1. Understanding search autocompletes from the perspectives of English and Spanish speakers during the early months of the COVID‐19 pandemic.
- Author
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Valera, Pamela, Carmona, David, Singh, Vivek, Malarkey, Sarah, Baquerizo, Humberto, and Smith, Nadia
- Subjects
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COVID-19 pandemic , *ALASKA Natives , *COVID-19 , *ALGORITHMIC bias , *STAY-at-home orders , *GROUPOIDS - Abstract
The purpose of the study was to explore differences in Google search autocompletes between English and Spanish‐speaking users during the first wave of the coronavirus disease 2019 (COVID‐19) pandemic. Twenty‐nine individuals who were in areas with shelter‐in‐place state orders participated in a virtual focus group meeting to understand the algorithm bias of COVID‐19 Google autocompletes. The three focus group meetings lasted for 90–120 minutes. A codebook was created and transcripts were coded using NVivo qualitative software with a 95% intercoder reliability between two coders. Thematic analysis was used to analyze the data. Among the 29 participants, six self‐identified as White, seven as Black/African American, five as American Indian or Alaska Native, four as Asian Indian, and three as Native Hawaiian or Pacific Islander. In terms of ethnicity, 21 participants identified as Hispanic/Latino. The themes that emerged from the study were: (1) autocompletes evoked fear and stress; (2) skepticism and hesitation towards autocomplete search; (3) familiarity with COVID‐19 information impacts outlook on autocomplete search; (4) autocompletes can promote preselection of searches; and (5) lesser choice of autocomplete results for Spanish‐speaking searchers. Spanish speakers expressed concerns and hesitation due to social factors and lack of information about COVID‐19. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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