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Research that audited search algorithms typically deployed queries in one language fielded from within only one country. In contrast, this study scrutinized 8,800 Google results retrieved in November 2020 from 5 countries (Russia, the United States, Germany, Ukraine, and Belarus) in response to queries on COVID-19 conspiracy theories in Russian and English. We found that the pandemic appeared similar to people who googled in Russian independent of their geolocation. The only exception was Ukraine, which had implemented rigorous media policies to limit the reach of websites affiliated with Russia within its national public sphere. Conspiracy narratives varied with input language. In response to Russian-language queries, 35.5% of the conspiratorial results suspected U.S. plotters to be behind the pandemic (English language: 5.8%). All source pages that blamed U.S. plotters showed connections with Russia’s elites. These findings raise important theoretical questions for today’s multilingual societies, where the practice of searching in nonlocal languages is increasing.
https://ijoc.org/index.php/ijoc/article/view/19423/4042
search engines, Google, Russia, conspiracy theory, disinformation, COVID-19, algorithms
search engines, Google, Russia, conspiracy theory, disinformation, COVID-19, algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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