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by san10
259 days ago
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Ty for the question. The system is new (built last week), so I don't have reliable production data on false positive rate yet. Right now my current detection logic is basically:
- 25%+ CCU growth vs 7-day baseline
- YouTube video mentioning game within 48h
- Keyword match (currently using regex and exploring other methods) If I have to guess where the false positives are going to come from:
- YouTuber plays game (drives CCU) but doesn't mention new mechanic
- CCU (concurrent users) spike from external event (streamer or holidays)
- Generic update videos that don't indicate mechanic type Next step is running it for 30 days and tracking precision/recall. More of that in the GitHub itself. Appreciate the question, since it's the main thing I need to validate. |
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