The YouTube algorithm assesses user behavior like watch time, engagement, and preferences to recommend videos. It analyzes past interactions to predict what content a viewer might enjoy, prioritizing relevance and quality. Factors such as click-through rate, likes, comments, and shares influence video visibility. Moreover, the algorithm considers user demographics and browsing history to personalize recommendations. Continuous learning and updates refine its accuracy, aiming to maximize user satisfaction and retention while promoting diverse content.
