Happiness Observer

Would you like to know what the entire work thinks about a certain concept? How much happiness there is in words like love, hate or together? Happiness Observer performs advanced text mining and data analysis to extract contextual information from Twitter, and decides whether the general feeling about a concept is positive or not.

Happiness Observer is a program that allows you to determine whether the general mood of a concept is positive or negative, based on data mining from real time Tweets. The scientific term is called "sentimental analysis", although it sounds more poetic than rather technical.

The approach used here uses classifiers which are built from machine learning algorithms. Traditional sentimental analysis is performed using keywords and tables approaches. They might have better precision, but they are not adaptable.

I am transparent in how I classify individual tweets. Other sites do not show you the classification of individual tweets and only show aggregated numbers, which makes it difficult to assess how accurate their classifiers are.

Only English is supported right now, but the application is learning every day :)

The application has been developed by Enrique López Mañas. I'm interested in machine learning, artificial intelligence and computer vision. I'm of course a geek of any mobile platform :)

If you want to contact me, please drop me a line at eenriquelopez@gmail.com"