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    <abstract>Stance detection is the computational task of determining the attitude (e.g., for, against, neutral) expressed in text toward a specific target topic. In its more conventional form, the task focuses on isolated, context-free input utterances. Conversational stance detection, by contrast, analyzes messages embedded within dialogue threads, enabling the interpretation of responses in relation to preceding discourse, and takes into account a greater variety of stance relations (e.g., support, deny, query, comment, etc.). Despite growing research attention, however, conversational stance detection remains relatively under-resourced and largely limited to the English language. To address these gaps, this study introduces CoSt-BR, a new corpus for conversational stance detection composed of a large set of annotated Reddit discussions in Brazilian Portuguese. In addition, the paper also reports benchmark results obtained using various computational methods, including supervised and prompt-based strategies, applied to the corpus data, providing baseline references for future research in this area.</abstract>
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%0 Conference Proceedings
%T CoSt-BR: A Language Resource for Conversational Stance Detection
%A da Fonseca, Felipe Penhorate Carvalho
%A Paraboni, Ivandre
%A Digiampietri, Luciano Antônio
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F da-fonseca-etal-2026-cost
%X Stance detection is the computational task of determining the attitude (e.g., for, against, neutral) expressed in text toward a specific target topic. In its more conventional form, the task focuses on isolated, context-free input utterances. Conversational stance detection, by contrast, analyzes messages embedded within dialogue threads, enabling the interpretation of responses in relation to preceding discourse, and takes into account a greater variety of stance relations (e.g., support, deny, query, comment, etc.). Despite growing research attention, however, conversational stance detection remains relatively under-resourced and largely limited to the English language. To address these gaps, this study introduces CoSt-BR, a new corpus for conversational stance detection composed of a large set of annotated Reddit discussions in Brazilian Portuguese. In addition, the paper also reports benchmark results obtained using various computational methods, including supervised and prompt-based strategies, applied to the corpus data, providing baseline references for future research in this area.
%R 10.63317/3g3kx7kbdrkp
%U https://aclanthology.org/2026.lrec-1.645/
%U https://doi.org/10.63317/3g3kx7kbdrkp
%P 8141-8146

Markdown (Informal)

[CoSt-BR: A Language Resource for Conversational Stance Detection](https://aclanthology.org/2026.lrec-1.645/) (da Fonseca et al., LREC 2026)

• CoSt-BR: A Language Resource for Conversational Stance Detection (da Fonseca et al., LREC 2026)

ACL

• Felipe Penhorate Carvalho da Fonseca, Ivandre Paraboni, and Luciano Antônio Digiampietri. 2026. CoSt-BR: A Language Resource for Conversational Stance Detection. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 8141–8146, Palma de Mallorca, Spain. ELRA Language Resource Association.