Women over 50 are most likely to share pandemic-related stories on Twitter from websites that share fake news, and Republicans are many times more likely to share questionable material than Democrats, according to a new study by  researchers from Northeastern, Harvard, Northwestern, and Rutgers.

The study looked at age and demographics to pinpoint who is sharing false pandemic content via Twitter—cross referencing shares on the social media platform this year with URLs from five websites identified with fake news.

“80 to 90 percent of fake news comes from a few tenths of one percent of all accounts,” says David Lazer, University Distinguished Professor of political science and computer and information sciences at Northeastern, and one of the researchers who conducted the study.

Researchers defined fake news as  information that mirrors legitimate news in form, but “lacks the news media’s editorial norms and processes for ensuring the accuracy and credibility of information.”

The fake news domain with the most shares is Gateway Pundit, the study found. Since March, the website has received an order of magnitude more shares than the second most shared fake news domain, Info Wars.

The popularity of Gateway Pundit is even more striking when compared with all other web domains—including mainstream news media—that share news about the pandemic.  In August and September respectively, Gateway Pundit was ranked the 4th and 6th most shared domain for URLs about COVID-19. In August, the only domains with more COVID-19-related shares were the New York Times, the Washington Post and CNN,  the study found.

“It is notable that, during 2020, registered Republicans and older people are more likely to share URLs from fake news domains. The same demographics were also more likely to do so during the 2016 presidential election,” researchers wrote in the study released today.

But researchers note that while older people are more likely to share fake news, younger people are more likely to believe it. In a study released earlier this year, researchers found that minorities and younger people are more susceptible to fake news and misinformation about COVID-19, and younger generations are also more likely to believe false claims they receive on closed messaging platforms such as WhatsApp and Facebook Messenger.

 

 

According to that report, 22 percent of participants said they believed the rumor that COVID-19 originated as a weapon in a Chinese lab, and 7 percent trusted the claim that the flu vaccine increases the risk of contracting COVID-19.  

This time around, researchers were curious about who was behind the sharing of bad information, not who was believing it. The average age of these so-called “super sharers” is 59, “considerably older than the average Twitter user,” Lazer says.

“In terms of the data, it’s disproportionately older women,” he says.

In October, Twitter started labeling tweets that contain misleading information about COVID-19, flagging the posts in a way that de-amplifies them in the platform’s algorithm, regardless of how viral they go. In some cases, misleading tweets are simply deleted.

Since the global respiratory disease took hold, killing more than 1 million people worldwide so far, there has been a great deal of confusion and misinformation surrounding COVID-19—much of it occurring online, in the so-called Infodemic. 

To conduct the study, researchers collected COVID-19-related tweets from registered voters in America between January and September 2020, and examined the content posted by a list of accounts matched to demographic information such as age, race, gender and political party affiliation. The number of COVID-19-related tweets was almost 30 million.

The study found that despite older people sharing more misinformation, they are actually more informed, likely because older users are more interested in COVID-19 generally. The seeming paradox warrants further research, Lazer says.

“It begs the question that maybe older people [overall] are less misinformed, but older people on Twitter are more misinformed. Alternatively, sharing may not be predicated on believing. We don’t know. This is a question that we will address with additional data.”

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