InstaFans

Inspiration

Having met each other for the first time in this hackathon, our team members wasted no time getting acquainted with one another. We were sharing social medias and browsing through each others Instagram pages when we noticed just how hype our comments were! We were one-upping each other on who has the best comment section vs the lamest one. How would we ever decide?

The solution is InstaFans! a fun way to see who your hypest and your angriest commenter is.

What it does

InstaFans is a light-hearted website that takes comments from your instagram account and shows you which followers are your:

Biggest Hypeman
Secret Admirer
Lowkey Toxic (friend)
Probably a bot

…and more to come!

InstaFans has got you covered if:

You want something fun to start conversation
Your curious about to know more about your instagram followers

How we built it

Cohere NLP API
Figma
ReactJS
MongoDB
NodeJS

Challenges we ran into

While we were working with one of the API for scraping, the API gave us a a very large JSON file with tons of data, most of it being useless to us. To only grab the specific data fields we needed, we worked on trying to filter the JSON file, loop through it and only grab the necessary parts, etc. With persistence and patience, we thankfully figured out a way to get the required fields.

Accomplishments that we're proud of

First, we’re proud to have completed and launched a successful end-to-end project. We worked tirelessly from brainstorming → Designing → Development → Launching → Testing–all within 36 hours!

What we learned

-Learned how to deal with API that are not the most efficient -Some of us learned about how to work with APIs and POST/GET with node.js -How to implement a nature language processing model with Cohere’s API

What's next for InstaFans

We know that InstaFans has a bright future ahead knowing that the digital space is becoming increasingly necessary for connections with peers.
To increase our reach, we plan to implement other social media apps into our platform (i.e. Facebook, TikTok, Twitter). Secondly, we plan to further our algorithm focusing on producing less biases, more accuracy, and understanding of basic human behaviour on social media.