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AI summaries in academic search show mixed results for social science research

By PulseAugur Editorial · [1 sources] ·

A new study published on arXiv explores the effectiveness of AI-generated summaries for academic search results in the social sciences. Researchers evaluated two general-purpose AI models, one commercial and one open-source, to develop an error taxonomy and safeguards for scholarly deployment. A user study with 30 participants indicated that while AI summaries did not significantly improve metrics like workload or satisfaction, they showed trends toward lower mental demand and frustration. Participants rarely expanded the summaries and made slightly fewer clicks and query reformulations, suggesting AI summaries might aid in early triage by concentrating information scent. AI

IMPACT AI summaries may aid in early triage of academic search results, but their effectiveness is context- and user-dependent.

RANK_REASON Academic paper detailing research findings on AI application in a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI summaries in academic search show mixed results for social science research

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Academic paper detailing research findings on AI application in a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Daniel Hienert ·

    AI Overviews in Academic Search: Evaluating AI-generated Summaries of Search Results in a Domain-specific Search Engine

    Evaluating search engine results pages (SERPs) to assess result relevance is a demanding step in academic search. In a formative mixed-methods design study, we examine AI-generated SERP-level summaries as a support feature in an academic search engine for social science informati…

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