Vaccine hesitancy is currently recognized by the WHO as a major threat to global health. During the COVID-19 pandemic, there has been a growing interest in the role of social media in the propagation of false information and fringe narratives regarding vaccination. Using a sample of approximately 60 billion tweets, Danish investigators conducted a large-scale analysis of the vaccine discourse on Twitter. They used methods from deep learning and transfer learning to estimate the vaccine sentiments expressed in tweets, then categorize individual-level user attitudes towards vaccines. Drawing on an interaction graph representing mutual interactions between users, They analyzed the interplay between vaccine stances, interaction network, and the information sources shared by users in vaccine-related contexts.
The results show that strongly anti-vaccine users frequently share content from sources of a commercial nature; typically sources that sell alternative health products for profit. An interesting aspect of this finding is that concerns regarding commercial conflicts of interests are often cited as one of the major factors in vaccine hesitancy.
The authors furthermore demonstrate that the debate is highly polarized, in the sense that users with similar stances on vaccination interact preferentially with one another. Extending this insight, the authors provide evidence of an epistemic echo chamber effect, where users are exposed to highly dissimilar sources of vaccine information, enforcing the vaccination stance of their contacts.
The authors concluded that their findings highlight the importance of understanding and addressing vaccine mis- and disinformation in the context in which they are disseminated in social networks.
In the article, the authors comment that their findings paint a picture of the vaccine discourse on Twitter as highly polarized, where users who express similar sentiments regarding vaccinations are more likely to interact with one another, and tend to share contents from similar sources. Focusing on users whose vaccination stances are the positive and negative extremes of the spectrum, we observe relatively disjoint ‘epistemic echo chambers’ which imply that members of the two groups of users rarely interact, and in which users experience highly dissimilar ‘information landscapes’ depending on their stance. Finally, we find that strongly anti-vaccine users much more frequently share information from actors with a vested commercial interest in promoting medical misinformation.
One implication of these findings is that online (medical) misinformation may present an even greater problem than previously thought, because beliefs and behaviors in tightly knit, internally homogeneous communities are more resilient, and provide fertile ground for fringe narratives, while mainstream information is attenuated. Furthermore, such polarization of communities may become self-perpetuating, because individuals avoid those not sharing their views, or because exposure to mainstream information might further entrench fringe viewpoints.