AI Search Citation Network

An AI search citation network is the set of domains, publishers, retailers, social platforms, and brand-owned sites that a generative search engine repeatedly cites for a topic, vertical, language, or query class.

Key points

• The GEO paper measures cited domains across engines and finds that different AI systems often consult substantially different domain sets for the same intent ^[src-028].
• In automotive and consumer-electronics experiments, each engine contributed many exclusive domains, while only a small core of high-authority review and media sites appeared across all engines ^[src-028].
• Local service queries were especially fragmented: Claude and GPT used narrower source sets, while Gemini and Perplexity surfaced broader domain pools with limited consensus ^[src-028].
• The paper’s proposed GEO operating model starts with continuous engine-specific competitive intelligence: mapping which sources each AI engine privileges for target queries ^[src-028].
• Citation-network monitoring links strategy to execution: identify target earned-media sources, build content for the evidence base, and track whether visibility shifts across engines over time ^[src-028].

Related entities

• OpenAI
• Anthropic
• Gemini
• Perplexity API

Related concepts

• Generative Engine Optimization
• AI Search
• Earned Media Bias in AI Search
• Machine-Scannable Content
• AI Search Language Sensitivity
• AI Search Paraphrase Sensitivity
• Big Brand Bias in AI Search

Source references

• ^[src-028] Mahe Chen, Xiaoxuan Wang, Kaiwen Chen, Nick Koudas — “Generative Engine Optimization: How to Dominate AI Search” (2025-09-10)