Engagement Pattern Mining
Algorithmic modeling of user interaction data (watch time, replays, saves, shares) to reverse-engineer what content types trigger dopamine loops and extended sessions.
Analysis
Decode what keeps your child watching. Our engagement analysis reverse-engineers algorithmic hooks by modeling interaction data—watch time, replays, saves, shares—to identify which content types trigger extended sessions and dopamine loops.
With behavioral modeling, we see which videos get rewatched, which creators get saved, which content sparks sharing. There's no need to guess what's most influential. The engagement patterns tell the story.
What this layer detects:
High-engagement content types and creators (most rewatched/saved)
Dopamine-triggering patterns and addictive content formats
Sharing behavior indicators (what content spreads socially)
Session extension patterns (what keeps them scrolling)
This layer reveals what the algorithm knows about your child's vulnerabilities—and exploits.
