Nyetwork News: The Convergence of the Russophobia Narrative in Russian Propaganda and Fox News in Election 2020

Abstract

This study demonstrates how the key ‘Russophobia’ narrative was woven both through Russian propaganda and Fox News coverage of the U.S. 2020 elections. As part of a larger study on how Russian propaganda narratives dovetail with rightwing media coverage in the U.S., this analysis uses human content analysis and machine learning to identify and track how a narrative that claimed criticism of Russia is based on Democratic paranoia was deployed on RT and Sputnik and echoed on Fox News. The study has three main goals. First, it presents the theory of ‘Nyetwork News,’ that former U.S. President Donald Trump and some American news outlets relied more on classic Russian techniques of propaganda than traditional U.S. news values. In addition, this paper identifies key elements of the Russophobia narrative, which is broader than any single frame or set of stories. Finally, this paper suggests two different methodological approaches to detecting Russian content in U.S. news. It demonstrates a way of combining human content analysis and machine learning to tag and trace news narratives on the MarvelousAI Story Arc system. We also use the open-source software tool Steno to detect the presence of Russian propaganda text in a broad sweep of U.S. media, with initial findings of a close relationship between Russian propaganda and the right-wing outlet Infowars.

Keywords: Russophobia, U.S. 2020 Elections, Russia, Trump, campaign narratives, machine learning, automated content analysis, Fox News, RT, Sputnik, InfoWars