COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities

Yuqiang Xie, Yue Hu, Wei Peng, Guanqun Bi, Luxi Xing


Abstract
Motivations, emotions, and actions are inter-related essential factors in human activities. While motivations and emotions have long been considered at the core of exploring how people take actions in human activities, there has been relatively little research supporting analyzing the relationship between human mental states and actions. We present the first study that investigates the viability of modeling motivations, emotions, and actions in language-based human activities, named COMMA (Cognitive Framework of Human Activities). Guided by COMMA, we define three natural language processing tasks (emotion understanding, motivation understanding and conditioned action generation), and build a challenging dataset Hail through automatically extracting samples from Story Commonsense. Experimental results on NLP applications prove the effectiveness of modeling the relationship. Furthermore, our models inspired by COMMA can better reveal the essential relationship among motivations, emotions and actions than existing methods.
Anthology ID:
2022.coling-1.15
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
163–177
Language:
URL:
https://aclanthology.org/2022.coling-1.15
DOI:
Bibkey:
Cite (ACL):
Yuqiang Xie, Yue Hu, Wei Peng, Guanqun Bi, and Luxi Xing. 2022. COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities. In Proceedings of the 29th International Conference on Computational Linguistics, pages 163–177, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities (Xie et al., COLING 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.coling-1.15.pdf
Code
 indexfziq/comma
Data
Story Commonsense