BasedNews

Headline Ingestion & Aggregation
N8N Workflow utilized in Headline Ingestion & Aggregation
People's Opinion Analysis
Political Bias Analysis
N8N Workflow utilized in Political Bias Analysis

Inspiration

In an era of polarized media, Based News was created to give readers a clearer picture of political news. We believe that informed citizens make better decisions, and informed citizens need access to unbiased information.

What it does

Based News is an AI-driven news aggregate, built to filter out the bias and deceit from mainstream media and other outlets, by conducting deep analysis on all sides of reporting. We offer general summaries of trending headlines, free from political bias, political bias analysis on different news outlets covering a headline, and a view into the public's opinion on a topic through Youtube comments.

How we built it

Our tech stack runs deep. For development of our Full-Stack application, we used Next.js App Router, with Supabase and Prisma, deployed on Vercel. To build our analysis pipelines, we utilized N8N, Parallel Web Systems, Exa.ai, and some custom JS scripts that took FOREVER to get working. We've attached diagrams depicting the systems and pipelines used in this project.

Challenges we ran into

Where do we even start. Firstly, we entered the project with a completely different idea than Based News. Our first five hours of the competition were landing on the idea of Based News and researching how in the world we were going to build it. Another challenge we ran into was honing our N8N skills and building robust workflows that function the way we intended. Additionally, we also faced the challenge of speeding up some of our workflows and API calls. The worst challenge of all was gaining insight on how the public viewed trending news. Ideally, we wanted to scrape Reddit or X, but Reddit API required you to request access and the X api rate-limited after 100 posts (NOT ENOUGH DATA). Hence, we found a workaround... Youtube Comments!!! We built our own API server using the Youtube Data API and a secret Python library to scrape all the popular comments off of videos related to specific headlines.

Accomplishments that we're proud of

An accomplishment that we are extremely proud of is the Headline Ingestion and Aggregation pipeline. It took the most time to complete and ended up working (almost) exactly how we wanted it to. Another accomplishment we are extremely proud of is collaborating on the same code base without any conflicts. Not running into any merge conflicts attributes greatly to the completion of this project.

What we learned

We are baffled by the number of technologies and concepts we worked with and learned about over the course of this competition. We want to give a huge shoutout to the boys at OpenNote, who taught us so much about vector stores and web search agents, which were essential to the core functionalities of our project.

What's next for BasedNews

BasedNews is barely an MVP. With the complex nature of the problem we are tackling, there are several bugs and inefficiencies in our systems. Our next steps are to finish and refine the core functions of the software, and optimize where we can.