A new study conducted by three MIT researchers has discovered that false news spreads much faster than truth on the social media platform Twitter.
According to this study, called “The Spread of True and False News Online” published in the journal Science, falsehoods are 70% more likely to be retweeted than true stories. The latter also took six times as long as false stories to reach an audience of 1500.
Looking at “cascades” which are uninterrupted retweet chains, false news stories reached cascade depths of 10 almost 20 times faster than true stories did. The top 1% false news cascades reached between 1,000 and 1,00,000 users whereas the truth rarely spread to more than 1,000 people. Further, falsehoods are retweeted by more unique users at every level of the cascade, as per the public release by the American Association for the Advancement of Science.
One of the researchers involved in this story, Deb Roy, an associate professor of media and art at the MIT Media Lab said that the researchers were “somewhere between surprised and stunned” at the different courses that truth and falsehoods took on Twitter.
For this study, the researchers looked at around 4.5 million tweets from 3 million people, which accounted for 1,26,285 stories that spread on Twitter between 2006 and 2017. They then used six different fact-checking websites, snopes.com, politifact.com, factcheck.org, truthorfiction.com, hoax-slayer.com and urbanlegends.about.com, to assess the veracity of each of these stories and classified them into ‘true’, ‘false’, and ‘mixed’ categories.
Nearly two thirds of the stories that were considered were false, while less than one fifths were true and the rest mixed, INQUIRER.NET reported. Sinan Aral, a co-author of this paper from MIT Sloan Institute of Management said that the six websites agreed with each other in 95% of the cases.
The three falsehoods that spread the farthest were about Muslim guard who was celebrated as a hero during the Paris shootings, an Iraq war veteran losing to Caitlyn Jenner for an ESPN courage award and an episode of The Simpsons from 2000 that predicted the Trump presidency, said MIT data scientist and lead author Soroush Vosoughi.
Of the 1,26,000 odd stories that they analysed, the researchers found that politics was the biggest news category accounting for around 45,000 stories, followed closely by urban legends, business, terrorism, science and entertainment. Further, political falsehoods reached 20,000 people 3 times faster than true stories reached 10,000 people.
Humans, not bots, responsible for disseminating fake news
According to Aral, the results revealed that “False news spread further, faster, deeper, and more broadly than the truth in every category of information”.
Surprisingly, this result did not change when tweets by bots (automated non-human accounts) were weeded out of the analysis, revealing that humans and not bots were responsible for the proliferating fake news stories.
Aral said that this was contrary to widespread belief that Russian bots may have influenced the U.S Elections 2016 heavily. He emphasised that it was important to understand the true impact of bots as that will determine how we react to false news.
Aral also said that this result indicated the necessity to adopt a more general approach in tackling the false news problem. “Now behavioral interventions become even more important in our fight to stop the spread of false news, whereas if it were just bots, we would need a technological solution.”
However, this optimism is not shared by everyone. David Lazer, a political and computer scientist at Northeastern University, who was not a part of this study, said that despite its results, the study may have missed many bots and cyborgs (in-between humans). His independent study revealed that around 80% of false stories come from a mere 0.1% of users.
Surprise, novelty drive false news spread
The researchers postulated that fake news spreads faster because it is more novel. According to the researchers, people want to spread novel information because sharing previously unknown information captures the attention. As Aral put it, “people who share novel information are seen as being in the know”. Roy said, “It’s easier to be novel and surprising when you’re not bound by reality”, Roy suggested.
David Beer, reader at University of York commented that people are more likely to circulate stories that are more surprising and attention-grabbing. He also suggested that more nuanced and detailed accounts are less likely to be shared and circulated.
The emotional profiles of the responses to tweets carrying these stories revealed that people were more likely to express feelings of surprise and disgust on reading false news whereas the truth garnered responses displaying sadness, anticipation and trust. The sensational nature of false news and the surprise it elicits may, thus, be responsible for the extent to which it spreads.
The researchers warned that while their results were limited to Twitter, similar phenomena may be at work in other social media platforms like Facebook and emphasised the need for careful studies to understand
Contrary to popular opinion that influential people with a huge follower base may be responsible for spreading false news, the study has shown that “people who spread false news had significantly fewer followers, were less often verified, and were less active on Twitter”, reported Vox.
Brian Resnick from Vox warned readers that the study was not without limitations. The impact of the truth and falsehoods have to consider that while false news spreads widely through social media, truth spreads through more conventional methods. Further, he argued that using fact-checking websites that are used more to check for fake news may not have allowed for a proper sampling of true news stories.
Writing for The Scholarly Kitchen, Kent Anderson pointed out what could possibly be the biggest flaw in the study – the Twitter algorithm. By not knowing and considering the black box that is the Twitter algorithm, he said that any study of how false news spreads on Twitter is failing to consider the biggest player that decides the content that is displayed to a user.
He suggested that Twitter “with its scrambled information presentation, weighting of tweets to drive clicks, and advertising-based business model” might be intervening in favour of ‘click-bait’ information.