Battling the Infodemic
Researchers are analysing false rumours and disinformation about COVID-19 in hopes of curbing their spread.
In the first few months of 2020, wild conspiracy theories about Bill Gates and the nwe coronavirus began sprouting online. Gates, the Microsoft co-founder and billionaire philanthropist who has funded efforts to control the virus with treatments, vaccines and technology, had himself created the virus, argued one theory. He had patented it, said another. He'd use vaccines to control people, declared a third. The flase claims quitely proliferated among groups predisposed to spread the message---people opposed to vaccines, globalization or the privacy infringements enabled by technology. Then one went mainstream.
On 19 March, the website Biohackinfo.com falsely claimed that Gates planned to use a coronavirus vaccine as a ploy to monitor people through an injected microchip or quantum-dot spy software.. Two days later, traffic started flowing to a YouTube video on the idea. It's been viewed nearly two million times. The idea reached Roger Stone---a former adviser to US President Donald Trump---who in april discussed the theory on a radio show, adding that he'd never trust a coronavirus vaccine that Gates had funded. The interview was covered by the newspaper the New York Post, which didn't debunk the notion. Then that article was likes, shared or commented on by nearly one million people on Facebook. "That's better performance than most mainstream media news stories," says Joan Donovan, a sociologist at Harvard University in Cambridge, Massachusetts.
Donovan charts the path of this piece of disinformation like an epidemiologist tracking the transmission of a new virus. As with epidemics, there are "superspreader" moments. After the New York Post story went live, several high-profile figures with nearly one million Facebook followers each posted their own alarming comments, as if the story about Gates devising vaccines to track people were true.
The Gates conspiracy theories are part of an ocean of misinformation on COVID-19 that is spreading online. Every major news event comes drenched in rumours and propaganda.
But COVID-19 the "the perfect storm for the diffusion of false rumour and fake news", says data scientist at the University of Venice, Italy. People are spending more time at home, and searching online for answers to an uncertain and rapidly changing situation. "The topic is polarizing, scary, captivating. And it's really easy for everyone to get information that is consistent with their system of belief," he says. The World Health Organization (WHO) has called the situation an infodemic: "An over-abundance of information---some accurate and some not---rendering it difficult to find trustworthy sources of information and reliable guidance."
For researchers who track how information spreads, COVID-19 is an experiemntal subject like no other. "This is an opportunity to see how the whole world pays attention to a topic," says one woman researcher. She and many others have been scrambling to track and analyse the disparate falsehoods floating around---both "misinformation", which is wrong but not deliberately misleading, and "disinformation", which refers to organized falsehoods that are intended to deceive. In a global healthe crisis, inaccurate information doesn't only mislead, but could be a matter of life and death if people start taking unproven drugs, ingoring public-health advice, or refusing a coronavirus vaccine if one becomes available.
By studying the sources and spread of false information about COVID-19, researchers hope to understand where such information comes from, how it grows and---they hope--how to elevate facts over falsehood. It's a battle that can't be won completely, researchers agree---it's not possible to stop people from spreading ill-founded rumours. But the language of epidemiology, the hops is to come up with effective strategies to "flatten the curve" of the infodemic, so that bad information can't spread as far and as fast.
No filter
Researchers have been monitoring the flow of information online for years, and have a good sense of how unreliable rumours start and spread. Over the past 15 years, technology and shifting societal norms have removed many of the filters that were once placed on information, says director of the communciations agency, sb who has worked on analysing misinformation for the UK government. Rumour-mongers who might once have been isolated in their local communities can connect with like-minded sceptics anywhere in the world. The social-media platforms they use are run to maximize user engagement, rather than to favour evidence-based information. As these platforms have exploded in popularity over the past decade and a half, so political partisanship and voices that distrust authority have grown too.
To chart the current infodemic, data scientists and communications researchers are now analysing millions of messages on social media. A team led by Emillo Ferrara, a data scientist at the University of Southern California in Los Angeles, has released a data set of more than 120 million tweets on the coronavirus. Theoretical physicist Manilio, a research institute for artificial intelligence in Trento, Italy, has set up what he calls a COVID-19 "infodemic observatory", using automated software to watch 4.7 million tweets on COVID-19 streaming past everyday. He and his team evaluate the tweets's emotional content and, where possible, the region they were sent from. They then estimate their reliability by looking at the sources to which a message links. Similiarly, in March, Quattrociocchi and his co-workers reported a data set of around 1.3 million posts and 7.5 million comments on COVID-19 from several social-media platforms, including Reddit, WhatsApp, Instagram and Gab, from 1 January to mid-February.
A study in 2018 suggested that false nws generally travels faster than reliable news on Twitter. But that isn't necessarily the case in this pandemic, says Quattrociocchi. His tea followed some example of false and true COVID-19 news---as classified by fact-checker sites---and found that reliable posts saw as many reactions as unreliable posts on Twitter. The analysis is preliminary and hasn't yet been peer reviewed.
Ferrara says that in the millions of tweets about the coronavirus in January, misinformation didn't dominate the discussion. Much of the confusion at the start of the pandemic related to fundamental scientific uncertainties about the outbreak. Key features of the virus---its transmissibility, for instance, and its case-fatality rate---could be estimated only with large error margins.Where expert scientists were honest about this, says biologist Carl at the university in Seattle, it created an "uncertainty vacuum" that allowed superficially reputable sources to jump in without real expertise. These included academic with meagre credentials for pronouncing on epidemiology, he says, or analysts who were good at crunching numbers but lacked a deep understanding of the underlying science.
