The YouTube algorithm prioritizes content based on a mix of relevance, engagement, and viewer behavior. It analyzes factors such as watch history, likes, comments, shares, and watch time to recommend videos that align with user interests. The algorithm uses machine learning to predict what viewers are likely to enjoy, based on previous interactions. It also considers metadata like titles, descriptions, and tags, ensuring content matches user searches. Videos with higher engagement rates, such as likes and comments, are more likely to appear in recommendations or search results. Consistent posting and audience retention also signal quality content, boosting a video's visibility. Ultimately, YouTube's goal is to keep viewers engaged, so the algorithm favors content that maximizes watch time and viewer satisfaction.

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