Understanding Generative AI-mediated User Engagement with Academic Library Resources
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Abstract (arXiv)
This study empirically analyzed generative AI as an emerging discovery pathway to academic library resources. Utilizing web analytics from August 2023 to October 2025, the research identifies a significant increase in AI-mediated traffic, particularly following the integration of linked citation features. Referral analysis identified ChatGPT, Perplexity, and Gemini as the primary platforms driving this traffic. A substantial portion of users reached the institutional repository, primarily accessing electronic theses and dissertations. This pattern suggests that AI retrieval mechanisms effectively surface resources with structured metadata and stable permalinks that are Open Access and freely available. The results illustrate how AI ecosystems currently expose library resources and underscore the need for continued analysis and a strategic response to the evolving AI landscape.
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References · 7
- 2024Generative AI Search Engines as Arbiters of Public Knowledge: An Audit of Bias and Authoritycited by 13
- 2024Grounding from an AI and Cognitive Science Lenscited by 6
- 2024Meta Knowledge for Retrieval Augmented Large Language Modelscited by 6
- 2025Attribution Gradients: Incrementally Unfolding Citations for Critical Examination of Attributed AI Answerscited by 3
- 2023What has ChatGPT read? The origins of archaeological citations used by a generative artificial intelligence applicationcited by 2
- 2025A RAG-Based Institutional Assistantcited by 2
- 2025When Content is Goliath and Algorithm is David: The Style and Semantic Effects of Generative Search Enginecited by 2
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