Blame It on the Algorithm? Russian Government-Sponsored Media and Algorithmic Curation of Political Information on Facebook

Elizaveta Kuznetsova, Mykola Makhortykh


Previous research highlighted how algorithms on social media platforms can be abused to disseminate disinformation. However, less work has been devoted to understanding the interplay between Facebook news curation mechanisms and propaganda content. To address this gap, we analyze the activities of RT (formerly, Russia Today) on Facebook during the 2020 U.S. presidential election. We use agent-based algorithmic auditing and frame analysis to examine what content RT published on Facebook and how it was algorithmically curated in Facebook News Feeds and Search Results. We find that RT’s strategic framing included the promotion of anti-Biden leaning content, with an emphasis on antiestablishment narratives. However, due to algorithmic factors on Facebook, individual agents were exposed to eclectic RT content without an overarching narrative. Our findings contribute to the debate on computational propaganda by highlighting the ambiguous relationship between government-sponsored media and Facebook algorithmic curation, which may decrease the exposure of users to propaganda and at the same time increase confusion.



social media, framing, U.S. 2020 election, propaganda, news, algorithms

Full Text: