Communications of the ACM
Science Denial, Partisanship on Social Media Indicate Where COVID-19 Strikes Next
Considering the emergence of new COVID-19 infection clusters based on the location of anti-science tweeters.
Credit: iStock
A machine learning-assisted social media analysis by researchers at the University of Southern California could help predict where COVID-19 will emerge based on anti-science views and political ideology.
USC's Kristina Lerman said the study determined entirely from social media data that "anti-science views are aligned with political ideology, specifically conservatism."
Using 27 million Twitter tweets posted by 2.4 million U.S. users from Jan. 21 to May 1, 2020, the researchers compared public discourse on COVID-19 with epidemiological outcomes.
They found that anti-science attitudes were high from January through April 2020 in Mountain West and Southern states that experienced COVID-19 surges.
Lerman said, "Now we can use social media data for science, to create spatial and temporal maps of public opinions along ideological lines, pro- and anti-science lines."
From University of Southern California
View Full Article
Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA
No entries found