Sentimenticon

The Sentimenticon module provides methods for returning word-level and average word sentiment scores, currently for English only.

The sentiment data is from the article Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter Peter Sheridan Dodds, Kameron Decker Harris, Isabel M. Kloumann, Catherine A. Bliss, and Christopher M. Danforth

Sentiments range from -1.0 to 1.0, where -1.0 is the most unfavorable, and 1.0 is the most favorable. Words must be downcased; sentences must be downcased and tokenized.

In addition, a Sentiment object can be inspected for the original values from the Hedonometrics paper.

Examples:

 >> require 'sentimenticon'
 >> analyzer = Sentimenticon::Analyzer.new; true
 => true
 >> analyzer.word_sentiment("love")
 => 0.855
 >> analyzer.word_sentiment("terrorist")
 => -0.925
 >> analyzer.average_word_sentiment("I love my happy friend.".downcase.scan(/\w+/))
 => 0.573
 >> analyzer.average_word_sentiment("I hate my terrorist enemy.".downcase.scan(/\w+/))
 => -0.332
 >> analyzer.average_word_sentiment("I fear our terrorist enemies.".downcase.scan(/\w+/))
 => -0.347

Add this line to your application's Gemfile:

gem 'sentimenticon'

And then execute:

$ bundle install

Or install it yourself as:

$ gem install sentimenticon

TODO: Write usage instructions here

After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and the created tag, and push the .gem file to rubygems.org.

Bug reports and pull requests are welcome on GitHub at https://github.com/willf/sentimenticon_rb