Dr. Nir Greenberg

Purpose: Accurate information is the basis for well-informed decision-making, which is particularly challenging in the dynamic reality of a pandemic. Search engines are a major gateway for obtaining information, yet little is known about the quality and scientific accuracy of information answering conspiracy-related queries about COVID-19, especially outside of English-speaking countries and languages. Design/methodology/approach: The authors conducted an algorithmic audit of Google Search, emulating search queries about COVID-19 conspiracy theories in 10 different locations and four languages (English, Arabic, Russian, and Hebrew) and used content analysis by native language speakers to examine the quality of the available information. Findings: Searching the same conspiracies in different languages led to fundamentally different results. English had the largest share of 52% high-quality scientific information. The average quality score of the English-language results was significantly higher than in Russian and Arabic. Non-English languages had a considerably higher percentage of conspiracy-supporting content. In Russian, nearly 40% of the results supported conspiracies compared to 18% in English. Originality/value: This study’s findings highlight structural differences that significantly limit access to high-quality, balanced, and accurate information about the pandemic, despite its existence on the Internet in another language. Addressing these gaps has the potential to improve individual decision-making collective outcomes for non-English societies.