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Research on digital misinformation has turned its attention to large language models (LLMs) and their handling of sensitive political topics. Through an AI audit, we analyze how three LLM-powered chatbots (Perplexity, Google Bard, and Bing Chat) generate content in response to the prompts linked to common Russian disinformation narratives about the war in Ukraine.

The Kremlin’s use of bots and trolls to manipulate the recommendation algorithms of social media platforms is well-documented by many journalists and researchers. However pro-Kremlin manipulation of search engine algorithms has rarely been explored. We examine pro-Kremlin attempts to manipulate search engine results by comparing backlink and keyphrase networks of US, European, and Russian think tanks, as well as Kremlin-linked “pseudo” think tanks that target Western audiences.

Following Russia’s invasion of Ukraine, policymakers worldwide have taken measures to curb the reach of Russia’s foreign communication outlets, RT and Sputnik. Mapping the audiences of these outlets in 21 countries, we show that in the quarter before the invasion, at least via their official websites and mobile apps, neither outlet reached more than 5% of the digital populations of any of these countries each month.

This paper examines how Russia tailors its vaccine propaganda to hostile and friendly audiences, like Ukraine and Serbia. Web scraping of all articles about vaccines on Russian state-owned websites from December 2020 to November 2021 provided data for quantitative topic modeling and qualitative analysis.

On 3 September 2021, the Russian court forbade Google and Yandex to display search results for “Smart Voting,” the query referring to a tactical voting project by the jailed Russian opposition leader Alexei Navalny. To examine whether the two search engines complied with the court order, we collected top search outputs for the query from Google and Yandex.

Social media companies have begun to use content-based alerts in their efforts to combat mis- and disinformation, including fact-check corrections and warnings of possible falsity, such as “This claim about election fraud is disputed.” Another harm reduction tool, source alerts, can be effective when a hidden foreign hand is known or suspected.

Platforms are increasingly using transparency, whether it be in the form of political advertising disclosures or a record of page name changes, to combat disinformation campaigns. In the case of state-controlled media outlets on YouTube, Facebook, and Twitter this has taken the form of labeling their connection to a state.

We analyzed the Russian Internet Research Agency’s (IRA) 2015–2017 English-language information operation on Twitter to understand the special role that engagement with outsiders (i.e., non-IRA affiliated accounts) played in their campaign. By analyzing the timing and type of engagement of IRA accounts with non-IRA affiliated accounts, and the characteristics of the latter, we identified a three-phases life cycle of such engagement, which was central to how this IRA network operated.

Evidence from an analysis of Twitter data reveals that Russian social media trolls exploited racial and political identities to infiltrate distinct groups of authentic users, playing on their group identities. The groups affected spanned the ideological spectrum, suggesting the importance of coordinated counter-responses from diverse coalitions of users.