With misinformation rife on social media, users could do with a tool that can sift truth from fiction.
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 retweets or re-shares of false information.
The system analyzed language in more than 100 rumors — some later confirmed — that went viral on Twitter. The 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. 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.