In recent years, the “recommendations system” has also been included in the successful development of YouTube over time. So how does this recommendation system work and what exactly is its logic?
The video platform pioneer of the internet age and the one that has become a part of our lives. YouTubeLike many other sectors, over time, it ceases to maintain its system only on demand and makes improvements to create supply. The most effective place to see this is undoubtedly YouTube’s recommendation system.
Sometimes we are surprisingly confused about our likes and the content we relate to. offering suggestions YouTube can sometimes show us content that we think has nothing to do with it. But behind all this is an important algorithm and data study is known to be. When YouTube first launched the recommendation system in 2008, it only offered popular videos to users, but with the improvements, it took the data and recommendation algorithms to a different dimension.
Simple principle of recommendations: Videos that will add value
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In an article published on the YouTube Blog, for the recommendation system In addition to important information, there is also a good example to understand its logic. The article, which states that each user has different viewing habits, includes the following example: For example, if you like tennis videos and the YouTube recommendation algorithm notices that other people who like tennis videos like you also like and watch jazz music videos, it may suggest jazz videos to you even if you have never watched them before. . YouTube believes that the simple principle of recommendations is for users. will add value It says it’s to deliver videos.
How are recommendations personalized?
Suggestions on YouTube appear in two places for users. These are the home page and the “next” panel next to the videos watched. YouTube’s recommendations are like clicks, watch times, etc. according to many different factors it varies. Here are these factors:
Click:
Clicking on a video can also mean that the user finds it interesting. As a result of these clicks, the algorithm recommends similar or indirectly related content to users.
Watch time of the video:
Understanding that clicking a video doesn’t mean it’s actually watched, YouTube added the watch time feature to its algorithm in 2012. Adding watch times, YouTube says it saw a 20 percent drop in views. But YouTube says it doesn’t care because it’s more important to add value to viewers.
Survey responses:
In addition to viewing or watching times, YouTube also pays attention to feedback to understand whether its users are satisfied with the videos they watch. For this reason, YouTube offers users a 5-star survey after watching videos, asking them to rate the content. As a result of these answers, it determines the content that the user is related to.
Share, like or dislike:
Depending on whether users share, like or dislike the video they watch, the YouTube recommendation algorithm gets information about the content that the user is interested in. The fact that users use these buttons actually means feedback for the YouTube algorithm.