“ I have come up with the idea to create this project when the whole COVID-19 situation was starting to spread all over the globe. There was a time where the only news you could get was bad or worrying. So the idea of running a sentiment analysis classifier came to mind and filter through hundreds of headlines to show up only positive ones. This project was created mostly as a learning experience, I'm using NLTK to train and classify sentences, scrappy to scrape the RSS feeds, Django for the backend and Nextjs for the frontend. Everything is set in docker and being served from docker-compose through a digital ocean droplet. There is still a lot of things that could be improved on this project, but I'm happy with this first MVP version of it and happy to share with you. Please let me know what do you think, I will look forward to reading your feedback. I also hope that you find some value on this project and that it can help you read some positive news and brighten your day. In the future, I want to add more sources and remove the ones that greet you with a paywall although this seems to be the norm when it comes to news publishers. ” – Fábio Rosado
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