arvix | Controversial understandings of the coronavirus pandemic have turned data visualizations into a battleground. Defying public health officials, 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 scientific establishment 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 Twitter 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 different inferences from similar data. Ultimately, we argue that the deployment of COVID data visualizations reflect a deeper sociopolitical rift regarding the place of science in public life.
This paper has investigated anti-mask counter-visualizations on social media in two ways: quantitatively, we identify the main types of visualizations that are present within different networks (e.g., pro-and anti-mask users), and we show that anti-mask users are prolific and skilled purveyors of data visualizations. These visualizations are popular, use orthodox visualization methods, and are promulgated as a way to convince others that public health measures are unnecessary. In our qualitative analysis, we use an ethnographic approach to illustrate how COVID counter-visualizations actually reflect a deeper epistemological rift about the role of data in public life, and that the practice of making counter-visualizations reflects a participatory, heterodox approach to information sharing. Convincing anti-maskers to support public health measures in the age ofCOVID-19 will require more than “better” visualizations, data literacy campaigns, or increased public access to data. Rather, it requiresa sustained engagement with the social world of visualizations andthe people who make or interpret them.While academic science is traditionally a system for producing knowledge within a laboratory, validating it through peer review,and sharing results within subsidiary communities, anti-maskers reject this hierarchical social model. They espouse a vision of science that is radically egalitarian and individualist. This study forces us to see that coronavirus skeptics champion science as a personal practice that prizes rationality and autonomy; for them, it is not a body of knowledge certified by an institution of experts. Calls for data or scientific literacy therefore risk recapitulating narratives that anti-mask views are the product of individual ignorance rather than coordinated information campaigns that rely heavily on networked participation.
Recognizing the systemic dynamics that contribute to this epistemological rift is the first step towards grappling with this phenomenon, and the findings presented in this paper corroborate similar studies about the impact of fake news on American evangelical voters [98] and about the limitations of fact-checking climate change denialism [42].Calls for media literacy—especially as an ethics smokescreen to avoid talking about larger structural problems like white supremacy—are problematic when these approaches are deficit-focused and trained primarily on individual responsibility. Powerful research and media organizations paid for by the tobacco or fossil fuel indus-tries [79,86] have historically capitalized on the skeptical impulse that the “science simply isn’t settled,” prompting people to simply“think for themselves” to horrifying ends. The attempted coup on January 6, 2021 has similarly illustrated that well-calibrated, well-funded systems of coordinated disinformation can be particularly dangerous when they are designed to appeal to skeptical people.While individual insurrectionists are no doubt to blame for their own acts of violence, the coup relied on a collective effort fanned by people questioning, interacting, and sharing these ideas with other people. These skeptical narratives are powerful because they resonate with these these people’s lived experience and—crucially—because they are posted by influential accounts across influential platforms.Broadly, the findings presented in this paper also challenge conventional assumptions in human-computer interaction research about who imagined users might be: visualization experts tradition-ally design systems for scientists, business analysts, or journalists.
Researchers create systems intended to democratize processes of data analysis and inform a broader public about how to use data,often in the clean, sand-boxed environment of an academic lab.However, this literature often focuses narrowly on promoting expressivity (either of current or new visualization techniques), assuming that improving visualization tools will lead to improving public understanding of data. This paper presents a community of users that researchers might not consider in the systems building process (i.e., supposedly “data illiterate” anti-maskers), and we show how the binary opposition of literacy/illiteracy is insufficient for describing how orthodox visualizations can be used to promote unorthodox science. Understanding how these groups skillfully manipulate data to undermine mainstream science requires us to adjust the theoretical assumptions in HCI research about how data can be leveraged in public discourse.What, then, are visualization researchers and social scientists todo? One step might be to grapple with the social and political dimensions of visualizations at the beginning, rather than the end, of projects [31]. This involves in part a shift from positivist to interpretivist frameworks in visualization research, where we recognize that knowledge we produce in visualization systems is fundamentally“multiple, subjective, and socially constructed” [73]. A secondary issue is one of uncertainty: Jessica Hullman and Zeynep Tufekc
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