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.

中文翻译：

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COVID-19 模因病毒式传播：关于口罩背后的多种多模态声音

推进多模态发声的概念作为描述用户生成的在线幽默的工具，本文报告了一项关于幽默 COVID-19 面具模因的研究。该语料库来自四个流行的社交媒体平台，并通过多模态话语分析镜头进行检查。主要的模因趋势被阐明并显示出以编程方式依赖嵌套（多模态）声音，无论是兼容的还是发散的，就像戴着特殊面具的个体的分离回声或他们集体声音的分离模仿回声一样。该分析的理论主旨是，由于一些模因在社交媒体上（重新）发布（有时会传播开来），先前的声音——模因主题/作者/海报——可以被重新利用（例如嘲笑) 或无意中被扭曲。全面的，这项调查为模因研究提供了新的理论和方法论意义：它表明了多模态发声、互文性和回声等概念作为研究工具的有用性；它揭示了对模因的外行和学术理解中认识论上的模糊性，其背后的声音并不总是绝对已知的。