Article Schema

What is Article Schema?

Article¹ is the schema.org JSON-LD type for editorial content — news pieces, blog posts, long-form essays, and informational guides. It captures the metadata that bare HTML doesn't: who wrote it, when it was published, when last modified, what publication it belongs to, and what topical scope it covers.

A typical Article payload includes:

• headline — the article title
• author — a Person object with name + URL
• datePublished and dateModified — ISO date strings
• publisher — an Organization object
• image — main image URL with dimensions
• mainEntityOfPage — the canonical URL of this article

Google's Article rich-result eligibility covers three schema.org types: Article itself, NewsArticle (journalistic content with a date hook), and BlogPosting (blog-format posts; BlogPosting inherits transitively from Article via SocialMediaPosting in schema.org, but Google treats it as a first-class Article subtype)². Other Article descendants like ScholarlyArticle and TechArticle exist in schema.org but aren't part of Google's Article rich-result eligibility set. Most editorial sites use Article as the safe default unless one of the supported subtypes is a stronger match.

Status in 2026

Foundational and broadly expected. Article schema is the baseline metadata layer for any publication that wants accurate authorship and freshness attribution in AI search results². The fields it exposes (datePublished, dateModified, author) feed Google's E-E-A-T inference and AI engines' citation-eligibility decisions. Pages without Article schema can still be indexed and cited, but they tend to lose attribution clarity — citations may credit the domain without naming the author, which hurts long-term authority building.

How to apply

Article schema is one of the cheapest schema additions to ship — most static-site frameworks and CMSes generate it automatically from frontmatter. Three concrete moves:

• Wire author to a real Person schema, not a freeform string: "author": "Jane Doe" is parseable, but "author": { "@type": "Person", "name": "Jane Doe", "url": "/about/jane-doe" } lets engines build an entity record. Engines tend to weight Person-typed authors over string authors for E-E-A-T inference.
• Bump dateModified only on legitimate updates: AI engines and Google both penalize date-spoofing on unchanged content and increasingly detect it via content-diff inspection. Update the date when you genuinely revise the content; keep it stable otherwise.
• Match headline to the visible <h1>: Article.headline should be the same string as the page's H1 element. Engines flag mismatches as content/markup discrepancy, which can suppress rich-result eligibility and reduce citation confidence.

What to skip: Article schema on glossary entries (use DefinedTerm), product pages (use Product), or pages that are really FAQs masquerading as articles. Wrong type signals worse than no type.

How it relates to other concepts

• Foundational metadata layer paired with FAQ schema and HowTo schema for content-heavy pages.
• Direct input to E-E-A-T authorship signals via the author property.
• Sibling to DefinedTerm schema — Article for editorial content, DefinedTerm for terminology entries; they coexist on glossary-with-blog sites.
• Foundational for GEO — Article metadata is what makes content cite-able as a discrete editorial piece rather than as a domain-level mention.