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<p>This work introduces UstanceBR, a novel social media corpus in the Brazilian Portuguese Twitter/X domain for target-based stance prediction. The corpus comprises 46.9 k labelled stances toward selected target topics, additional publications, and extensive network information about the 11.3 k users who published these stances on social media. In this study, we describe the corpus data and a number of usage examples for both in-domain and cross-target stance prediction based on text and network-related information, which are intended to provide initial baseline results for future studies in the field.</p>

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UstanceBR: a social media language resource for stance prediction

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月8日

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  • Camila Pereira,
  • Matheus Pavan,
  • Sungwon Yoon,
  • Ricelli Ramos,
  • Pablo Costa,
  • Laís Cavalheiro,
  • Ivandré Paraboni

摘要

This work introduces UstanceBR, a novel social media corpus in the Brazilian Portuguese Twitter/X domain for target-based stance prediction. The corpus comprises 46.9 k labelled stances toward selected target topics, additional publications, and extensive network information about the 11.3 k users who published these stances on social media. In this study, we describe the corpus data and a number of usage examples for both in-domain and cross-target stance prediction based on text and network-related information, which are intended to provide initial baseline results for future studies in the field.