Exploring the latent social space of COVID-19 Twitter elites

The COVID-19 pandemic brought upon a massive wave of disinformation, exacerbating polarization in the increasingly divided landscape of online discourse. In this context, popular social media users play a major role, as they have the ability to broadcast messages to large audiences, thus influencing public opinion. We make use of publicly available Twitter data to study the behavior of influential users discussing the pandemic, whom we term COVID-19 Twitter elites. We tackle the issue from a network perspective, by considering users as nodes and following relationships as directed edges. The resulting network structure is modeled by embedding the actors in a latent social space, where users closer to one another have a higher probability of forming edges. The results suggest the existence of two distinct communities, which can be interpreted as "generally pro" and "generally against" vaccine mandates. We further focus on a number of exposed users, such as politicians, activists, and news outlets, and discuss their roles in the latent space. Our findings show that the full spectrum of beliefs between the two poles is represented, with more radical users positioned towards the extremes of the space, and more moderate actors in the middle. Our analysis demonstrates how it is possible to provide a nuanced representation of the COVID-19 Twitter ecosystem by only considering follows within the network of elites. This finding corroborates existing evidence on the pervasiveness of echo chamber effects on the platform, and showcases the power of latent space models for studying communication on social media.