There’s a lot of noise and very little signal on Twitter, and sometimes it can be hard to know what to pay attention to. A team of scientists might be able to help with that, though, because they’re developing algorithms to sort the truthful tweets from the lies. Slate reports new research, due to be published in the journal Internet Research next month, which uses a series of tests to predict whether tweets are true or otherwise. It looks for obvious clues which humans spot instinctively: messages are more likely to be true if they come from a well-followed source, are longer, or contain URLs, for instance. Language is important, too: question marks, exclamation marks, and first- or third-person pronouns all hint that a tweet shouldn’t be trusted. Roll that all together, and the researchers have developed an algorithm that can tell if a tweet’s truthful 86 percent of the time.
About Shelly Palmer
Shelly Palmer is the Professor of Advanced Media in Residence at Syracuse University’s S.I. Newhouse School of Public Communications and CEO of The Palmer Group, a consulting practice that helps Fortune 500 companies with technology, media and marketing. Named LinkedIn’s “Top Voice in Technology,” he covers tech and business for Good Day New York, is a regular commentator on CNN and writes a popular daily business blog. He's a bestselling author, and the creator of the popular, free online course, Generative AI for Execs. Follow @shellypalmer or visit shellypalmer.com.