Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing

Fuente: arXiv
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Autores principales: Troiano, Enrica, Labat, Sofie, Stranisci, Marco Antonio, Patti, Viviana, Damiano, Rossana, Klinger, Roman
Formato: Preprint
Publicado: 2024
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author Troiano, Enrica
Labat, Sofie
Stranisci, Marco Antonio
Patti, Viviana
Damiano, Rossana
Klinger, Roman
author_facet Troiano, Enrica
Labat, Sofie
Stranisci, Marco Antonio
Patti, Viviana
Damiano, Rossana
Klinger, Roman
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2409_19025
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing
Troiano, Enrica
Labat, Sofie
Stranisci, Marco Antonio
Patti, Viviana
Damiano, Rossana
Klinger, Roman
Computation and Language
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.
title Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing
topic Computation and Language
url https://arxiv.org/abs/2409.19025