How Streaming Recommendation Algorithms Decide What You See
Streaming platforms surface a small slice of a huge catalog. Here's how that recommendation decision actually gets made.
Streaming platforms use recommendation systems to decide which small fraction of a massive catalog to actually surface to each individual viewer, since most people would never manually browse a full library on their own.
What actually feeds the recommendation
Viewing history, how long you watched before stopping, and what similar viewers with comparable tastes enjoyed all feed into a model predicting what you're statistically likely to watch and enjoy next.
Why this shapes what gets made, not just what gets shown
Because these systems heavily influence how much exposure a given show or film actually receives, platforms increasingly consider algorithmic performance when deciding what content to commission in the first place, meaning the recommendation system shapes production decisions, not just viewing choices.