Interpretable Relevant Emotion Ranking with Event-Driven Attention

Yang Yang, Deyu Zhou, Yulan He, Meng Zhang


Abstract
Multiple emotions with different intensities are often evoked by events described in documents. Oftentimes, such event information is hidden and needs to be discovered from texts. Unveiling the hidden event information can help to understand how the emotions are evoked and provide explainable results. However, existing studies often ignore the latent event information. In this paper, we proposed a novel interpretable relevant emotion ranking model with the event information incorporated into a deep learning architecture using the event-driven attentions. Moreover, corpus-level event embeddings and document-level event distributions are introduced respectively to consider the global events in corpus and the document-specific events simultaneously. Experimental results on three real-world corpora show that the proposed approach performs remarkably better than the state-of-the-art emotion detection approaches and multi-label approaches. Moreover, interpretable results can be obtained to shed light on the events which trigger certain emotions.
Anthology ID:
D19-1017
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
177–187
Language:
URL:
https://aclanthology.org/D19-1017
DOI:
10.18653/v1/D19-1017
Bibkey:
Cite (ACL):
Yang Yang, Deyu Zhou, Yulan He, and Meng Zhang. 2019. Interpretable Relevant Emotion Ranking with Event-Driven Attention. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 177–187, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Interpretable Relevant Emotion Ranking with Event-Driven Attention (Yang et al., EMNLP-IJCNLP 2019)
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PDF:
https://aclanthology.org/D19-1017.pdf