Korean scientists create a tool that can help separate fact from fiction on Twitter

BRANDS OF THE WORLD - Scientists say they have a tool that can sift fact from fiction in social media.

Tracking Bigfoot, or not

Bigfoot was finally discovered in 2009 — at least according to rumors circulating on Twitter. With misinformation rife on social media, users could do with a tool that can sift truth from fiction.

More health and science news

Have you used the new health insurance exchanges?

Have you used the new health insurance exchanges?

What has been your experience with the online insurance exchanges?

Why do allergies wax and wane as we age?

Why do allergies wax and wane as we age?

Scientists look at clues in the environment, in the role of viruses — and in our minds.

At least two species of mammals lived for 23 million years

At least two species of mammals lived for 23 million years

Paleontologist’s list of enduring animals includes whale ancestors, marsupials, rodents and insectivores.

NASA ‘flying saucer’ is due to splash into Hawaiian waters

NASA ‘flying saucer’ is due to splash into Hawaiian waters

A spacecraft designed to land heavy loads and people on the surface of Mars will be tested over Kauai.

Now Sejeong Kwon and colleagues at the Korea Advanced Institute of Science and Technology have designed an artificial intelligence system that, they claim, does this correctly around 90 percent of the time. If built into social networks, it could help people avoid embarrassing retweets or reshares of false information.

The system analyzed language used in more than 100 rumors — some later confirmed, others unfounded — that went viral on Twitter over a period of 31 / 2 years. The researchers found that false rumors were far more likely to contain negative terms such as “no” or “not” than positive terms such as “like” or “love.”

Being mentioned in “singleton” tweets — ones that were neither retweeted nor replied to — was another indicator of false content. Indeed, the best predictor that something was false was that it was tweeted separately by many users; accurate stories tended to have a few, widely retweeted sources.

New Scientist

 
Read what others are saying