By Libby Hemphill
Social media platforms provide fertile ground for white supremacist networks, enabling farright extremists to find one another, recruit and radicalize new members, and normalize their hate. Platforms such as Facebook and Twitter use content matching and machine learning to recognize and remove prohibited speech, but to do so, they must be able to recognize white supremacist speech and agree that it should be prohibited. Critics in the press1 and advocacy organizations still argue that social media companies haven’t been aggressive or broad enough in removing prohibited content. There is little public conversation, however, about what white supremacist speech looks like and whether white supremacists adapt or moderate their speech to avoid detection. Our team of researchers set out to better understand what constitutes English-language white supremacist speech online and how it differs from general or non-extremist speech. We also sought to determine whether and how white supremacists adapt their speech to avoid detection. We used computational methods to analyze existing sets of known white supremacist speech (text only) and compared those speech patterns to general or non-extremist samples of online speech. Prior work confirms that extremists use social media to connect and radicalize, and they use specific linguistic markers to signal their group membership. We sampled data from users of the white nationalist website Stormfront and a network of “alt-right” users on Twitter. Then, we compared their posts to typical, non-extremist Reddit comments.* We found that platforms often miss discussions of conspiracy theories about white genocide and Jewish power and malicious grievances against Jews and people of color. Platforms also let decorous but defamatory speech persist. With all their resources, platforms could do better. With all their power and influence, platforms should do better.
New York: ADL, 2022. 66p.
