ROLLA — Researchers at Missouri University of Science and Technology are analyzing millions of tweets to track the nation’s mood and behavior during the coronavirus outbreak.
And they say the data could help devise strategies to deal with this pandemic and others.
Computer science professor Sanjay Madria and Ph.D. student Yasin Kabir created a program that started searching Twitter in early March for trending topics, keywords, phrases and other elements in tweets that give some insight to the public sentiment about coronavirus.
“We can see how people are reacting to news and officials’ briefings about COVID-19, when they are more comfortable and when they are more panicked,” Kabir said. “If we can understand that, we can help officials know how to share their news in a way that avoids panic.”
The early analysis shows there has been a steady shift in the mood among Twitter users since the virus started spreading through the U.S.
“In the beginning of March, it was positive, and people were thinking it was not going to affect them. But then they realize it’s not the case, and now, people are having negative sentiments,” Madria said.
The analysis can also provide geographical information among Twitter users who have enabled geotagging. That group has provided Madria and Kabir with more than 3 million tweets. It revealed some success in getting people to stay close to home.
The number of people who tweeted from two different states went down throughout March.
“We have analyzed weekly, and we see that this has helped and the number of cases, basically, have gone down in many different states because people were traveling less,” Madria said.
The two plan to continue collecting and analyzing data for months. They also plan to consult with psychologists to help make more informed conclusions on national mood and anxiety levels based on the tweets.
Madria and Kabir then plan to publish the results in a way that can help public health and policy officials make better decisions on how to manage information and messaging to help stop the spread of a pandemic.
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