Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing
Contributo in Atti di convegno
Data di Pubblicazione:
2024
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.
Tipologia CRIS:
04A-Conference paper in volume
Keywords:
coping, microaggressions, natural language processing, emotions
Elenco autori:
Enrica Troiano, Sofie Labat, Marco Antonio Stranisci, Rossana Damiano, Viviana Patti, Roman Klinger
Link alla scheda completa:
Link al Full Text:
Titolo del libro:
The 2024 Conference on Empirical Methods in Natural Language Processing: Findings of EMNLP 2024