Misinformation & Data Visualization in the Age of COVID-19
Data visualizations have become key to a robust public health response to COVID-19. Experts are using them to track metrics, and graphics like “Flatten the Curve” have proven critical for engaging the broader public. However, as hundreds of charts flood online media, there is a pressing need to study how they are being created, disseminated, and understood in order to mitigate public confusion and the spread of misinformation.
Using an approach that combines quantitative methods (e.g., scraping social media, clustering visualization designs, etc.) as well as qualitative ones (e.g., digital ethnography) we will study the flow of data visualizations in social media to understand what role they play in shaping the discourse around COVID-19. What made “Flatten the Curve” so effective at galvanizing the public? And, how are charts being reappropriated (e.g., #Masks4All annotations on charts from the Financial Times, or through memeifcation)?
Research areas: Human-Computer Interaction, Data Visualization, Misinformation, Social Media, Computational Social Science