Researchers rely on academic web search engines to find scientific sources, but search engine mechanisms may selectively present content that aligns with biases embedded in the queries. This study examines whether confirmation-biased queries prompted into Google Scholar and Semantic Scholar will yield skewed results. Six queries (topics across health and technology domains such as "vaccines" or "internet use") were analyzed for disparities in search results. We confirm that biased queries (targeting "benefits" or "risks") affect search results in line with the bias, with technology-related queries displaying more significant disparities. Overall, Semantic Scholar exhibited fewer disparities than Google Scholar. Topics rated as more polarizing did not consistently show more skewed results. Academic search results that perpetuate confirmation bias have strong implications for both researchers and citizens searching for evidence. More research is needed to explore how scientific inquiry and academic search engines interact.

翻译：研究人员依赖学术网络搜索引擎查找科学资源，但搜索引擎机制可能选择性呈现与查询中隐含偏见相一致的內容。本研究考察了将确认偏误查询输入谷歌学术和Semantic Scholar后，是否会得到偏差结果。我们分析了六个查询（涵盖健康与技术领域，如"疫苗"或"互联网使用"）在搜索结果中的差异。研究证实，偏见性查询（针对"益处"或"风险"）会影响搜索结果，使其与偏见方向一致，其中技术相关查询表现出更显著的差异。总体而言，Semantic Scholar显示的差异少于谷歌学术。被评价为更具两极分化的主题并未始终呈现更多偏差结果。学术搜索结果中延续确认偏误的现象，对寻求证据的研究人员和公民均具有重要影响。未来需进一步探讨科研探索与学术搜索引擎之间的相互作用机制。