False News Spreads Faster Than Truth on Twitter, MIT Study Reveals

False news travels significantly faster and reaches more people than accurate information on Twitter, according to groundbreaking research from three MIT scholars. The study found that falsehoods are 70 percent more likely to be retweeted than truthful stories and reach 1,500 people six times faster.

“We found that falsehood diffuses significantly farther, faster, deeper, and more broadly than the truth, in all categories of information, and in many cases by an order of magnitude,” explained Sinan Aral, professor at the MIT Sloan School of Management and co-author of the paper published in Science.

The researchers analyzed approximately 126,000 news story cascades on Twitter, cumulatively shared over 4.5 million times by around 3 million users between 2006 and 2017. To determine accuracy, they relied on assessments from six established fact-checking organizations, finding their judgments overlapped more than 95 percent of the time.

Surprisingly, the researchers discovered that automated bots were not primarily responsible for the rapid spread of misinformation. “When we removed all of the bots in our dataset, the differences between the spread of false and true news stood,” said Soroush Vosoughi, a postdoctoral researcher at MIT’s Laboratory for Social Machines and co-author of the study.

Instead, human behavior appears to drive the phenomenon. False stories generate more surprise and disgust among users, while true stories tend to elicit sadness, anticipation, and trust. This emotional distinction suggests novelty plays a crucial role in what content goes viral.

“False news is more novel, and people are more likely to share novel information,” Aral noted. “People who share novel information are seen as being in the know,” giving users social currency when they spread previously unknown—if potentially false—information.

The study revealed the problem is particularly acute in political news, which comprised the largest category with approximately 45,000 cascades. Urban legends, business, terrorism, science, entertainment, and natural disasters followed, though false stories spread more prominently in political content than other categories.

The genesis of this research traces back to the 2013 Boston Marathon bombings, when Vosoughi observed significant misinformation circulating on social media during the crisis. This experience prompted him to shift his doctoral focus toward developing models that could predict the veracity of information on Twitter.

Twitter provided the researchers with full access to its historical archives, with support from Deb Roy, who served as Twitter’s chief media scientist from 2013 to 2017 and is also an associate professor at the MIT Media Lab and study co-author. Roy described the team as “somewhere between surprised and stunned” by the disparities they found between how true and false information spread.

The findings have significant implications for combating misinformation online. “Now behavioral interventions become even more important in our fight to stop the spread of false news,” Aral emphasized. “Whereas if it were just bots, we would need a technological solution.”

The researchers suggest their work could help establish measurements or benchmarks for social networks, advertisers, and other stakeholders to evaluate information quality. While they focused exclusively on Twitter, similar patterns may exist on other platforms like Facebook, though they stress additional research is needed.

“Science needs to have more support, both from industry and government, in order to do more studies,” Aral said, highlighting the need for continued investigation of online information ecosystems.

For everyday users navigating social media, Roy offers simple but powerful advice: “Think before you retweet.”