About that data though, just publish that. Throw the data and tooling up on github or huggingface if it's a massive dataset. Would be interested in comparing methodologies for deriving sentiment.
159 stories that hit score 100 in my tracking, with HN points, comments, and first-seen timestamp.
Methodology: - Snapshots every 30 minutes (1,576 total) - Filtered to score=100 (my tracking cap) - Deduped by URL, kept first occurrence - Date range: Dec 2025 - Jan 2026
For sentiment, I ran GPT-4 on the full article text with a simple positive/negative/neutral classification. Not perfect but consistent enough to see the 2:1 pattern.