This project is the result of the #devfest16 hackathon at Columbia University, which took place on February 5th, 2016.

The goal of this project is to analyse the variation in presidential candidates' emotions during debates. For that matter, we took as a sample the debate between Hillary Clinton and Bernie Sanders, which took place on February 4th, 2016.

Samples were taken from the following video:

The graph below shows the emotion levels of both candidates over time, during the two-hour long presidential debate on February 4th. Emotions range from anger to happiness.

Hovering over specific points show the estimated emotion levels on a video capture at a specific time. Additionally, emotions can be turned off and on in order to clarify the plots.

Just open app/index.html in a browser. Safari and Firefox are recommended. There are known issues with Google Chrome, which we hope to fix soon.

This project relies heavily on the following APIs:

• Microsoft® Project Oxford Video API
• Microsoft® Project Oxford Emotion API
• Alchemy® Entity Extraction API

• All data processing was done in Python 3 with MongoDB as the database, connecting through pyMongo.
• Text and grep-hacking was done using Sublime Text 3 and Atom.
• The front-end has been implemented using jQuery, d3.js and nvd3.
• The video file was split sequentially using Matlab.

We're MS in Data Science students at Columbia University. We go by the following names:

• Carlos Espino (Mexico)
• Amirhos Imani (Iran)
• Xavier González (Argentina)
• Diego Llarrull (Argentina)