Characterizing the nature of trust & misinformation on Twitter

We analyze a dataset from Twitter of misinformation related to the COVID-19 pandemic. We consider this dataset from the intersection of two important but, heretofore, largely separate perspectives: misinformation and trust. We apply existing direct trust measures to the dataset to understand their topology, and to better understand if and how trust relates to spread of misinformation online. We find evidence for small worldness in the misinformation trust network; outsized influence from broker nodes; a digital fingerprint that may indicate when a misinformation trust network is forming; and, a positive relationship between greater trust and spread of misinformation.