Study public attention to an AI policy proposal
Researchers studying AI-policy attention need a clean daily series with stated limits. This dataset joins news, search and community discussion and lists what was verified.
How policy research teams use Superintelligence News
- Compare the news spike with "AI ban" searches, which stayed at 11-15 (news coverage did not become search demand).
- Use the sources table to separate verified events from reports.
- Combine with Policywren for the federal rule record.
Neutral: the dataset takes no position on the bill, the speech or any person.
daily, 20-24 Sep 2026: news % of monitored online news (GDELT), US search interest 0-100 (24 Sep partial)
| Date | News % "super intelligence" | News % "superintelligence" | Search "super intelligence" | Search "AI ban" | HN stories |
|---|---|---|---|---|---|
| 2026-09-20 | 0.007% | 0.026% | 4 | 11 | 0 |
| 2026-09-21 | 0.021% | 0.019% | 4 | 15 | 1 |
| 2026-09-22 | 0.169% | 0.061% | 65 | 13 | 6 |
| 2026-09-23 | 0.220% | 0.085% | 50 | 14 | 4 |
| 2026-09-24 | 0.140% | 0.159% | 24 | 14 | 2 |
Source: Superintelligence News daily table, build of 24 Sep 2026 (products/superintelligence-news/store/listing.json; HF dataset CyberMax-tools/superintelligence-ban-bill-coverage). Sources: GDELT, Google Trends (US), Hacker News (Algolia API).
FAQ
Why not collect it ourselves?
You can from the same public sources; this saves the joins and the primary-source checks.
Is it updated?
Weekly while the story stays in the news; check the build date on the card.
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