Fake News

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Twitter Tests Fake News Warning System

Andrew Orr · · 4 Comments

Twitter is testing a fake news warning system on its platform. Bright labels will appear under tweets with misinformation.

Twitter confirmed that the leaked demo, which was accessible on a publicly available site, is one possible iteration of a new policy to target misinformation it plans to roll out March 5.

In this version, disinformation or misleading information posted by public figures will be corrected directly beneath the tweet by fact-checkers and journalists who are verified on the platform, and possibly other users who will participate in a new “community reports” feature, which the demo claims is “like Wikipedia.”

I could see “community reports” abused by Twitter trolls mass-reporting anything they disagree with as fake news. Hopefully Twitter builds a good system.

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Only 44% of People Correctly Spotted Fake News on Facebook

Andrew Orr · · 1 Comment

In a small study (n=80) undergraduate students were fitted with a wireless electroencephalography (EEG) headset. They were then asked to read political news headlines as they would appear on a Facebook feed to determine their credibility. They overwhelmingly chose headlines that aligned with their political beliefs as true.

“We all believe that we are better than the average person at detecting fake news, but that’s simply not possible,” said lead author Patricia Moravec, assistant professor of information, risk and operations management. “The environment of social media and our own biases make us all much worse than we think.”

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New Tool Credder Will Rate News Media Credibility

Andrew Orr · · Add Comment

A startup called Credder wants to offer a rating system like Rotten Tomatoes, but for news publications. The hope is to offer people a way to check the credibility of a particular website, and rate them.

Startup Credder is trying to solve this problem with reviews from both journalists and regular readers. These reviews are then aggregated into an overall credibility score (or rather, scores, since the journalist and reader ratings are calculated separately). So when you encounter an article from a new publication, you can check their scores on Credder to get a sense of how credible they are.

Sounds like a good idea to me.

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The 11 People Trying to Fight Fake News in the Indian Election

Charlotte Henry · · Add Comment

The Indian election is the world’s largest democratic exercise. There is, unsurprisingly, some concern that it could be undermined by fake news. Bloomberg News met Boom Live, an 11-strong team of fact-checkers that make up 1 of the 7 firms working with Facebook’s efforts.

Based on the early tallies, more than 60 percent of India’s 900 million eligible voters are expected to cast ballots between now and May 19, as the center-left Congress Party tries to seize power from the right-wing Bharatiya Janata Party. As in other elections around the world, paid hacks and party zealots are churning out propaganda on Facebook and the company’s WhatsApp messenger, along with Twitter, YouTube, TikTok, and other ubiquitous communication channels. Together with Facebook’s automated filters, Boom’s 11 fact-checkers and its similar-size fellow contractors are the front line of the social network’s shield against this sludge.

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It is Still Down to Humans to Fight Fake News

Charlotte Henry · · 1 Comment

2019 is undoubtedly going to be a big year in AI. The discussion over fake news will continue too. Sean Gourley, CEO of machine intelligence company Primer, wrote in Wired that while progress in AI is being made, at the moment humans, not algorithms, need to lead the fight against fake news. I know from my own research into fake news how important a role bots play in the spread of disinformation. Unfortunately, the technology is not yet discerning enough to be relied upon to separate fact from fiction. AI has not been able to fight back. It may be able to one day, but until then, it is down to us humans.

One of the reasons that computational propaganda has been so successful is that the naïve, popularity-based filtering systems employed by today’s leading social networks have proven to be fragile and susceptible to targeted fake information attacks.To solve this problem, we will need to design algorithms that amplify our intelligence when we’re interacting together in large groups. The good news is that the latest research into such systems looks promising.