Take a tweet, extract a TON of information out of a short bit of text. Let's do this.
Get it running
1. Install RVM (if you have it already, skip to step 2)
bash -s stable < <(curl -s https://raw.github.com/wayneeseguin/rvm/master/binscripts/rvm-installer) source ~/.bash_profile
rvm install 1.9.3
Install XCode from the App Store if you haven't already (it's free).
rvm install 1.9.3 --with-gcc=clang
OS X users may be interested in Jewelry Box, a Cocoa UI for RVM.
Install Ruby from RubyInstaller
The DevKit is also required to install some of the gems described below
2. Install the necessary gems
gem install bundler bundle install
3. Run it
bundle exec ./app.rb
lib/ is where the bulk of the code lies. It is all of the library files used by our app.rb.
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.
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.
Modeling Statistical Properties of Written Text (lookup!)