Data Science

MIT Study: False News Spreads Faster than Truth Online


The rapidity with which falsity travels has been proverbial for centuries: “Falsehood flies, and the Truth comes limping after it,” wrote Swift in 1710. Yet empirical verification of this common wisdom has been scarce — to our chagrin these past few years as lies in seven-league boots outpace a hobbled truth on platforms seemingly bespoke for this lopsided race.

A comprehensive new study from MIT looks at a decade of tweets, and finds that not only is the truth slower to spread, but that the threat of bots and the natural network effects of social media are no excuse: we’re doing it to ourselves.

The study, published recently in Science, looked at the trajectories of more than 100,000 news stories, independently verified or proven false, as they spread (or failed to) on Twitter . The conclusion, as summarized in the abstract: “Falsehood diffused farther, faster, deeper, and more broadly than the truth in all categories of information.”

But read on before you blame Russia, non-chronological feeds, the election or any other easy out. The reason false news (a deliberate choice in nomenclature to keep it separate from the politically charged “fake news”) spreads so fast is a very human one.

“We have a very strong conclusion that the spread of falsity is outpacing the truth because human beings are more likely to retweet false than true news,” explained Sinan Aral, co-author of the paper.

“Obviously we didn’t get inside the heads of the people deciding to retweet or consume this information,” he cautioned. “We’re really just scratching the surface of this. There’s been very little empirical large scale evidence one way or the other about how false news spreads online, and we need a lot more of it.”

Still, the results are robust and fairly straightforward: people just seem to spread false news faster.

It’s an unsatisfying answer, in a way, because people aren’t an algorithm or pricing model we can update, or a news outlet we can ignore. There’s no clear solution, the authors agreed — but that’s no reason why we shouldn’t look for one.

A decade of tweets

The study, which co-author Soroush Vosoughi pointed out was underway well before the current furor about fake news, worked like this.

The researchers took millions of tweets from 2006 to 2017 and sorted through them, finding any that related to one of 126,000 news stories that had been evaluated by at least one of six fact-checking organizations: Snopes, PolitiFact, FactCheck.org, Truth or Fiction, Hoax Slayer and About.com.

They then looked at how those news stories were posted and retweeted using a series of measures, such as total tweets and retweets, time to reach a threshold of engagement, reach from the originating account and so on.

These patterns form “cascades” with different profiles: for instance, a fast-spreading rumor that’s quickly snuffed out would have high breadth but little depth, and low virality.

Read the source article at TechCrunch.


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