Take a tweet, extract a TON of information out of a short bit of text. Let's do this.
Start from scratch
Install RVM (if you haven't already)
Follow the instructions at beginrescueend.com. In short, install RVM:
$ 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 the necessary gems
# is a legitimate bash/zsh comment so you can still copy-paste)
gem install rake # Ruby Make - build tool gem install yard # YARDoc docuementation generator gem install yajl-ruby # Fastest JSON parser this side of the atlantic gem install cucumber # Cucumber BDD/TDD test suite gem install tweetstream # Ruby wrapper for Twitter Streaming API gem install twitter # Ruby wrapper for Twitter RESTful API gem install face # Ruby wrapper for Face (recognition) API gem install paint # Ruby pretty colorful console output gem install progressbar # Ruby pretty console progress bars
We will move this to a RubyGem when development is further down the road to make these dependencies more easily fulfilled.
dict/ contains the collection of dictionaries (bag of words, or BoW) being used for sentiment analysis.
lib/ contains the generalized libraries used by our toolkit.
research/ is a general placeholder for interesting papers and potential BoWs.
Modeling Statistical Properties of Written Text (lookup!)