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arXiv · 2312.06374

UstanceBR: a social media language resource for stance prediction

Camila Pereira·Matheus Pavan·Sungwon Yoon·Ricelli Ramos·Pablo Costa·Lais Cavalheiro·Ivandre Paraboni
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Abstract

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.

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Camila Pereira, Matheus Pavan, Sungwon Yoon, Ricelli Ramos, Pablo Costa, Lais Cavalheiro, Ivandre Paraboni. 2023-12-11. UstanceBR: a social media language resource for stance prediction. https://arxiv.org/abs/2312.06374

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