Using Jensen-Shannon Divergence to detect narrative regime shifts in daily news corpora [P]

I've been working on a system that scores AI sector news daily for sentiment, and the sentiment part turned out to be the least interesting problem. The harder question is whether you can detect a narrative shift in a news corpus before it shows up in aggregate scores. The approach uses JSD in two places. The first is over unigram/bigram frequency distributions of article body text, comparing a rolling 7-day window against the prior 7-day window, with a stop-word list tuned to strip AI and finance boilerplate that would otherwise dominate.