From Fast Company:
Publicly correcting misinformation on Twitter is not the thing to do. This is the conclusion of MIT researchers who attempted to politely correct flagrantly false posts on social media.
“What we found was not encouraging,” says coauthor Moshen Mosleh, a research affiliate at MIT’s Sloan School of Management, whose study appeared this week in Nature. Polite corrections to factually inaccurate tweets set off an avalanche of further misinformation and toxic language. “They retweeted news that was significantly lower in quality and higher in partisan slant, and their retweets contained more toxic language.”
Read the Complete Research Summary Article
From the Underlying Research Article: “Shifting Attention to Accuracy Can Reduce Misinformation Online (via Nature; 10.1038/s41586-021-03344-2)
In recent years, there has been a great deal of concern about the proliferation of false and misleading news on social media. Academics and practitioners alike have asked why people share such misinformation, and sought solutions to reduce the sharing of misinformation. Here, we attempt to address both of these questions. First, we find that the veracity of headlines has little effect on sharing intentions, despite having a large effect on judgments of accuracy. This dissociation suggests that sharing does not necessarily indicate belief. Nonetheless, most participants say it is important to share only accurate news. To shed light on this apparent contradiction, we carried out four survey experiments and a field experiment on Twitter; the results show that subtly shifting attention to accuracy increases the quality of news that people subsequently share. Together with additional computational analyses, these findings indicate that people often share misinformation because their attention is focused on factors other than accuracy—and therefore they fail to implement a strongly held preference for accurate sharing. Our results challenge the popular claim that people value partisanship over accuracy, and provide evidence for scalable attention-based interventions that social media platforms could easily implement to counter misinformation online.
Direct to Full Text Article