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South Carolina is talking about celebrating July Fourth, not staying at home

Posted July 1, 2020


South Carolina social media conversations about the July Fourth holiday are focused more on fireworks and celebrations than staying at home to protect against the coronavirus, according to an analysis by the University of South Carolina Social Media Insights Lab.  

On Tuesday, the state Department of Health and Environmental Control recommended that families have “home-based activities” on July 4. The Insights Lab analyzed 1,098 South Carolina social media posts since Monday that mention July Fourth.  Fewer than 10 percent mention the stay-at-home directive.

“There have not been a lot of social media conversations about the Fourth of July, far fewer than last year,” said Kaitlyn Park, Insights Lab manager. “What we see largely are comments about celebrations, fireworks and beaches.”

A number of comments were political.  Some talked about President Trump’s planned visit to Mount Rushmore. Some Trump supporters blamed Democrats for trying to take away America's patriotic holiday due to unfounded concern. One post suggested the country should postpone its celebrations until children confined in U.S. immigration detention centers are released later in the month.


About the Social Media Insights Lab

The lab is part of the College of Information and Communications. It is used for teaching, academic research and public reports intended to help people better understand issues of the day.

The Insights Lab software, Crimson Hexagon, uses artificial intelligence to interpret data. View a full list of reports  and follow the lab on Twitter at @UofSCInsights

For media inquiries or to request graphic files, contact Rebekah Friedman at rebekahb@mailbox.sc.edu or 803-576-7270.

How is sentiment calculated?
The lab uses software developed by Crimson Hexagon, now known as BrandWatch following a merger. The software gauges the emotional tone of conversations using auto-sentiment artificial intelligence technology. This feature is useful for identifying patterns within large sets of social media data, but it should be noted that auto-sentiment has its limits. For example, it does not always recognize sarcasm, nor does it account for posts which may express more than one emotion.

 


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