Idea: neural news network 6/28/25

Idea #5 of the week! Another idea that I’ve had for a couple years now.

Problem: It can be challenging to see the impacts of various news stories on other seemingly unrelated topics.

Solution: Create a news app that shows the neural network connection of one story to another.

Right now, the way we consume news is 1D. We read individual stories. And we try to piece them together in our brain. We end up creating some narrative, whether based in reality or not based on our biases.

For example, let’s say we read an article on a local company that just raised $10M in the FinTech space. But now I want to find out how FinTech funding has trended in the last few decades in my hometown of Kansas City. Then I want to see the specific policy changes that have impacted that funding over time across various municipalities. Then I may want to see how these compared to other MSAs across the country and the world. Maybe I go back to the original article and want to go to the local economic impacts and learn how many net new jobs it’s created (or removed).

The point is a news article is part of the overall information landscape. And that landscape is (at least) 2D. No news operates in a complete silo. There were, are, and will be upstream and downstream impacts. So our consumption of it should reflect this multi-dimensionality.

So what I’m proposing is that the fundamental structure of news consumption changes from 1D feeds to 2D network nodes.

The UI I imagine is something like an interactive Social Network Map. You can do this easily with notes on Graph View in Obsidian. But we’re just applying this to the news industry.

This app would improve our systems thinking ability because we can actually see how one story is related to another across every sector without having to dig for it ourselves.

1) Is there anything like this that already exists??

2) Would anyone actually use something like this??