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A Japanese Dataset for Aspect-based Sentiment Polarity Classification and Emotion Intensity Estimation

Kenta Hanafusa Kota Manabe Yuki Maeda Daisuke Maekawa Tomoyuki Kajiwara Hideaki Hayashi Yuta Nakashima Hajime Nagahara
2026 · International Conference on Language Resources and Evaluation · pp. 8076-8084 · 0 citations · 29 references
Computer Science

TL;DR

A Japanese dataset for Aspect-based Sentiment Analysis (ABSA), annotated with both sentiment polarity and the emotional intensities for Plutchik’s eight emotions is constructed and it is demonstrated that multi-task learning, utilizing both word and sentence levels, can improve performance on difficult-to-estimate subjective emotions.

DOI Semantic Scholar
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