How to track fake news on social media article The BBC is being criticised for its coverage of the Zika virus, which has claimed more than 1,000 lives across Brazil and spread to over 1,800 countries.
But a new tool called ‘fake news detection’ has the BBC at a competitive disadvantage.
How it works Fake news is a collection of fake or misleading content that purports to be from a news organisation, but is not backed up by the source, according to Mark Smith, the BBC’s director of news.
The BBC has a team of researchers in the US, Australia and Canada, who spend a week researching and reviewing each piece of fake news before publishing it on the BBC News website.
The team uses a machine learning algorithm to identify which content is most likely to be fake.
If a piece of content is found to be false, it is removed from the site.
In most cases, a small number of fake stories are removed before they are replaced by a genuine news story.
But there are a few exceptions.
“If we find that a piece is misleading, it will be removed from our site,” Mr Smith said.
The algorithm uses a range of criteria to determine if a piece has been manipulated or fake news.
If the piece contains a claim, it may contain a claim that is untrue or misleading, but it may not be as clearly false or misleading as a claim.
The most common way that a fake story is debunked is through a social media post.
It is possible to flag a fake article, so a user can see it on Facebook, Twitter or any other social media site.
The fake article that is flagged is then shown in the newsfeeds for the fake news, along with the number of retweets it has received.
The article can be shown to the user in a “clicked” state.
“We have had very good success with this in the past, but the problem is we don’t have a good way of spotting fake news,” Mr Miller said.
“When we start getting reports that are very strong we start to feel a bit like we’ve got an alarm going off.”
He said the BBC is trying to improve its technology to identify fake stories.
“As technology improves, we can use it to detect fake news and flag it so we can keep up with it,” he said.
A more sophisticated version of the algorithm uses data from real users to create a list of “fake news” articles that appear in newsfeed and are likely to have been posted by the same user.
“The best way to get around this is by checking the content that’s being shared on social networks,” Mr Jones said.
“If someone’s sharing a picture of a car they are not necessarily sharing a car, or they’re sharing something they’re not necessarily retweeting,” he added.
He said the system can be applied across a wide range of different social media platforms, including Twitter and Facebook.
But the BBC said it has not yet had a chance to test its new technology, and it will take time to make sure it is accurate.
What’s the point of fake journalism?
The BBC’s new system is not a new development.
Earlier this year, the network announced it was testing a new algorithm to detect if articles published on its news website were misleading.
The new system will also use information from its audience’s comments and comments on the news article to determine the quality of the content.
But Mr Jones told the BBC that it is not about detecting the accuracy of articles; it is about ensuring the accuracy is fair to both readers and the news outlet.
“You can’t use the same method that’s been proven to work for Facebook to tell you how many retweers someone is sharing on Twitter,” he told the ABC.
“So we’re really trying to build on this idea that there’s no difference between Facebook and Twitter.”
Mr Smith said the new system would only work if the news is accurate, not whether the news was fake.
The real news is that the BBC has had to respond to fake news stories in a way that is not in its interests, he said, but that is a challenge.
“Fake news doesn’t stop,” he says.
Fake stories can be spread by any means, including bots and malicious software.
“It’s really hard to find them in the way that they can be reported,” he explained.
The fake news detector is one of a number of new technologies that have been developed by the BBC.
A new ‘digital blasphemy’ programme has been introduced to better track fake content and to highlight the impact of the virus, as well as other social and cultural issues.
It also has been updated to be able to detect new, more complex types of fake content, such as “misleading” or “misbranded” content.
It has also been updated with more details on the development of the new detection system, and the fact that fake news detection is a subject of a major academic study.