The purpose of this application is to provide an easier way to get informed, it analyzes any given article and separates its sentences and words and thru a series of algorithms it returns a reduced version of the text, a reading of the article's sentiment (ideally, for a more objective point of view, ther reading should be neutral) and finally a list of wikipedia links to the article's most important mentions.
The application utilizes Google's Natural Language Processing API to get important information, then, it processes that information to return what aims to be an easier to digest and simplified version of the article.
In the sentiment measure section, what the user gets, is a reading of objectivity by the author of the original article. It doesn't determine if the actual information is of negative or positive nature, this means that if an article gets a reading of negative sentiment we can assume that this is the way the news was reported rather than the article being negative in nature.
This is the main page of the application, where the user feeds the raw article to be analyzed:
Here's how the results are displayed after the analysis:
The Technology used for this application is (HTML/CSS/JavaScript/jQuery).
This application was created by Eric Rubio @EricRubio589.
Background image by jer*ry (https://www.flickr.com/photos/ghb624/).