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Researchers rely on academic web search engines to find scientific sources,but search engine mechanisms may selectively present content that aligns withbiases embedded in the queries. This study examines whether confirmation-biasedqueries prompted into Google Scholar and Semantic Scholar will yield skewedresults. 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 searchresults in line with the bias, with technology-related queries displaying moresignificant disparities. Overall, Semantic Scholar exhibited fewer disparitiesthan Google Scholar. Topics rated as more polarizing did not consistently showmore skewed results. Academic search results that perpetuate confirmation biashave strong implications for both researchers and citizens searching forevidence. More research is needed to explore how scientific inquiry andacademic search engines interact.

Examining bias perpetuation in academic search engines: an algorithm audit of Google and Semantic Scholar