How Generative AI Reshapes Academic Library Resource Discovery: An Empirical Study Based on Three-Year Web Analytics
Score
79首次利用长期网络分析数据量化AI对图书馆资源发现的具体影响，填补了该领域的实证空白。
研究方法规范，样本跨度两余年，但分析深度可进一步扩展至不同类型的图书馆和资源。
对图书馆管理者、AI平台运营者及开放获取推动者具有直接策略指导意义。
数据截至2025年10月，研究问题紧贴当前AI应用与学术传播的快速变化。
论文来源于arXiv预印本，虽未正式发表但数据源自实际网站分析，可信度较高。
Base 88 × T2 Source weight ×0.9 = 79
Curation line 70Selected
Why selected
The paper leverages two years of real-world web analytics data on the cutting-edge topic of AI-mediated resource discovery, with rigorous empirical methodology and conclusions of direct relevance to the industry.
AI commentary
「This paper offers a rare empirical window into how AI platforms are actually reshaping the flow of academic information. For library directors and digital resource managers, the data signals an urgent need to refine metadata strategies and Open Access policies in the age of AI. For AI developers, the observed user behavior patterns provide concrete inputs for improving retrieval ranking and citation features. A must-read for anyone concerned with scholarly communication.」
Quick overview
This study empirically analyzes the impact of generative AI as an emerging discovery pathway for academic library resources using web analytics data from August 2023 to October 2025. Results show a significant increase in AI-mediated traffic, especially after integrating linked citation features. ChatGPT, Perplexity, and Gemini are the primary platforms driving traffic, with a substantial portion of users accessing the institutional repository for electronic theses and dissertations. The findings indicate that AI retrieval mechanisms effectively surface resources with structured metadata and stable permalinks that are Open Access, offering strategic insights for libraries in the evolving AI landscape.
- AI-mediated traffic to academic library resources increased significantly from 2023 to 2025, especially after the deployment of linked citation features.
- ChatGPT, Perplexity, and Gemini are the three primary AI platforms driving traffic to institutional repositories.
- AI retrieval excels at surfacing resources with structured metadata and stable permalinks, particularly Open Access electronic theses and dissertations.
- The study provides an evidence-based foundation for libraries to develop strategic responses to the evolving AI ecosystem.
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