
Twitter as a Corpus for Sentiment Analysis and Opinion Mining
Modeling Statistical Properties of Written Text (lookup!)