Google, Facebook and Twitter Struggle to Identify Fake News

Nancy Anderson
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Fake news made big news in 2016 when mainstream media outlets reported on false news stories circulating around the American presidential election. These stories came to light due to intense media scrutiny throughout the Donald Trump versus Hillary Clinton campaign period, yet they didn't determine the outcome of the election. However, made-up news is still a problem that Twitter, Facebook and Google must deal with in the future.

How Fake News Became a Thing

Social media websites and search algorithms boost the popularity of fake news. When stories are shared by thousands or millions of people, they go to the top of the search pile or into a special section off to the side of your feed. It doesn't matter if the news is real or not. The headline of the original story appears prominently somewhere on the home page of your account, making it more likely that you'll click on and read it.

Once the term 'fake news' became popular during the election, politicians and media pundits began overusing it as a way to discredit real stories. For example, Trump called a CNN story fake when it disagreed with his position, even though it was a well-researched piece. The National Catholic Register called a story in The Atlantic fake when it compared how ultrasound technology can influence someone's political ideas.

There are even positions in vaunted media companies designed to root out fake news and debunk it. CNN created a beat position whose sole purpose is to research false stories. Governments in European countries created commissions to investigate misinformation spread through internet.

How Technology Can Solve This Problem

Social media platforms and Google can take several steps to solve the problem of false news versus real news. Companies can change the way they use advertising to generate revenue. In response to this issue, Google banned 200 seemingly real news outlets from using its AdSense algorithm. Facebook updated the program to reject news stories coming from a single source of information as a way to prevent viral stories from taking over someone's feed.

One student at Stanford created an artificial intelligence algorithm that takes into account 55 criteria for separating real news from false rumors. Anyone can use the software for free. Snap, the parent company of Snapchat, went so far as to fact-check stories on its platform first before people circulate them. As of 2017, Snap has one of the most robust news verification policies among social websites. Considering the importance of social sharing to advertising, personal branding and disseminating information, Snap's decision seems to be a step backward in terms of speed, but a step forward to try to clamp down on disinformation.

Websites that thrive on advertising revenue by spreading false news can still game the system by creating multiple sites that share the same story. Once enough people click on the share buttons or likes through these website's social presence, the stories may still become viral even though they are untrue. These platforms still have to adapt to ways of getting around search algorithms.

Fake news is a real problem for tech firms, but it doesn't have to be this way. Just like anything else in the tech industry, companies must adapt to solve these dilemmas while still finding ways to make money.


Photo courtesy of Stuart Miles at FreeDigitalPhotos.net

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