Emotional Intensity Estimation based on Writer’s Personality
Haruya Suzuki, Sora Tarumoto, Tomoyuki Kajiwara, Takashi Ninomiya, Yuta Nakashima, Hajime Nagahara
Abstract
We propose a method for personalized emotional intensity estimation based on a writer’s personality test for Japanese SNS posts. Existing emotion analysis models are difficult to accurately estimate the writer’s subjective emotions behind the text. We personalize the emotion analysis using not only the text but also the writer’s personality information. Experimental results show that personality information improves the performance of emotional intensity estimation. Furthermore, a hybrid model combining the existing personalized method with ours achieved state-of-the-art performance.- Anthology ID:
- 2022.aacl-srw.1
- Volume:
- Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Student Research Workshop
- Month:
- November
- Year:
- 2022
- Address:
- Online
- Venues:
- AACL | IJCNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1–7
- Language:
- URL:
- https://aclanthology.org/2022.aacl-srw.1
- DOI:
- Cite (ACL):
- Haruya Suzuki, Sora Tarumoto, Tomoyuki Kajiwara, Takashi Ninomiya, Yuta Nakashima, and Hajime Nagahara. 2022. Emotional Intensity Estimation based on Writer’s Personality. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Student Research Workshop, pages 1–7, Online. Association for Computational Linguistics.
- Cite (Informal):
- Emotional Intensity Estimation based on Writer’s Personality (Suzuki et al., AACL-IJCNLP 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.aacl-srw.1.pdf