The LinkedIn algorithm is probably one of the most misunderstood topics in digital marketing.
Ask ten creators how it works, and you’ll likely get ten different answers.
Some swear by posting times. Others insist on three hashtags, avoiding external links, or replying to comments within the first hour.
The problem?
Very little of that advice comes directly from LinkedIn.
So instead of repeating myths, let’s look at what LinkedIn has actually documented about how its feed works.
1. LinkedIn algorithm first checks for spam
Every post goes through an initial quality filter.
LinkedIn looks for signals that a post might be:
- Spam
- Engagement bait
- Misleading
- Low quality
- Excessively promotional
If a post is classified as low quality, its distribution can be limited before many people see it.
This comes directly from LinkedIn’s engineering blog and official documentation.
2. Your audience does NOT see your post all at once
This is probably the biggest misconception.
LinkedIn doesn’t push your post to all your followers.
Instead, it shows it to a small sample of your audience first.
If those people respond positively, LinkedIn gradually expands distribution.
Think of it like:
50 people
↓
500 people
↓
5,000 people
↓
50,000 people
The numbers aren’t published, but staged distribution is well documented by LinkedIn.
3. Early engagement matters…
…but not simply because it’s “early.”
What matters is whether people actually interact in meaningful ways.
LinkedIn has repeatedly said it values:
- Comments
- Replies
- Shares
- Saves (not officially weighted, but widely believed to matter)
- Meaningful reactions
A thoughtful comment is generally considered a stronger signal than a simple Like.
4. Comments are not all equal
LinkedIn has said it tries to understand conversation quality.
Examples:
Good:
“We’ve seen the same issue with enterprise procurement.”
Better signal.
Bad:
Great
Nice
Amazing
These contribute much less value.
5. Dwell time matters… probably
LinkedIn has acknowledged using what it calls “dwell time.”
That means:
Did someone stop scrolling?
Did they spend time reading?
It doesn’t necessarily mean they clicked.
Simply pausing to read appears to be a positive signal.
LinkedIn has confirmed this publicly.
6. Relevance is more important than follower count
Someone with 2,000 highly relevant followers often gets more reach than someone with 50,000 uninterested followers.
LinkedIn tries to predict:
“Will THIS member care about THIS post?”
rather than simply rewarding popularity.
7. Expertise matters
LinkedIn has said it attempts to surface content from people with expertise.
For example:
A cybersecurity professional posting about ransomware
is more likely to be viewed as authoritative than someone who posts about unrelated topics every day.
Your profile, work history, skills, and posting history all help establish topical authority.
8. Native content usually performs better
This is observed consistently.
Native:
- Images
- PDFs
- Videos
- Text posts
often receive broader distribution than posts that primarily drive users off LinkedIn.
LinkedIn algorithm wants users to stay on the platform.
However, LinkedIn has never officially said “external links are penalized.”
9. Consistency helps
LinkedIn has never said:
“Post five times per week.”
There is no official posting frequency.
However, consistent creators generally build stronger audiences because:
- followers expect content
- expertise accumulates
- engagement compounds
10. Relevance beats virality
A viral post about productivity won’t necessarily help if you sell ITAD software.
LinkedIn’s recommendation systems increasingly optimize for:
“Who should see this?”
instead of
“How many people can we show this to?”
This is especially important for B2B.
Things people say that are NOT proven
These are common claims, but there is no public evidence from LinkedIn supporting them.
Never edit your post.
Hashtags boost reach.
Three hashtags are optimal.
The first hour determines everything.
Posting at exactly 8:00 AM doubles reach.
External links are automatically penalized.
Using emojis reduces reach.
Using AI-written content is detected and suppressed.
None of these have been confirmed by LinkedIn.
What consistently works
Based on LinkedIn’s published guidance and large-scale analysis, the strongest signals appear to be:
- Content that’s genuinely relevant to a defined audience.
- Posts that encourage meaningful discussion, not engagement bait.
- High-quality comments and conversations.
- Clear topical expertise over time.
- Strong dwell time (people actually reading the post).
- Native formats such as documents, images, and videos.
- Consistent publishing within your area of expertise.
This isn’t meant to be the final word on the LinkedIn algorithm.
It’s my interpretation of what LinkedIn has publicly documented through its engineering blogs and research papers.
If you disagree with any point, I’d genuinely love to hear why. Share the official source or your reasoning in the comments. If I’ve missed something or got it wrong, I’ll happily update the post. Good discussions make all of us better.
Understanding the algorithm is only the first step.
The real advantage comes from consistently creating content your audience wants to engage with.
Retentia Technology helps businesses develop data-driven content, SEO, LinkedIn, and AI search strategies that turn visibility into qualified opportunities.
Get in touch to discuss your growth goals.
This article was originally published on the Retentia Technology LinkedIn page and has been republished here for our website audience.