I guarantee you've wondered why Instagram, TikTok, or YouTube show you certain reels.
Just watch or like a few reels, and then your feed gets filled with similar content.
It's all thanks to machine learning algorithms.
These algorithms have one goal — to keep you in the app or on the site for as long as possible. In other words, to consume content.
Remember in my last post I mentioned that the model takes a huge number of examples from the past and tries to find patterns? The principle here is almost the same. The algorithms analyze your behavior in real-time.
What the Algorithm Analyzes
The algorithm looks at, for example:
- which videos you watch;
- which ones you like;
- which ones you scroll past;
- whether you watch videos to the end;
- whether you open comments;
- whether you scroll through comments.
Based on this data, the machine learning algorithm tries to predict which next video you will like.
How It Works in Simplified Terms
In simplified terms, you could say: the algorithm predicts the probability — whether you will like the next video or not.
If the algorithm predicts a high probability that you will like the next video, you get it in your feed.
If the probability is low — you probably won't see it.
Why the Feed Isn't Random
Any reel feed on Instagram or news feed on VKontakte is not a random collection of posts and videos.
It's the result of an algorithm that has learned from your behavior.
Thus, the social network gradually starts to "understand" what interests you. And sometimes — even better than you do.
Why This Matters to Platforms
The better such an algorithm is optimized, the more time you spend inside the social network.
And the more time you spend in the app, the more ads the platform can show you.
In the end, this is directly related to money: more reach, more ad impressions, more revenue.
Conclusion
So, a "smart" feed is not magic or randomness. It's quite practical machine learning that learns in real-time from your actions and tries to select the next content so that you stay longer.