Inspiration

Looking at the recent rise of Retail Investing and the boom in stocks like GME and AMC due to the catalyzing effect of social media, We were extremely fascinated by the effect of Social Media on Stock Prices. Hence we built Stockity to help compare Stock News, Social Media Sentiment, and the Technical analysis of stocks.

What it does

Stockity scrapes for information through Reddit and Twitter to find the stocks that are being talked about the most. On the first screen, you will be displayed with a word cloud of stock tickers. The bigger stocks are being talked about the most while the smaller ones are the stocks that are being talked about the least. Once a user clicks on a ticker on the word cloud, he is directed to a details page of the chosen stock. The details page shows the stock's performance on a graph, the sentiment analysis of the company that was aggregated in real-time , the top 5 Twitter posts talking about the company stock and news about the company. With Stockity you will always know what is the most talked-about stock !

How we built it

FIrst, we created a Trello board where we had our user stories and MVP planned out. After that was situated, we all agreed on what needs to be built, we created a rough sketch in Figma on how we wanted our app to look like. Looking at the Trello and Figma we decided on what our tech stack should be and what roles we would want to play in creating this project.

We built the backend in Python using Flask because Python has a lot of great tools for scraping websites and tools for sentiment analysis.

We built the frontend in Angular since the team had knowledge of it and how to use it.

Challenges we ran into

  1. We had a teammate ( backend developer ) who dropped out of the hackathon early and we were left with 3 team members, two frontend and one backend developer.
  2. Sparky - Did not know Angular and had to learn how to use it, creating a websocket connection to get the last traded price
  3. Knowing how to use the Twitter API and doing sentiment analysis on news articles.
  4. Fetching news articles through a query via RSS

Accomplishments that we're proud of

  1. Completing the MVP and what we designed on Figma
  2. We're proud of having built an application that can get trending stocks anytime through multiple sites along with technical details of the stock, fetching top tweets and displaying them, providing relevant new articles

What we learned

  1. Learned how to create a WebSocket in Angular
  2. Learned Angular
  3. Learned how to build a functional Flask API
  4. finance libraries like yfinance
  5. How to use Twitter API,
  6. How to create sentiment analysis in python

What's next for Stockity

We have a lot planned for the future of Stockity. We would love to add more data about trending stocks, a comparison of their share price with the social media sentiment, scrap other social media apps, add a Google search bar next to the Stockity search bar so that users are more likely to make Stockity a homepage for their browsers. We want to add the company's ESG score so users can check how socially responsible a company is. This is only the beginning and we cant wait to see where Stockity goes next.

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