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Proof of, MongoDB Atlas, and UIPath in screenshots above. (

Why Improving Awareness and Behaviour?

Our project is a great example for using data science for social awareness. Mainly targeted at large companies, we wanted to keep these companies accountable for their reaction to a pandemic. Our website allows users(consumers, potential workers, investors) to be aware of how each company treats employees, reacts to high stress situations, and provides to the community. We hope this project brings enough awareness to each companies' actions such that it changes these companies' behaviour for the better.


Companies are handling the COVID situation in a myriad of ways. We the consumers and workers of the future should use this period of adversity to see the company's true colors and see how they react and treat their employees. Did they fire all their interns? Do they force non-essential workers to work from home? These are things that should be remembered far after the COVID virus has subsided.

What it does

Remembering COVID uses a web-scraper to find news articles about how a Company is handling the COVID situation. Using semantic analysis these articles are computed into a metric that is displayed on our site. Using a clean frontend we display these scores. Now someone who is interested in investing or working at a company can see at a glance how the company in question reacted.

How I built it

Remembering COVID was built using Full-Stack Javascript for the website and backend. The scraping was done using Python with beautiful soup. The semantic analysis was also done in Python and used Google Cloud.

Challenges I ran into

One of our main challenges was running sentiment analysis on such a HUGE variety of news sources. We learned a lot about Google’s sentiment analysis service and was able to make use of MongoDB to display our calculations on our website. Another challenge we ran into was deciding how to display the information in a concise way so users can have a great experience navigating our website and they are able to see the sources that back our numbers up. Being a remote hackathon, not being in front of our teammates definitely made it harder to collaborate to the extent of which we had hoped. Nevertheless, through GroupMe, Discord, Zoom, and Slack we as a team overcame this challenge and worked hard to boost our overall collaboration effectiveness.

Accomplishments that I'm proud of

This was our first virtual hackathon weekend, and we didn’t know what to expect. We are proud of how we worked together although some of our internet connections were spotty at times, and we weren’t next to each other sharing ideas.

On the technical side, we are proud of being able to get news articles from so many different sources and formats and process them to get a number. In terms of data, this was probably the most complicated project that we have tried. Although there is more stuff to be done. Our team has grown so much and we have so many more ideas to improve on this project. Thank you to the Hack Quarantine team for coordinating such a great event!

What I learned

This weekend was the first weekend we did a hackathon remotely. We learned a lot about being flexible when faced with unexpected challenges and finding a way to use resources to boost productivity. One of the main things we learned this weekend was analyzing so much qualitative data with sentiment analysis and producing a fairly representative metric.

What's next for Remembering COVID

We plan to expand our web scraping to take into account more news sources and take care of biases that may come up. Another feature we would like to include in a blurb about how each company is handling the pandemic on the overall score so users can get a quick rundown of the company’s actions. Because of the data science tools we used, data is critical, and the more time we spend collecting data sets and building features, the more useful our website will become.

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