Dealing with controversy : an emotion and coping strategy corpus based on role playing
- Author
- Enrica Troiano, Sofie Labat (UGent) , Marco Antonio Stranisci, Rossana Damiano, Viviana Patti and Roman Klinger
- Organization
- Project
- Abstract
- There is a mismatch between psychological and computational studies on emotions. Psychological research aims at explaining and documenting internal mechanisms of these phenomena, while computational work often simplifies them into labels. Many emotion fundamentals remain under-explored in natural language processing, particularly how emotions develop and how people cope with them. To help reduce this gap, we follow theories on coping, and treat emotions as strategies to cope with salient situations (i.e., how people deal with emotion-eliciting events). This approach allows us to investigate the link between emotions and behavior, which also emerges in language. We introduce the task of coping identification, together with a corpus to do so, constructed via role-playing. We find that coping strategies realize in text even though they are challenging to recognize, both for humans and automatic systems trained and prompted on the same task. We thus open up a promising research direction to enhance the capability of models to better capture emotion mechanisms from text.
- Keywords
- coping, emotion analysis, natural language processing, role-playing, lt3
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01JD2E04BP3FB09984PE3BQVFY
- MLA
- Troiano, Enrica, et al. “Dealing with Controversy : An Emotion and Coping Strategy Corpus Based on Role Playing.” Findings of the Association for Computational Linguistics : EMNLP 2024, edited by Yaser Al-Onaizan et al., Association for Computational Linguistics (ACL), 2024, pp. 1634–58, doi:10.18653/v1/2024.findings-emnlp.89.
- APA
- Troiano, E., Labat, S., Stranisci, M. A., Damiano, R., Patti, V., & Klinger, R. (2024). Dealing with controversy : an emotion and coping strategy corpus based on role playing. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), Findings of the Association for Computational Linguistics : EMNLP 2024 (pp. 1634–1658). https://doi.org/10.18653/v1/2024.findings-emnlp.89
- Chicago author-date
- Troiano, Enrica, Sofie Labat, Marco Antonio Stranisci, Rossana Damiano, Viviana Patti, and Roman Klinger. 2024. “Dealing with Controversy : An Emotion and Coping Strategy Corpus Based on Role Playing.” In Findings of the Association for Computational Linguistics : EMNLP 2024, edited by Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen, 1634–58. Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.findings-emnlp.89.
- Chicago author-date (all authors)
- Troiano, Enrica, Sofie Labat, Marco Antonio Stranisci, Rossana Damiano, Viviana Patti, and Roman Klinger. 2024. “Dealing with Controversy : An Emotion and Coping Strategy Corpus Based on Role Playing.” In Findings of the Association for Computational Linguistics : EMNLP 2024, ed by. Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen, 1634–1658. Association for Computational Linguistics (ACL). doi:10.18653/v1/2024.findings-emnlp.89.
- Vancouver
- 1.Troiano E, Labat S, Stranisci MA, Damiano R, Patti V, Klinger R. Dealing with controversy : an emotion and coping strategy corpus based on role playing. In: Al-Onaizan Y, Bansal M, Chen Y-N, editors. Findings of the Association for Computational Linguistics : EMNLP 2024. Association for Computational Linguistics (ACL); 2024. p. 1634–58.
- IEEE
- [1]E. Troiano, S. Labat, M. A. Stranisci, R. Damiano, V. Patti, and R. Klinger, “Dealing with controversy : an emotion and coping strategy corpus based on role playing,” in Findings of the Association for Computational Linguistics : EMNLP 2024, Miami, Florida, USA, 2024, pp. 1634–1658.
@inproceedings{01JD2E04BP3FB09984PE3BQVFY,
abstract = {{There is a mismatch between psychological and computational studies on emotions. Psychological research aims at explaining and documenting internal mechanisms of these phenomena, while computational work often simplifies them into labels. Many emotion fundamentals remain under-explored in natural language processing, particularly how emotions develop and how people cope with them. To help reduce this gap, we follow theories on coping, and treat emotions as strategies to cope with salient situations (i.e., how people deal with emotion-eliciting events). This approach allows us to investigate the link between emotions and behavior, which also emerges in language. We introduce the task of coping identification, together with a corpus to do so, constructed via role-playing. We find that coping strategies realize in text even though they are challenging to recognize, both for humans and automatic systems trained and prompted on the same task. We thus open up a promising research direction to enhance the capability of models to better capture emotion mechanisms from text.}},
author = {{Troiano, Enrica and Labat, Sofie and Stranisci, Marco Antonio and Damiano, Rossana and Patti, Viviana and Klinger, Roman}},
booktitle = {{Findings of the Association for Computational Linguistics : EMNLP 2024}},
editor = {{Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung}},
keywords = {{coping,emotion analysis,natural language processing,role-playing,lt3}},
language = {{eng}},
location = {{Miami, Florida, USA}},
pages = {{1634--1658}},
publisher = {{Association for Computational Linguistics (ACL)}},
title = {{Dealing with controversy : an emotion and coping strategy corpus based on role playing}},
url = {{http://doi.org/10.18653/v1/2024.findings-emnlp.89}},
year = {{2024}},
}
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