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README.md

Twitter Sentiment

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

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=clang

OS 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

Install the necessary gems

(don't worry, # 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
gem install linguistics     # Linguistics methods

We will move this to a RubyGem when development is further down the road to make these dependencies more easily fulfilled.

Directory Structure

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.

Research Leads

AFINN

Descriptions

AFINN: A new word list for sentiment analysis

Simplest Sentiment Analysis in Python

Related

Twitter Mood

ANEW Sentiment-Weighted Word Bank

Measuring User Influence in Twitter

Projects/Papers

Sentiment strength detection in short informal text

Twitter as a Corpus for Sentiment Analysis and Opinion Mining

We Feel Fine

Modeling Statistical Properties of Written Text (lookup!)

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