What is the LinkedIn Algorithm?
The LinkedIn algorithm is the automated ranking system that decides which posts appear in each user's feed, in what order, and with what reach. It processes millions of posts daily and distributes content based on a combination of relevance signals, engagement patterns, and user behavior.
Unlike Instagram's interest-based algorithm, which can show content from complete strangers, LinkedIn's algorithm has historically been more network-centric — prioritizing content from people and companies you're connected to or follow, along with content that's generating strong engagement within your professional context.
How the LinkedIn Algorithm Works
LinkedIn's algorithm evaluates content in stages:
Initial filtering: When you publish a post, the algorithm first checks it for spam signals, policy violations, and quality indicators. Low-quality posts are throttled before reaching any audience.
Small audience test: The post is shown to a small initial subset of your network. The algorithm measures how they respond in the first 30–60 minutes — primarily looking at likes, comments, shares, and dwell time (how long people pause on the post).
Engagement-based amplification: If the initial audience engages at above-average rates, the algorithm expands distribution — first to a broader segment of your network, then potentially to second-degree connections and followers of your commenters.
Human review (for viral content): Posts approaching very high engagement may be reviewed by LinkedIn team members to verify quality before further amplification.
Factors That Positively Influence the LinkedIn Algorithm
Early engagement velocity. The first hour after posting is critical. Comments and reactions in this window signal strong relevance and trigger broader distribution. This is why engaging with your own network before posting (warming the audience) and posting when your specific audience is most active online matters significantly.
Comments over reactions. LinkedIn weights comments more heavily than simple reactions. A post with 15 comments outperforms one with 50 likes in algorithmic terms. Content that provokes thoughtful responses — questions, controversial opinions, relatable professional experiences — naturally generates more comments.
Dwell time. LinkedIn tracks how long users linger on your post before scrolling past. Longer text posts, carousels that require swiping, and videos that retain viewers signal high value. Conversely, posts users scroll past immediately are penalized.
Native content over external links. LinkedIn's algorithm significantly deprioritizes posts that include external URLs (links to websites, articles outside LinkedIn). Posting an external link in the first comment — rather than in the post body — is a common workaround used to preserve reach while still sharing external resources.
Connection depth. Content from first-degree connections is shown more frequently than content from second-degree connections or company pages. This is why a founder's personal profile typically outreaches a company page with the same follower count.
What Reduces Reach
- Posting at irregular intervals or long hiatuses followed by sudden bursts
- Including external links directly in the post body
- Low engagement in the first hour (posting at 3am when your audience is asleep)
- Content that generates reactions but not comments (signals passive consumption)
- Tagging people who don't engage with the post (can trigger spam signals)
How publy.ch Helps
publy.ch generates LinkedIn content formatted to perform well within the algorithm — hook-first structure, comment-inviting questions, and native-content formatting. Consistent, quality-optimized posts build the sustained engagement patterns the LinkedIn algorithm rewards.