Year: 2026
Type: article
Abstract: This work introduces UstanceBR, a novel social media corpus in the Brazilian Portuguese Twitter/X 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 data, and a number of usage examples in 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.
Institution: Universidade de São Paulo
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
OpenAlex ID: W7118275099