Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media. (arXiv:2205.03296v1 [cs.CL])

Building models to detect vaccine attitudes on social media is challenging
because of the composite, often intricate aspects involved, and the limited
availability of annotated data. Existing approaches have relied heavily on
supervised training that requires abundant annotations and pre-defined aspect
categories. Instead, with the aim of leveraging the large amount of unannotated
data now available on vaccination, we propose a novel semi-supervised approach
for vaccine attitude detection, called VADet. A variational autoencoding
architecture based on language models is employed …

arxiv attitude detection learning media social social media topics vaccine