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Citation behavior in LLM answer engines
An empirical study of which sources answer engines cite, and why.
The paper measures citation frequency across engines and finds strong biases toward well-structured, dated, and named content.
What the study found
Structured pages with named authors and explicit dates were cited multiple times more often than unstructured equivalents, even at similar ranking positions.
Content-farm patterns — unnamed authors, undated pages, boilerplate paragraphs — were systematically underrepresented in citations.