Algorithmic Curation of Russian Propaganda: A Comparative Analysis of Online Information Environments

Russian propaganda influence on global public discourse has been a major concern for democratic societies since the 2016 US Election (Mueller, 2019). The intensity of Kremlin’s digital deception campaigns has amplified following the Russian full-scale invasion of Ukraine (Litvinenko, 2022). Despite burgeoning literature on Russian digital propaganda, we still lack a comprehensive account on how online platforms manage problematic content produced by Kremlin and how their algorithms shape information environments where publics are exposed to propaganda-related topics. To remedy this limitation, our paper focuses on how platform algorithms counter or sometimes facilitate the spread of various dimensions of Russian propaganda, such as anti-system claims about failing Western democracies, conservative values, and conspiratorial content. Particularly, we focus on search engines and their role in algorithmic information curation - understood as a process of "organizing, selecting and presenting subsets of a corpus of information" to users (Rader & Gray, 2015) - of propaganda-related content. To systematically investigate algorithmic curation of Russian propaganda, we perform an agent-based comparative algorithmic audit of a selection of the world’s most used search engines: Google, Bing, Yandex, and DuckDuckGo. Earlier research (e.g. Toepfl et al., 2023) has already been looking at how search engines interact with Russian propaganda, albeit it has so far focused primarily on the Russian domestic information environment and the neighboring countries and studied a small sample of propaganda-related topics. By contrast, we use Google Compute Cloud to simulate user browsing activity in 6 countries (USA, India, Qatar, Brazil, Poland, Germany) and use a structured corpus of Russian propaganda statements based on dimensionality analysis translated into 9 languages (English, Spanish, Portuguese, German, Hindi, Polish, Arabic, Russian, and Ukrainian). Using 144 queries, we investigate what sources different search engines return in response to queries, whether these sources support or debunk common propaganda narratives, and how the outputs vary depending on the location and the language of the query. Our preliminary observations highlight more impact of the language on search engines’ outputs. Particularly, we notice a still concerning amount of Russian state-controlled sources suggested. This is problematic due to search algorithms potentially amplifying information inequality and points to the importance of a comprehensive understanding of information environments surrounding critical political topics and the role of algorithmic systems in shaping these environments.