Show HN: Viral Potential Predictor

The analysis they ran in their research paper found most surface features don’t meaningfully separate viral from non‑viral outcomes. So the tool isn't actually predicting if your launch title will go viral, it's more like checking for heuristics and descriptive patterns.

Cool idea though! And they're on the front page lol

As someone who has spent an embarrassing amount of time researching Hacker News title trends over the years, I was excited to look at the methodology (https://hn-ph.vercel.app/analysis) but after looking at it, I am calling shenanigans afoot.

That's not a methodology paper and it doesn't explain how the model being advertised works in the spirit of open machine learning research; given that the startup is an AI startup, I assume that the actual model is more sophisticated. As Section 8 notes: "This analysis is descriptive and intended to summarize empirical patterns."

It's an exploratory data analysis which not only does not explain the methodology around how the model is constructed, but it also makes a number of assumptions that imply the people making it without proper context of how Hacker News works:

1. The extreme right-skewed nature should have raised a very large number of flags in the statistical methodology and calculations, but it mostly ignores them. The mean values are effectively useless, the p-values even more useless. It doesn't point out that the negative performing terms are likely spam.

2. It does not question why there are so few questions with a title >80 characters (answer: 80 characters is the max for a HN submission)

3. The analysis separates day of the week and hour: you can't do that. They're intrinsically linked and weekend behavior with respect to activity is far different than on weekdays.

4. "Title length has a weak relationship with score (Pearson r = -0.017, Spearman r = 0.048, n = 100k)". No statistician would call that a weak correlation; those values are effectively no correlation.

There is also no person tied to this paper, just the "Memvid Research Team", which raises further questions.

Show HN: I built a Rust compiler in Python with JavaScript using Java on Android

Found a relevant comment here: https://github.com/memvid/memvid/issues/86#issuecomment-3560...

> We’ve rebuilt everything from the ground up for Memvid v2, new format, new core, new benchmarks, no QR hacks. It’s a real storage engine now, crash-safe, deterministic, and fully verified with a proper TOC, WAL, Merkle tree, and time index.

So I guess the QR code hack isn't a thing any more.