Vaccine-hesitant people misperceive the social norm of vaccination.

Vaccine hesitancy is one of the main threats to global health, as became clear once more during the COVID-19 pandemic. Vaccination campaigns could benefit from appeals to social norms to promote vaccination, but without awareness of the social norm in place any intervention relying on social norms may backfire. We present a two-step approach of social norm diagnosis and intervention that identifies both whether a vaccination norm exists or develops over time and corrects misperceptions. In two studies (N=887 and N=412) conducted in Rome, Italy from June to August 2021 (during the first COVID-19 vaccination campaign), we show that vaccine-hesitant people strongly underestimated vaccine acceptance rates for COVID-19 despite increases in region-wide vaccination rates. This suggests a false consensus bias on the social norm of vaccination. We presented a subgroup of vaccine-hesitant people with the accurate vaccine acceptance rates (both planned uptake and vaccine approval) and tested if this social information would lower their vaccine hesitancy. We do not find clear effects, most likely because of the introduction of the COVID-19 health certificate (the "green pass") that was implemented during our data collection. The green pass reduced both misperceptions in the social norm and vaccine hesitancy, thus undermining our treatment effect. We conclude that to alleviate misperceptions on the social norm of vaccination in early stages of the vaccination campaign governments and media should report not just the current vaccination rate, but also about vaccination intentions and approval.

The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing.

Online platforms play a relevant role in the creation and diffusion of false or misleading news. Concerningly, the COVID-19 pandemic is shaping a communication network which reflects the emergence of collective attention towards a topic that rapidly gained universal interest. Here, we characterize the dynamics of this network on Twitter, analysing how unreliable content distributes among its users. We find that a minority of accounts is responsible for the majority of the misinformation circulating online, and identify two categories of users: a few active ones, playing the role of 'creators', and a majority playing the role of 'consumers'. The relative proportion of these groups (approx. 14% creators-86% consumers) appears stable over time: consumers are mostly exposed to the opinions of a vocal minority of creators (which are the origin of 82% of fake content in our data), that could be mistakenly understood as representative of the majority of users. The corresponding pressure from a perceived majority is identified as a potential driver of the ongoing COVID-19 infodemic.