DEBATE IN EMOTION

Are you curious about how candidates feel during the debate? we explore and track their emotions when they speak

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Inspiration

This!

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What it does

The goal of this project is to explore and 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.

How we built it

  • 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.

This project relies heavily on the following APIs:

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

Challenges we ran into

  • Defining the scope of project.
  • Tailoring the data.
  • Merging data from various sources like matching the text with the image.
  • Data conversion

Accomplishments that we're proud of

We brainstormed to define a project from scratch. we defined it and did it!

What we learned

  • In the technical side we learnt how to use MongoDB and Project Oxford APIs.
  • In the political side, a lot!

What's next for DEBATE IN EMOTION

  1. We are excited to analyse other debates specially in the Republicans side
  2. Real-time emotion analysis of debates by using speech to text api
  3. Possibly sentiment analysis of tweets using debate hashtags
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