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This article introduces ViTOED, a new dataset designed for target-oriented emotion detection in Vietnamese social media, which serves as a resource for advancing natural language processing models in low-resource languages. By evaluating various pre-trained language models on this data, the study highlights specific challenges in span detection and relation extraction that are critical for improving NLP capabilities outside of English.
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ViTOED: A Dataset for Target-Oriented Emotion Detection on Vietnamese Social Media Texts

arXiv2 min read

arXiv:2608.12776v2 Announce Type: replace Abstract: This paper introduces ViTOED, a novel dataset for target-oriented emotion detection in Vietnamese social media texts. The ViTOED comprises 10,985 user comments and 21,244 manually annotated opinion quadruples (source, target, expression, polarity) that follow strict guidelines. The dataset reveals Vietnamese-specific phenomena, such as implicit sources and targets and vocabulary ambiguities, enabling deeper analysis of user emotions toward entities. We propose a baseline using structured sentiment graphs and evaluate various Vietnamese pre-trained language models. The empirical results highlight challenges in span detection and relation extraction and indicate substantial room for model improvement in Vietnamese Target-Oriented Emotion Detection tasks.

Abstract:This paper introduces ViTOED, a novel dataset for target-oriented emotion detection in Vietnamese social media texts. The ViTOED comprises 10,985 user comments and 21,244 manually annotated opinion quadruples (source, target, expression, polarity) that follow strict guidelines. The dataset reveals Vietnamese-specific phenomena, such as implicit sources and targets and vocabulary ambiguities, enabling deeper analysis of user emotions toward entities. We propose a baseline using structured sentiment graphs and evaluate various Vietnamese pre-trained language models. The empirical results highlight challenges in span detection and relation extraction and indicate substantial room for model improvement in Vietnamese Target-Oriented Emotion Detection tasks.

Computation and Language (cs.CL)

arXiv:2608.12776 [cs.CL]

(or arXiv:2608.12776v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.12776 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.1109/MAPR72750.2026.11685817 Focus to learn more DOI(s) linking to related resources

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Full text under the publisher's open licence · 200 words

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