RadCompare

Changing the way people think about large-scale food delivery services: we think that's pretty rad.

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Inspiration

We were inspired by Radish, one of this year's sponsors for McHacks10, a food delivery service whose mission is to bring forth a more equitable relationship between restaurateurs, delivery drivers and consumers. We wanted to create a place where people can learn and understand others' opinions regarding various food delivery services, hopefully inspiring them to move away from large-scale delivery platforms and towards food delivery collectives that put members first. We think that's pretty rad.

What it does

RadCompare collects tweets regarding existing food delivery services, filters out retweets and spam and runs natural language processing (NLP) on the data to gather user and employee sentiment regarding food delivery services.

How we built it

For the backend functionality, we used Python, NumPy, pandas, Tweepy and Co:here. For the frontend design, we used HTML/CSS and JavaScript and used Figma to design the site's logos.

Main Challenges

  • Getting permission to use the Tweepy API
  • Configuring and understanding Co:here for NLP
  • Our .DS_Store being chaotic

Accomplishments we're proud of

  • Using technology to change the way people think about large-scale food delivery services
  • Learning how to use Co:here for the first time
  • Adapting to various challenges by using different frameworks
  • The overall website design and our rad logo :)

What we learned

  • The power of natural language processing (and how cool it is)!
  • More about Radish's mission and values and how they're changing the game when it comes to food delivery services

What's next for RadCompare

  • Full integration of the frontend and backend
  • Expanding our website

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