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In the buildup to and in the weeks following the Russian Federation'sinvasion of Ukraine, Russian state media outlets output torrents of misleadingand outright false information. In this work, we study this coordinatedinformation campaign in order to understand the most prominent state medianarratives touted by the Russian government to English-speaking audiences. Todo this, we first perform sentence-level topic analysis using thelarge-language model MPNet on articles published by ten different pro-Russianpropaganda websites including the new Russian "fact-checking" websitewaronfakes.com. Within this ecosystem, we show that smaller websites likekatehon.com were highly effective at publishing topics that were later echoedby other Russian sites. After analyzing this set of Russian informationnarratives, we then analyze their correspondence with narratives and topics ofdiscussion on the r/Russia and 10 other political subreddits. Using MPNet and asemantic search algorithm, we map these subreddits' comments to the set oftopics extracted from our set of Russian websites, finding that 39.6% ofr/Russia comments corresponded to narratives from pro-Russian propagandawebsites compared to 8.86% on r/politics.

Happenstance: Utilizing Semantic Search to Track Russian State Media Narratives about the Russo-Ukrainian War On Reddit