I built a daily AI news classifier to see whether journalism framing predicts short-term market moves.

I'm retired and have been writing software since the early 80s. A few months ago I got curious about whether AI-sector financial news has any predictive structure beyond simple bullish/bearish sentiment.

Not sentiment in the usual sense exactly more like what kind of story journalists are collectively telling. Earnings story, growth story, regulatory-risk story, market-correction story, etc.

So I built a pipeline that pulls in a few hundred AI-related articles every morning, runs sentiment scoring, classifies them into eight story types, then aggregates everything across six buckets: semis, hyperscalers, enterprise software, GPU cloud, datacenter infrastructure, and pure-play AI companies.

One thing I didn't expect: the mix of story types sometimes shifts before the aggregate sentiment does. I first noticed it while debugging the classifier in March. There were a couple of rotations where coverage moved from growth/earnings framing toward risk framing about a day or two before the overall sentiment scores rolled over.

No idea whether that translates into prices yet. Could easily be noise.

I pre-registered the test before looking at returns data because I know how easy it is to fool yourself with this kind of thing. Earliest analysis date is June 1 once I have \~60 trading days.

The other thing that's been interesting is how much AI coverage changed in April. Earlier coverage was dominated by capability narratives; now it's much more deployment/revenue/commercialization focused, and that shift has persisted longer than I expected.

Dashboard is at [https://knowentry.com/canary-dashboard/](https://knowentry.com/canary-dashboard/) if anyone wants to take a look at it. No signup/paywall/cookies it's a personal site. Mostly curious whether anyone here has worked on similar news-framing problems or knows relevant literature I should read.