Nearing the Far(right)
Author: Jaclyn R. Fox
Publisher:
Published: 2023
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKOn January 6, 2021, images of Capitol insurrectionists flooded the newsfeed. From the shirtless "QAnon Shaman" in a Viking hat and face paint, to fully kitted out militia members and suburban moms in MAGA gear, law enforcement and news media quickly worked to understand just who these individuals - so bent on overturning the election - actually were. This dissertation explores this key puzzle of who and what comprises the burgeoning modern-day far-right. Through three articles I use open-source social media data to analyze the modern-day far-right (2011-2023) vis-a-vis traditional ways of understanding the movement, including ideology, psychological motivation, and organizational structure. I engage in a variety of analytic methods: from machine learning and text-as-data analysis, to sentiment analysis, topic modelling, and content analysis. More specifically, the first article investigates the potential for using open-source social media data to explore extremism in the U.S. military. I use data from five relevant subreddits: r/army, r/navy, r/AirForce, r/USMC, and r/Military to understand this potential by service and in relation to specific "inflection points." In the second article, I examine the modern-day far-right's stance on gender politics and the rights and roles of women using the dual-process motivational model (Duckitt 2001). Specifically, I compare the prevalence of psychological motivations: social dominance orientation (SDO) and right-wing authoritarianism (RWA) across gender-relevant comments on the influential fascist forum, Iron March, from 2011-2017. In the third article I examine the evolution of anti-LGBTQ+ sentiment on Iron March. I also map the spread of the anti-LGBTQ+ groomer narrative between fringe (23 alternative platforms) and mainstream conversations. Overall, this dissertation argues that the modern-day far-right movement is expanding, incorporating hitherto mainstream individuals into a broad coalition based in hatred, conspiracy, and anti-government action. To stem the movement's growth and potential for destruction, it is essential to begin with a mapping of the modern-day far-right, using a combination of machine learning, text-as-data analysis, and content analysis. Through this analysis we can see the growth in violent elements of the far-right (e.g., preponderance of those motivated by SDO), as well as the mainstreaming of conspiracies through the online ecosystem.