COVID-19 Analysis: A Twitter-based Social Distancing Measure

• Activity Number: 558 - Data and Algorithmic Biases: Systematic Harms and Potential Solutions
• Type: Invited
• Date/Time: Thursday, August 6, 2020 : 3:00 PM to 4:50 PM
• Sponsor: IMS
• Author(s): Samah Jarad*
• Companies: Yale

Abstract

Social distancing has been one of the primary mitigation strategies in the United States to control the spread of novel coronavirus disease (COVID-19) and can be viewed as a multi-faceted public health measure. Using Twitter data, we aim to (1) define and quantify the prevalence and evolution of facets of social distancing during the COVID-19 pandemic in the US in a spatiotemporal context and (2) examine the most amplified tweets among social distancing facets. This talk will present this urgent and timely work, and is based on a paper and dashboard developed in collaboration Jiye Kwon, Connor Grady, and Josemari T. Feliciano and available here: https://samahfodehlab.github.io/