  This work introduces UstanceBR, a multimodal corpus in the Brazilian
Portuguese Twitter domain for target-based stance prediction. The corpus
comprises 86.8 k labelled stances towards selected target topics, and extensive
network information about the users who published these stances on social
media. In this article we describe the corpus multimodal data, and a number of
usage examples in both in-domain and zero-shot stance prediction based on text-
and network-related information, which are intended to provide initial baseline
results for future studies in the field.
