“When people are consuming news on social media, their inclination to share that news with others interferes with their ability to assess its accuracy, according to a new study co-authored by MIT researchers.”
Photo credit: Jose-Luis Olivares, MIT
Date: 9 July 2020
Institution: Massachusetts Institute of Technology
Study published in: Psychological Science
Digest: In order to be updated about the COVIR-19 pandemic, we often endup health information via various news sources. It will also expose people to health misinformation about the illness.
a study co-authored by MIT scholars contains bad news and good news about Covid-19 misinformation — and a new insight that may help reduce the problem.
The bad news is that when people are consuming news on social media, their inclination to share that news with others interferes with their ability to assess its accuracy. The study presented the same false news headlines about Covid-19 to two groups of people: One group was asked if they would share those stories on social media, and the other evaluated their accuracy. The participants were 32.4 percent more likely to say they would share the headlines than they were to say those headlines were accurate.
“There does appear to be a disconnect between accuracy judgments and sharing intentions,” says MIT professor David Rand, co-author of a new paper detailing the findings. “People are much more discerning when you ask them to judge the accuracy, compared to when you ask them whether they would share something or not.”
The good news: A little bit of reflection can go a long way. Participants who were more likely to think critically, or who had more scientific knowledge, were less likely to share misinformation. And when asked directly about accuracy, most participants did reasonably well at telling true news headlines from false ones.
Moreover, the study offers a solution for over-sharing: When participants were asked to rate the accuracy of a single non-Covid-19 story at the start of their news-viewing sessions, the quality of the Covid-19 news they shared increased significantly.
“The idea is, if you nudge them about accuracy at the outset, people are more likely to be thinking about the concept of accuracy when they later choose what to share. So then they take accuracy into account more when they make their sharing decisions,” explains Rand, who is the Erwin H. Schell Associate Professor with joint appointments at the MIT Sloan School of Management and the Department of Brain and Cognitive Sciences.
“A lot of people have a very cynical take on social media and our moment in history, that we’re post-truth and no one cares about the truth any more,” Pennycook says. “Our evidence suggests it’s not that people don’t care; it’s more that they’re distracted.”
“Our results suggest that the life-and-death stakes of Covid-19 do not make people suddenly take accuracy into [greater] account when they’re deciding what to share,” Lu says.
Indeed, Rand suggests, the very importance of Covid-19 as a subject may interfere with readers’ ability to analyze it.
“Part of the issue with health and this pandemic is that it’s very anxiety-inducing,” Rand says. “Being emotionally aroused is another thing that makes you less likely to stop and think carefully.”
Still, the central explanation, the scholars think, is simply the structure of social media, which encourages rapid browsing of news headlines, elevates splashy news items, and rewards users who post eye-catching news, by tending to give them more followers and retweets, even if those stories happen to be untrue.
“There is just something more systemic and fundamental about the social media context that distracts people from accuracy,” Rand says. “I think part of it is that you’re getting this instantaneous social feedback all the time. Every time you post something, you immediately get to see how many people liked it. And that really focuses your attention on: How many people are going to like this? Which is different from: How true is this?”
The authors are David Rand a professor at MIT, Gordon Pennycook, an assistant professor of behavioral science at the University of Regina; Jonathan McPhetres, a postdoc at MIT and the University of Regina who is starting a position in August as an assistant professor of psychology at Durham University; Yunhao Zhang, a PhD student at MIT Sloan; and Jackson G. Lu, the Mitsui Career Development Assistant Professor at MIT Sloan.
The research was supported by the Ethics and Governance of Artificial Intelligence Initiative of the Miami Foundation; the William and Flora Hewlett Foundation; the Omidyar Network; the John Templeton Foundation; the Canadian Institute of Health Research; and the Social Sciences and Humanities Research Council of Canada.
Original written by: Peter Dizikes
Interested in original study: read here