Crowdsourcing can effectively check fake news swamp

MIT study suggests crowdsourcing approach could work well, if implemented correctly

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Using public opinion surveys to vet the authenticity of political stories may be an effective strategy to combat the menace of fake news and other kinds of online misinformation, an MIT study has found.

False news stories have proliferated online in recent years, and social media sites such as Facebook have received sharp criticism for giving them visibility.

Facebook also faced pushback for a January 2018 plan to let readers rate the quality of online news sources.

However, the study from Massachusetts Institute of Technology (MIT) in the US suggests such a crowdsourcing approach could work well, if implemented correctly.

"What we found is that, while there are real disagreements among Democrats and Republicans concerning mainstream news outlets, basically everybody—Democrats, Republicans, and professional fact-checkers—agree that the fake and hyperpartisan sites are not to be trusted," said David Rand, an MIT scholar.

Using a pair of public-opinion surveys to evaluate of 60 US news sources, the researchers found that Democrats trusted mainstream media outlets more than Republicans do -- with the exception of Fox News, which Republicans trusted far more than Democrats did.

However, when it comes to lesser-known sites peddling false information, as well as "hyperpartisan" political websites, both Democrats and Republicans show a similar disregard for such sources.

"If the goal is to remove really bad content, this actually seems quite promising," Rand says.

To perform the study, the researchers conducted two online surveys that had roughly 1,000 participants each. In each case, respondents were asked to rate their trust in 60 news outlets, about a third of which were high-profile, mainstream sources.

The second survey's participants had demographic characteristics resembling that of the US as a whole.

The survey also measured the general audience's evaluations against a set of judgments by professional fact-checkers, to see whether the larger audience's judgments were similar to the opinions of experienced researchers.

Respondents generally distrusted the more marginal websites, there was significant agreement among the general audience and the professional fact-checkers.

That means the crowdsourcing approach could work especially well in marginalising false news stories—for instance by building audience judgments into an algorithm ranking stories by quality.

Crowdsourcing would probably be less effective, however, if a social media site were trying to build a consensus about the very best news sources and stories.

However, researchers said that the method would indeed build bias into the system, because people are more skeptical of news sources they have less familiarity with—and there is likely good reason why most people are not acquainted with many sites that run fake or hyperpartisan news.

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