  Vaccine hesitancy is widespread, despite the government's information
campaigns and the efforts of the World Health Organisation (WHO). Categorising
the topics within vaccine-related narratives is crucial to understand the
concerns expressed in discussions and identify the specific issues that
contribute to vaccine hesitancy. This paper addresses the need for monitoring
and analysing vaccine narratives online by introducing a novel vaccine
narrative classification task, which categorises COVID-19 vaccine claims into
one of seven categories. Following a data augmentation approach, we first
construct a novel dataset for this new classification task, focusing on the
minority classes. We also make use of fact-checker annotated data. The paper
also presents a neural vaccine narrative classifier that achieves an accuracy
of 84% under cross-validation. The classifier is publicly available for
researchers and journalists.
