Our project took inspiration from the events that recently transpired on the subreddit r/wallstreetbets, which had us thinking: clearly there’s a plethora of useful information on these subreddits, but they aren’t exactly accessible to the everyday user. More than that, sometimes the subreddits, especially r/WallStreetBets, are downright toxic.

To put it simply: We want to democratize the financial advice across various subreddits and present it to our users!

What it does

We created a model to sift through low quality posts, and a Frontend to let people query the most important posts from the last couple days. We also created a notebook that details our work, as well as showcases fun statistics such as frequency of words, and scoring distributions.

Important posts were found through a scoring function that took in keywords, comment numbers, and their inherit Reddit submission score.

How we built it

To create our datasets, we used the Reddit PRAW API to scrape post content/information from the subreddits r/wallstreetbets, r/financialindependence, and r/options. These subreddits were chosen on consensus that they contained the most overall useful information. These datasets were uploaded to GitHub, where they can be pulled and updated before execution. The datasets were then each put through a model, which utilizes a scoring function based on keywords, comment numbers, and their inherent reddit "score." The scoring information was used for our plots on the notebook as well as the website, where the highest ranked posts(according to the model) are outputted onto the homepage.

The website was built through HTML, Flask, and JavaScript. We also used Pandas extensively, and nltk for language processing.

Challenges we ran into

Creating the website was far more difficult than we anticipated, as none of us had much experience in frontend developement. We're also a group of relative novices(this is our second Hackathon), so we did a lot of learning on the fly! Timing was also an issue, we had a lot of ideas we wanted to implement(like a search bar and a nicer UI), but the time crunch got to us.

Accomplishments that we're proud of

We're super proud of producing an MVP, as well as learning as much as we did. We're also proud of how, despite not knowing each other that well, we were able to learn and actually make something we all think is genuinely useful.

What we learned

We learned a ton! About collaboration, about technologies, and about eachother. We learned more about technologies like language processing, API interaction, and frontend developement. We also learned(after a lot of trial and error) how to more effectively use GitHub.

What's next for Reddit Financial

We'd like to add more features to our Web App, such as making it functional across more subreddits, adding search functionality, and getting our filtering even more precise by adding more data to our datasets. We hope y'all support us in this endeavor!

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