The University of Cambridge has released a new game designed to help people sort fact from cleverly faked fiction when it comes to online information about Covid-19.
Players of Go Viral! assume the role of a malicious actor who is on a mission to spread misinformation online about the global health pandemic. The online game has been designed to introduce members of the public to the wide variety of techniques criminals use to circulate fake news, particularly on social media.
Go Viral! was launched in partnership with the UK government and published last week in the Journal of Experimental Psychology: Applied. Its creators hope that the game will make it easier for people to identify and disregard information about Covid-19 that can't be substantiated by legitimate sources.
The team who made the game say that playing it just once will decrease the chances of a social media user's being duped with fake news for a period of at least three months.
Dr. Sander van der Linden, leader of the project and the Social Decision-Making Lab at Cambridge, said false information was difficult to dislodge from the minds of people who have been exposed to it.
"Fake news can travel faster and lodge itself deeper than the truth," said van der Linden. "Fact-checking is vital, but it comes too late and lies have already spread like the virus."
Since the removal of fake news from the mind of a victim is so difficult even when the actual truth has come to light, the game's makers opted for a more pre-emptive approach to tackling what is a growing problem in all forms of media.
“We are aiming to pre-emptively debunk, or pre-bunk, misinformation by exposing people to a mild dose of the methods used to disseminate fake news," said van der Linden.
“It’s what social psychologists call ‘inoculation theory.’”
Over the course of around six minutes, players are introduced to various news-spreading techniques commonly used by bad actors. These include using emotionally charged language to create outrage and fear, quoting from fake 'experts,' and mining conspiracies for social media ‘likes.’