By skyforbes 
The Science Behind Addiction in Recommendation Systems
Illustration: How recommendation systems filter content
Introduction:
In 2025, recommendation systems power the apps we can’t put down TikTok’s addictive For You page, Netflix’s spot on movie picks, Amazon’s scarily accurate product suggestions.
These systems handle billions of interactions daily, cutting through the noise to deliver content you will love. At their core are Content Based Filtering (CBF) and Collaborative Filtering (CF), two approaches that work differently but share one goal: keeping you engaged.
This article breaks down how they work, their pros and cons, and how they solve challenges like the cold start problem.