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A comparison of online search engine autocompletion in Google and Baidu

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arxiv 2405.01917 v1 pith:G4FIXVEN submitted 2024-05-03 cs.CY

classification cs.CY
keywords searchauto-completionsbaiduenginegooglegroupsnegativeonline
verification ladder T0 review T1 audit T2 compute T3 formal
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Warning: This paper contains content that may be offensive or upsetting. Online search engine auto-completions make it faster for users to search and access information. However, they also have the potential to reinforce and promote stereotypes and negative opinions about a variety of social groups. We study the characteristics of search auto-completions in two different linguistic and cultural contexts: Baidu and Google. We find differences between the two search engines in the way they suppress or modify original queries, and we highlight a concerning presence of negative suggestions across all social groups. Our study highlights the need for more refined, culturally sensitive moderation strategies in current language technologies.

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Cited by 1 Pith paper

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  1. Auditing LLM Editorial Bias in News Media Exposure

    cs.CY 2025-10 conditional novelty 6.0 of 10

    Compared with Google News, GPT-4o-Mini, Claude-3.7-Sonnet, and Gemini-2.0-Flash surface fewer unique news outlets, distribute attention more unevenly, and lean ideologically in system-specific ways.

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