Algorithm
Social media algorithm
Also known as: social feed algorithm, social recommendation algorithm, feed ranking algorithm
A social media algorithm is the ranking and recommendation system a platform uses to decide which posts each person sees, and in what order. It scores candidate content against signals such as predicted engagement, relevance to the viewer's interests and recency. Because every feed is assembled per user, two people following the same accounts rarely see the same thing.
What it is
It is a set of machine learning models that retrieve a pool of candidate posts, then rank them by predicted value to the individual viewer. Candidates come from accounts a person follows and, increasingly, from recommended content they have no connection to. The output is a personalised feed rather than a straight chronological list.
Why it matters
For most brands the algorithm, not the follower count, decides how many people actually see a post, which makes it the main gatekeeper between publishing and distribution. It also shapes discovery, because recommendation surfaces can put content in front of people who have never heard of you. Understanding the signals a platform optimises for is the difference between posting and being seen.
How it works
Platforms typically weight explicit engagement such as saves, shares, comments and follows alongside implicit signals such as watch time, dwell time and repeat views, then adjust for recency, relationships and content type. Practitioners test formats and hooks, watch which posts earn early engagement, and publish more of what the system rewards. Most platforms publish some guidance on their ranking principles, which is a better starting point than third party folklore.
When it applies
It applies any time you distribute content on a feed based platform, including LinkedIn, Instagram, TikTok, Facebook, X, YouTube and Pinterest.
Examples
- A LinkedIn post gets strong early comments from a company's own team and is then shown to second degree connections, widening reach well beyond followers.
- A short video with high average watch time is pushed into TikTok's For You feed and reaches an audience that does not follow the account.
- An Instagram carousel earns a high save rate, and the account sees similar carousels distributed more widely over the following weeks.
How it is measured
- Reach split between followers and non followers
- Engagement rate by reach, broken down by saves, shares and comments
- Average watch time or percentage watched for video posts
- Impressions per post by format, to see which formats the system favours
Insights on Social media algorithm
Related terms in Algorithm
- Core updateA broad Google algorithm update affecting search rankings sitewide rather than a single feature. Recent core updates (e.g. May 2026) have increasingly favoured intent-aligned content over keyword-optimised content.
- EEATGoogle's quality framework: Experience, Expertise, Authoritativeness, Trustworthiness. EEAT signals are increasingly weighted in both classical ranking and AI Overview source selection.
- Entity salienceEntity salience is a measure of how central an entity is to a piece of content, as opposed to merely being mentioned in it. Natural language processing systems assign a salience score based on signals such as position, frequency, grammatical role and surrounding context. It helps a system decide what a document is actually about.
- Google Search algorithmThe Google Search algorithm is the collection of ranking and retrieval systems Google uses to find, order and present results for a query. It is not a single formula but many interacting systems that assess content, links, query intent, context and user signals. Google updates these systems continuously, with larger changes announced as core updates.
- Google Spam UpdateA Google Spam Update is a rollout of changes to the systems Google uses to detect and demote content that breaks its spam policies. These updates target things like scaled content abuse, cloaking, hacked pages, link schemes and site reputation abuse rather than general content quality. Sites hit by a spam update usually need to remove the offending practices before they can recover.
- Helpful Content UpdateGoogle's quality-focused update class targeting low-value, AI-generated, or thin content. Successive HCUs have favoured first-hand experience and named expertise over comprehensive but shallow coverage.
Primary research · August 2026
How ChatGPT Shortlists Software Brands
An audit across 10 categories and 60 buying questions. I recorded what ChatGPT reads, throws away and links to when a buyer asks it which software to buy, and what that decides.
- 60
- Questions asked
- 10
- Software markets
- 2,680
- Results read
- 367
- Links shown
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