分析3大厂商AI搜索的新闻引用模式，发现存在明显偏见但用户不敏感。
News Source Citing Patterns in AI Search Systems
- 基于2.4万次对话数据，对比OpenAI、Perplexity、Google的引用行为。
- 9%引用新闻源，头部少数媒体占主导，呈现明显自由派倾向。
- 用户满意度不受引用新闻政治倾向或可信度影响，设计需警惕偏差。
AI驱动的搜索系统正成为新型信息守门人，深刻改变用户获取新闻与信息的方式。尽管其影响力日益增强，但这些系统的内容引用模式仍不清晰。本文通过分析AI Search Arena这一竞对评估平台的数据，涵盖来自OpenAI、Perplexity和Google三大厂商的超过24,000次对话及65,000条响应。在超过366,000个嵌入式引用中，有9%指向新闻来源。研究发现，不同厂商模型引用的新闻来源各异，但在引用行为上存在共性：新闻引用高度集中于少数媒体，且表现出显著的自由派倾向，但低可信度来源极少被引用。用户偏好分析表明，引用新闻的政治立场或质量均未显著影响用户满意度。这些发现揭示了当前AI搜索系统在信息呈现上的重大挑战，对系统设计与治理具有重要意义。
原文摘要 · Abstract (English)
AI-powered search systems are emerging as new information gatekeepers, fundamentally transforming how users access news and information. Despite their growing influence, the citation patterns of these systems remain poorly understood. We address this gap by analyzing data from the AI Search Arena, a head-to-head evaluation platform for AI search systems. The dataset comprises over 24,000 conversations and 65,000 responses from models across three major providers: OpenAI, Perplexity, and Google. Among the over 366,000 citations embedded in these responses, 9% reference news sources. We find that while models from different providers cite distinct news sources, they exhibit shared patterns in citation behavior. News citations concentrate heavily among a small number of outlets and display a pronounced liberal bias, though low-credibility sources are rarely cited. User preference analysis reveals that neither the political leaning nor the quality of cited news sources significantly influences user satisfaction. These findings reveal significant challenges in current AI search systems and have important implications for their design and governance.
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