The life of COVID-19 mask memes: A diachronic study of the pandemic memescape

 Marta Dynel, Vilnius (Lithuania)

https://doi.org/10.3916/C72-2022-06

Keywords

COVID-19 mask, diachronic corpus, meme, memetic construct, humour, viral

Abstract

Taking as its point of departure a fine-tuned definition of an Internet meme (vis-à-vis a memetic construct), this paper reports the findings of the first diachronic study of memes, the focus being on mask memes on the vast COVID-19 mask memescape evolving in the wake of the pandemic, relative to the changing socio-political situation. The study capitalises on a diachronic corpus of user-tagged COVID-19 mask memes (posted online from January 2020 to January 2021) collected from Google through a Python script. Based on a grounded-theory approach, ten memetic categories (clustered into four groups) are extracted and examined through a multimodal discourse analytic lens. The diachronic quantitative analysis shows that the memetic constructs, inspired by the current socio-political situation/events and facilitated by the socio-political context (e.g. going into lockdown), seem to persist, albeit with varied intensity, for the best part of the year, with many individual memes going viral. Memes’ and memetic constructs’ long lifespan is indicative of users’ primary goal, which is to share interesting and/or humorous (not always newly minted or relevant) items for the sake of fun, regardless of the memes’ nature (i.e. autotelic humour for its own sake or users’ commentaries on the surrounding reality).

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Fundref

The National Science Centre, Poland (Project 2018/30/E/HS2/00644, Marta Dynel, University of Łódź). The author would like to thank Gosia Krawentek for her assistance.

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Technical information

Received: 18-11-2021

Revised: 03-01-2022

Accepted: 02-03-2022

OnlineFirst: 15-05-2022

Publication date: 01-07-2022

Article revision time: 46 days | Average time revision issue 72: 31 days

Article acceptance time: 104 days | Average time of acceptance issue 72: 75 days

Preprint editing time: 180 days | Average editing time preprint issue 72: 151 days

Article editing time: 225 days | Average editing time issue 72: 196 days

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