I'm trying to understand how LinkedIn's feed ranking works under the hood. What signals does the platform use to decide which posts show up at the top of a user's homepage? Is it engagement history, how close you are to the poster in your network, or how relevant the content is? How are these factors weighted and updated over time? Looking for a high-level breakdown.
How does LinkedIn's algorithm prioritize content in users' feeds?
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When I first tried to boost my LinkedIn profile, I noticed that posts with just a few likes from colleagues in the same department appeared in the feed much later than those where I tagged people from my wider network. It turned out that the algorithm doesn’t just prioritize direct interactions but also the "depth" of connections: if your content gets responses from people you frequently engage with (comments, likes, shared projects), the platform considers it more relevant to your audience. So, I started commenting on and sharing colleagues’ posts before publishing my own articles—and their reach skyrocketed.
Later, I realized that content tied to trending topics in my field (like new web development frameworks) gets an extra boost from LinkedIn. The algorithm also considers the subject matter, comparing it to your past activity: if you often read or like articles about React, the system will suggest similar content and increase its visibility. As a result, I adjusted my posting strategy: first, I "soak in" the network by engaging with others, then I share content relevant to my niche—so the algorithm accounts for interaction history, network proximity, and topic relevance while constantly adjusting the weight of these signals.