Daily cross-source mention tracking for video generation: how many AI news articles, Hacker News stories, research papers and GitHub trending repos mention it. Deterministic whole-word counts of real stored items, updated daily.
| Source | Last 7 days | All stored days |
|---|---|---|
| News articles | 6 | 6 |
| Hacker News stories | 0 | 0 |
| Research papers | 4 | 10 |
| GitHub trending repos | 0 | 0 |
Each item counts once per day if its title (plus summary or description where available) contains video generation or one of its tracked aliases, matched case-insensitively on whole words. Heat on the Hype Meter board is scored as: raw = total mentions across sources in trailing 7 days; breadth = number of distinct sources with >=1 mention in those 7 days (1-4); heat = percentile rank of (raw * breadth) among all terms with raw>0, scaled 0-100, rounded. News and repo counts start the day tracking began; Hacker News and paper counts are backfilled from stored daily snapshots. No language model touches these numbers.