Controversial understandings of the coronavirus pandemic have turned data visualizations into a battleground. Defying public health ofcials, coronavirus skeptics on US social media spent much of 2020 creating data visualizations showing that the government's pandemic response was excessive and that the crisis was over. This paper investigates how pandemic visualizations circulated on social media, and shows that people who mistrust the scientifc estab-lishment often deploy the same rhetorics of data-driven decision-making used by experts, but to advocate for radical policy changes. Using a quantitative analysis of how visualizations spread on Twit-ter and an ethnographic approach to analyzing conversations about COVID data on Facebook, we document an epistemological gap that leads pro-and anti-mask groups to draw drastically diferent inferences from similar data. Ultimately, we argue that the deploy-ment of COVID data visualizations refect a deeper sociopolitical rift regarding the place of science in public life.
Lee, C., Yang, T., Inchoco, G., Jones, G. M., & Satyanarayan, A. (2021). Viral visualizations: How coronavirus skeptics use orthodox data practices to promote unorthodox science online. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3411764.3445211