The short answer
LinkedIn's Help Center says it looks at three kinds of signals: your identity (profile details such as location, workplace and skills), the content (how often it's viewed or engaged with, whether it provides knowledge or advice, how recent it is, whether it comes from someone you follow or are connected to, how constructive the conversation is), and your activity (what you react to, comment on, share and spend time viewing, and who you interact with).
Since March 2026 those signals feed a new ranking system. LinkedIn's engineering blog describes a Generative Recommender model that “processes more than a thousand of your historical interactions”, with retrieval built on large language models. LinkedIn says it wants the Feed to be “relevant to your interests, not a popularity contest” (LinkedIn newsroom, March 12, 2026).
Where this guide's facts come from
Only LinkedIn's own sources: its Help Center and Professional Community Policies, its newsroom and engineering blog, and posts written by named LinkedIn product and policy leaders on LinkedIn itself. Many guides quote third-party studies with exact reach percentages; LinkedIn has said such reports are “often incorrect”, so this guide doesn't repeat them.
Where feed posts come from
Your feed includes “posts from your connections, people and companies you follow, groups you belong to, and relevant updates from outside your network” (Help Center). For posts from outside your network, LinkedIn's recommended posts page says it looks for high quality, professionally relevant content with enough context that isn't overly promotional, and weighs member feedback such as disinterest signals and reports.
Being connected doesn't guarantee you see every post: LinkedIn's former VP of Product Gyanda Sachdeva wrote that it “doesn't mean we'll always show you every single post from people you are connected to or following” (December 2025). Since June 2026 post analytics split reach into in-network and out-of-network.
What the ranking model watches
LinkedIn's engineers say the model learns from “what you've read, liked, commented on, returned back to, or simply scrolled past”, splitting actions into passive ones (click, skip, long dwell) and active ones (like, comment, share). For each post it reads the format, author information, engagement counts and the post text. LinkedIn also says its systems don't use demographic information such as age, race or gender.
Product director Rishi Jobanputra put it simply in June 2026: a like is “only one of many” signals; reading the full post, saving it, sending it to a friend, a thoughtful comment and a repost all signal that the post was valuable.
What LinkedIn shows less of
- Engagement bait. LinkedIn says it is reducing “repetitive, low-substance posts and engagement bait, such as 'comment to agree' prompts or videos that don't match the text” (March 2026).
- Artificial engagement. Its spam policy lists emoji or reaction polls that boost engagement artificially, chain-letter posts asking for likes and shares, and repetitive comments. Its Community Policies say not to agree ahead of time to like or re-share each other's content, and LinkedIn says it limits the reach of posts boosted by engagement pods.
- Automated comments. Comments posted by a browser extension, script or third-party tool without a person clicking Comment are not allowed (Gyanda Sachdeva, February 2026).
- Generic AI content. Using AI to help you write is fine, but content that looks AI-generated and lacks a clear perspective “is less likely to be widely distributed beyond a person's immediate network” (Laura Lorenzetti, May 2026). In August 2026 Chief Product Officer Hari Srinivasan said members now see 40% fewer views of what LinkedIn classifies as AI slop.
Myths LinkedIn has answered
| Popular tip | What LinkedIn says |
|---|---|
| Hashtags boost reach | “Hashtags do not impact distribution” (Sachdeva, Dec 2025) |
| Posting twice a day hurts you | Posting more than once a day “won't hurt your total reach”; close-together posts compete, and people see the most relevant one (Sachdeva, Dec 2025) |
| Scheduled posts get less reach | “No, scheduling a post doesn't impact distribution”, as long as you don't post a lot back-to-back (Jobanputra, Feb 2026) |
| The first hour decides everything | Posting when your audience is online “can help”, but “timing isn't everything” and strong content keeps showing up for days (Jobanputra, Jan 2026) |
| Links kill your reach | Make sure the post “gives enough context that it could stand alone without the link” (Jobanputra, 2025). LinkedIn has published no link penalty figure. |
Sources: posts by LinkedIn product leaders on LinkedIn, read November 7, 2026.
How you control your own feed
You can sort the feed by “Most relevant first” or “Most recent first”, for one visit or as a default in Settings (Help Center). Telling LinkedIn you're not interested in a post, or reporting it, is feedback the system uses for recommended posts, and since 2026 there's also a “seems like AI slop” option. LinkedIn says no single piece of feedback decides how a post is distributed.
What to do this week
PersonaXpand schedules your LinkedIn posts with your other networks, which LinkedIn says doesn't affect distribution, so you can post consistently and spend your time in the comments. See also how to schedule LinkedIn posts and our guides to the X and Facebook algorithms.
- Teach something. Whether a post “provides knowledge or advice” is one of LinkedIn's listed content signals.
- Write in your own voice, with a clear point of view. Use AI to help, not to replace you.
- Give full context in the post, then add a link if it helps.
- Post 2 to 5 times a week. That's LinkedIn's own suggestion; Sachdeva wrote that members who post twice a week see up to 5x more profile views on average.
- For video: a text hook, burned-in captions and engaging visuals, per the same post.
- Reply to comments yourself and join other people's conversations with something new to add. Never automate comments.