Register via Zoom: https://mit.zoom.us/meeting/register/tJMqc-mtpjwrHtbEk12_RH7uP9YHJQ5vfmQb

Presented by: Crystal Lee, PhD candidate at MIT, Fellow at Harvard University’s Berkman Klein Center

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 project investigates how pandemic visualizations circulated on social media by blending computational analysis of almost half a million tweets and 41k images with a digital ethnography of COVID skeptic communities. These communities often adopt the same rhetoric of data-driven decision-making used by experts, but to advocate for radically different—and often dangerous—policy changes. In this talk, I’ll walk through the implications of this project on how we should think about scientific expertise during a public health crisis, and I’ll conclude by reflecting on how to tie together qualitative and quantitative methodologies to study phenomena on social media.