Prof Stock

Inspiration

StockPiece and the overall lack of available compiled resources for professor ratings online

What it does

Problem Statement

Currently professor reviews can be scarce and highly fragmented with rating and opinions spread across unofficial sources (Rate my Professor and r/UCSD)

Our Solution

We created a website that scrapes all the necessary data and does sentiment analysis on opinions, creating aggregate scores for a professor at UCSD and also evaluating them on a quarter by quarter basis, ensuring that the score is up to date. This helps students know how a professor has performed in the past and how they may perform in the future based on how students currently seem to think of them.

Features

The main interactive element of the website allows users to buy and sell stocks in professors, similar to that of a prediction market, using a fake currency. The stock prices of a professor offer a way to potentially evaluate how good or bad a professor is performing currently with the aggregate scores serving as a past benchmark for investors.

How we built it

We setup a MongoDB cluster to function as the backend database and used Loveable to generate the frontend. We also leveraged Claude and Github Copilot to help with some of the core features of the backend, such as the login and stock calculations.

Challenges we ran into

We were running into issues with having both JavaScript and TypeScript files within the project, so we had to spend time converting the JavaScript files into TypeScript. We were also having difficulties with integrating the frontend generated by Loveable with our backend.