The Gag City Grammar Police: Language and Algorithmic Community on Stan Twitter

Abstract

While there is a wealth of sociolinguistic research on subculture and a rapidly growing field of digital ethnography, little research has been conducted on subcultural language use online. Superfan groups, or stans, form speech communities on Twitter/X and present as a closed group despite remaining public. Through digital ethnographic observation of nonstandard English use on Twitter, I argue that Barbz--Nicki Minaj stans––discourage their posts from spreading to the general public. Working with the algorithm’s composition of social media feeds, Barbz use language to conceal themselves while remaining discoverable. Individuals use language variation and encoding to interact directly with the algorithm, strategically hiding their conversations from the public. By way of sociolinguistic theories including variance and enregisterment, I situate this study in relation to fandom studies, cultural capital, and structural theories of internet. This netnography takes a multimodal approach to social media, showing that Barbz strategically open their community at specific times and in specific ways that are advantageous to them. On Twitter, Barbz employ language to manipulate the borders of both their community and their audience. In order to understand group maintenance, formation, and relationality online it is vital to account for the role of the algorithm as companion rather than structural affordance.