On the Vernacular Language Games of an Antagonistic Online Subculture

Open Access
Authors
Publication date 08-2021
Journal Frontiers in Big Data
Article number 718368
Volume | Issue number 4
Number of pages 15
Organisations
  • Faculty of Humanities (FGw) - Amsterdam Institute for Humanities Research (AIHR) - Amsterdam School for Cultural Analysis (ASCA)
  • Faculty of Humanities (FGw) - Amsterdam Institute for Humanities Research (AIHR)
Abstract
In this paper we develop an empirical, big data approach to analyze how alt-right vernacular concepts (such as kek and beta) were used on the notorious anonymous and ephemeral imageboard 4chan/pol/and the fan wiki Encyclopedia Dramatica. While 4chan/pol/is broadly regarded as an influential source of many of the web’s most successful memes such as Pepe the Frog, Encyclopedia Dramatica functions as a kind of satirical Wikipedia for this meme subculture, written in high concept and highly offensive vernacular style. While the site’s affordances make them distinct, they are connected by a subcultural style and politics that has recently become increasingly connected with violent right-wing activism, forming a loose subcultural language community. Contrary to “memetic” theories of cultural evolution in media studies, our analysis draws on theoretical frameworks from poststructuralist and pragmatist philosophies of language and deploys empirical techniques from corpus linguistics to consider the role of online platforms in shaping these vernacular modes of expression. This approach helps us to identify instances of vernacular innovation within these corpora from 2012-2020—a period during which the white supremacist “alt-right” movement arose online. Through these analyses we contribute both to ongoing interdisciplinary attempts to bridge the gap between cultural-theoretical and computational-linguistic approaches to studying online subcultures, and to the empirical study of the vernacular roots of the “toxic memes” that appear to be an increasingly common feature on social media.
Document type Article
Note Dataset
Language English
Published at https://doi.org/10.3389/fdata.2021.718368
Other links https://zenodo.org/record/4792071#.Ybcg3vmZNPY
Downloads
fdata-04-718368 (Final published version)
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