Then their algorithm takes over. Emergent.info is essentially a web app, built on an API from the back-end database. (You can think of it as something of a data-driven version of Snopes—with a more expansive premise. "Snopes, they're amazing," Silverman says, "but they only do Snopes work; they don't aggregate what other people are doing. This site is able to identify claims and then actually see, okay, who's got the best information about it?") Every hour, Emergent.info's script crawls the stories to see whether their text has changed. The system also checks share counts to monitor how stories are moving through the social media ecosystem.

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All of which, Silverman says, helps to answer questions that haven't been so systematically analyzed before. Among them: "What's the life cycle of a rumor in the press now? And how are news organizations dealing with things that are unconfirmed? And are they updating the stories, and are they sticking with it over time?"

Take the reports—false reports, it turns out—that Durex is making a pumpkin-spice condom: Through Emergent.info, you can see who repeated the rumor, who checked it, and who debunked it. Or take, more seriously, the stories that emerged last week claiming that a meteorite had landed in Nicaragua. (That rumor is still listed as unverified on Emergent.info, because no one has been able to prove that such a meteorite actually fell.) Or take, even more seriously, the claim made earlier this month that the ISIS leader Abu Bakr al-Baghdadi had been killed in a U.S. airstrike. He had not; Emergent.info lists the rumor as "confirmed false."

A challenge news organizations face when it comes to rumor-reporting in particular is the fact that rumors tend to be much more shareable—and much more clickable—than corrections. Take your friend and mine, Ms. Tampa Triple-Breast (self-given pseudonym: Jasmine Tridevil). One of the early stories about her, in the New York Post, got 40,000 shares. The Snopes article (mostly) debunking the initial story had 12,500 shares—a decent amount for a story that is, technically, a non-story.

For the most part, though, the articles debunking the rumor get extremely little attention. (For a more crystalline example of all that, you can look to Buzzfeed's coverage of the story. Its initial story got more than 30,000 shares; its debunking of that story got just over 1,000.) Which means that news organizations often have very little incentive—direct, commercial incentive, at least—to put their time and energy into them. As a result, as Silverman puts it: The Total Recall rumor is "a story that, I would argue, the average person probably doesn't know is not true."

The larger problem with all that is that rumors, once they're put out there into the maw of the media, are notoriously hard to correct. There's the fact that "sorry, just kidding about that three-boobed lady thing" is nowhere near as sharable as a "whoa, three-boobed lady!" thing in the first place. But there's also the fact that there is very little uniformity among media outlets about how updates, corrections, retractions, and the like should be presented to readers. Most outlets will simply update a story that contains a debunked claim; a few will write new stories altogether, linking to the previous one in the process. That can leave readers, however, in a kind of epistemological limbo: You're never quite sure what's been verified and what has not. Trust is a precious resource in journalism; many outlets haven't fully figured out how to preserve it.

"So much of this stuff is public before news organizations get to it," Silverman points out. "So that's a very different dynamic from what used to happen. So if something is by default public, how do you decide when you're doing to point at it in a way that's responsible? And then how do you deal with it as it sort of takes its life path to being true or false?" Bringing some data to bear on those questions, he's hoping, will help news outlets start to answer them.

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