Computer Model Seeks to Explain the Spread of Misinformation, and Suggest Counter Measures
It starts with a superspreader, and winds its way through a network of interactions, eventually leaving no one untouched. Those who have been exposed previously may experience little effect when exposed to a different variant.
No, it’s not a virus. It’s the contagious spread of misinformation and disinformation— misinformation that’s fully intended to deceive.
Now Tufts University researchers have come up with a computer model that remarkably mirrors the way misinformation spreads in real life. The work might provide insight on how to protect people from the current contagion of misinformation that threatens public health and the health of democracy, the researchers say.
“Our society has been grappling with widespread beliefs in conspiracies, increasing political polarization, and distrust in scientific findings,” said Nicholas Rabb, a Ph.D. computer science student at Tufts School of Engineering and lead author of the study, which came out January 7 in the journal Public Library of Science ONE. “This model could help us get a handle on how misinformation and conspiracy theories are spread, to help come up with strategies to counter them.”
Scientists who study the dissemination of information often take a page from epidemiologists, modeling the spread of false beliefs on how a disease spreads through a social network. Most of those models, however, treat the people in the networks as all equally taking in any new belief passed on to them by contacts.
