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Press release

Fakebuster: Fighting fake news with artificial intelligence
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The Snipfeed team is happy to introduce our first public tool to debunk fake news online: Fakebuster.

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Developed by UC Berkeley and Stanford data scientists Fakebuster helps you to check how trustworthy an article is based on the writing style, facts mentioned as well as the headline. There is no magic here, and this should be only considered as a mere indicator. Trust and “fake news” are two complicated and ambiguous terms, there is no simple answer to address those issues. However, trained over hundreds of thousands of articles and checking in real time where and how a piece of news spreads, the algorithm gives most of the time a pretty good score.

As Mark Zuckerberg told legislators, artificial intelligence cannot stop fake news, and it could be five years or more until it might be able to do it. However, we believe we should give to the public state of art tools to help anyone figure out If they are in front of doubtable information.  This is a general effort which is why we ask everyone to report mistakes when the AI gives a wrong result on an article: It will expand our dataset and improve the algorithm. Keep in mind there is no real dataset on fake news yet and our goal here is to build the largest to date.

This effort goes hand in hand with a relfexion on how should content be distributed online espcialy on mobile. The “news” format needs to change dramatically, we still offer users content experience similar to what they would find on newspaper while it needs to be entirely rethought. Publishers need to pursue their own avenues of distribution and monetization. Their need to acquire, retain and monetize is one of the most difficult challenge to master profitably and at scale, which is why most companies relied on Social media. But the latter were never meant for It as the change of algorithms has shown.

Snipfeed tries to tackle those issues building a game changing platform. Stay tuned.

You can read more about it in this Medium article:

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