AGI – The contents were false, but misleading 46 times more effective in determining Covid vaccine hesitancy over reported misinformation. This is according to a new study that explores the real-world impacts of exposure to misinformation.
Similarly, a second study, reported in ‘Science’ and aimed at better understanding the characteristics of ‘supersharer’, a small group of individuals who are increasingly spreading misinformation, reports that just over 2,000 supersharers on X (Twitter) have spread 80% of the fake news during the US presidential elections of 2020.
The research involved a sample of over 660,000 X voters, finding that supersharers were mainly middle-aged Republican women, who resided in conservative states. Disinformation, particularly that spread through social media, is considered a substantial threat to science, public health and democratic processes around the world.
Despite this, the actual impact of exposure to misinformation remains unknown. Furthermore, it is difficult to identify the characteristics and extent of influence of those who spread disinformation. In two separate studies, the authors sought to fill these knowledge gaps through quantitative analyses.
Their findings offer insights for designing more effective strategies to limit the spread of misinformation. In one study, Jennifer Allen, del Massachusetts Institute of Technology, and colleagues assessed the impact of factually accurate but misleading vaccine links shared on Facebook during the vaccine rollout. first Covid-19 vaccine in 2021.
Poor vaccine uptake in the United States has been widely attributed to misinformation on social media. While the impact of blatant vaccine misinformation has been reduced once reported and debunked as false by Facebook’s third-party fact-checker, the more ambiguous contents, such as factual ones that spread skepticism about vaccines but, potentially misleading as they came from credible sources, were often not reported.
An example of this true but misleading content is a story published by the Chicago Tribune: “A ‘healthy’ doctor died two weeks after receiving Covid-19 vaccine; CDC is investigating why.” Although there was no evidence that the vaccine had anything to do with the death, the wording of the headline falsely implied causation. The story has been viewed by nearly 55 million people on the platform.
Using a combination of laboratory experiments, crowdsourcing and machine learning, To estimate the causal effect of 13,206 vaccine-related URLs on vaccination adoption among approximately 233 million U.S. Facebook users, Allen and the research team found that unreported misinformation was 46 times more instrumental in driving vaccine hesitancy over content reported as misinformative. In the second study, Data-Scientist, Sahar Baribi-Bartov, together with his colleagues, investigated who was responsible for spreading misinformation about voting during the 2020 US presidential election on X.
According to the authors, little is known about the spread of fake news by individual users.
In this regard, scientists evaluated supersharers on Twitter, finding that in a sample of 664,391 registered voters in the United States, just 2,107 were responsible for 80% of the fake news shared on X, during the 2020 US presidential election.
In a demographic breakdown of these individuals, the authors found a significant overrepresentation of middle-aged white Republican women residing in three largely conservative states: Arizona, Florida and Texas.
These individuals most often came from neighborhoods with a generally low level of education but with a relatively higher income. Furthermore, the authors found that the huge volume of content promotion by supersharers was generated through manual and persistent retweeting.
One of the key findings of the study is that these supersharers, despite making up a small percentage of users, received higher engagement than other users and were highly connected and influential, reaching approximately 5.2% of registered voters on the platform .
