2024/05/03 by Geng Liu, Liu, Geng, Pietro Pinoli +5 · 1 citation
Computer Science · #Computers and Society (cs.CY) #FOS: Computer and information sciences #Web Data Mining and Analysis
paper · pdf · doi:10.48550/arxiv.2405.01917
openalex publication_date 2024/05/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.