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

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ID: 283106
2024
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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.
Reference Key
klinger2024dealing Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Enrica Troiano; Sofie Labat; Marco Antonio Stranisci; Viviana Patti; Rossana Damiano; Roman Klinger
Journal arXiv
Year 2024
DOI
DOI not found
URL
http://arxiv.org/abs/2409.19025v1
Keywords
cs.cl

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