Twitter on a mobile phone. Photo credit: Solen Feyissa, via Wikimedia Commons

Political discourse on Twitter helps to predict where future COVID-19 outbreaks are likely to occur, according to a study by university researchers.

The tool, they argue, could help health officials proactively respond to prevent or lessen the severity of an outbreak.

“We show that anti-science views are aligned with political ideology, specifically conservatism,” said Kristina Lerman, the study’s lead author and a USC professor. “While that’s not necessarily brand new, we discovered this entirely from social media data that gives detailed clues about where COVID-19 is likely to spread so we can take preventive measures.”

Researchers said they found that “anti-science” attitudes posted between January and April 2020 were high in some Mountain West and Southern states that were later hit with deadly surges of the virus.

The study’s findings can help policymakers and public health officials by allowing them to tailor messages to mitigate distrust of science and prepare for a potential outbreak if they see anti-science sentiment growing in a region, according to Lerman, a computer scientist.

The study, published in the Journal of Medical Internet Research, examined public health attitudes based on 27 million tweets by 2.4 million Twitter users in the U.S. between Jan. 21 and May 1, 2020.

Researchers parsed the data by demographics and geography and in an attempt to achieve near real-time monitoring of partisan and “pseudo-science” attitudes. They then used advanced computing techniques to refine the data, according to Lerman.

The team tracked attitudes in a region to see how they changed and found that polarization on the topic of science lessened over time, suggesting that most people are ready to accept scientific evidence and trust those who produce it, she said.

The ability to track public discourse around coronavirus and compare it with epidemiological outcomes emerged as a result of the study. according to Lerman, an expert in mining social media for clues about human behavior.

“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,” Lerman said. “We can also see what topics are important to these segments of society, and we can plan proactively to prevent disease outbreaks from happening.”

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