Understanding search autocompletes from the perspectives of English and Spanish speakers during the early months of the COVID-19 pandemic

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.