Emotivate

How's everyone feeling today? Read the stories of the world on Emotivate, a visually stunning exploration of why we feel the way we do.

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Inspiration

Our team was inspired by how projects such as Waterloo Waterworks and forest fire maps were able to take data and give meaning to it through visualization. We were also inspired by the effect large collective data projects can have on people who feel emotionally isolated when they realize they are not alone. Finally, we were inspired by the potential of co:here's NLP API and wanted to see how we could use it to process data on a large scale to return useful and compelling conclusions.

What it does

With the combination of these ideas, we decided to develop a program that took responses to the prompt "How are you feeling today?" and added them to a dataset. Each response was analyzed and given a sentiment score. We wanted to give meaning to our data by representing it in a visually interesting way. The data was arranged using an algorithm that graphically layered each of the responses depending on how positive or negative their sentiment was, and we also developed an algorithm that concluded the overall "vibe" of everyone's day.

How we built it

In order to create our best work, we played to the strength of each of our team members. The backend connection and analysis algorithms were developed using Python, and the frontend was designed using Figma and implemented using JavaScript and Processing. Flask was used to bridge our front-end and back-end components together.

Challenges we ran into

Some of the challenges that we ran into were... basically everything. We had never set up Flask on our own before and were not experienced with using Python for the back-end. We struggled to debug and combine all of our code components since we had implemented the front-end, back-end, and Flask on three different computers.

Accomplishments that we're proud of

We're really proud of how we all learned so much from this experience and challenged ourselves out of our comfort zones. Despite a lot of hurdles and being really sleep-deprived, we persisted and continued to problem-solve until we were satisfied with what we came up with. We're really impressed with what we've created and our perseverance.

What we learned

We learned how to use the co:here API, how to work in a team with really diverse skill sets, and how to successfully deploy a complicated web application!

What's next for Emotivate

Human beings are hugely emotional creatures, so a web app that has access to a large group of people to accurately represent their emotions has enormous potential. We think that expanding Emotivate to the public web would be the logical next step in allowing it to create a unique value in society by allowing us to use our emotions to inform our habits.

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