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CSCW2022顶会

"Self-Quaranteens" Process COVID-19: Understanding Information Visualization Language in Memes

Laura J. Perovich, Meryl Alper, Corey Cleveland

2022年份
5被引次数
2顶会引用

摘要

The COVID-19 pandemic has led to a surge of information visualizations that aim to increase our scientific understanding and communicate about the ongoing health crisis with the general public. In this time, there has also been significant use of data visualization language in artefacts from online communities that provide commentary on the pandemic and create meaning through participatory digital culture. Using a qualitative approach, this paper examines over 300 memes collected from a public social media group targeted to young adults in the United States that uses the language of data visualization to discuss topics related to COVID-19. We outline four main ways that data visualization language is used in these memes-as a coarse indicator, as a visual analogy, as an opportunity for augmentation with emotion or interpretation, and as a visual pun-as well as two ways that memes leverage traditional and emerging approaches in the information visualization community. We describe the context in which these memes are socially created and interpreted in light of the political nature of online spaces and connect this work to ongoing research on participation, emotion, and embodiment in information visualization. These results aim to start a conversation about the use of data visualization language in digital culture and more casual networked environments beyond official channels.

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