COVID-19 memes going viral: On the multiple multimodal voices behind face masks

Abstract

Advancing the concept of multimodal voicing as a tool for describing user-generated online humour, this paper reports a study on humorous COVID-19 mask memes. The corpus is drawn from four popular social media platforms and examined through a multimodal discourse analytic lens. The dominant memetic trends are elucidated and shown to rely programmatically on nested (multimodal) voices, whether compatible or divergent, as is the case with the dissociative echoing of individuals wearing peculiar masks or the dissociative parodic echoing of their collective voice. The theoretical thrust of this analysis is that, as some memes are (re)posted across social media (sometimes going viral), the previous voice(s) – of the meme subject/author/poster – can be re-purposed (e.g. ridiculed) or unwittingly distorted. Overall, this investigation offers new theoretical and methodological implications for the study of memes: it indicates the usefulness of the notions of multimodal voicing, intertextuality and echoing as research apparatus; and it brings to light the epistemological ambiguity in lay and academic understandings of memes, the voices behind which cannot always be categorically known.