Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing
Clicks: 11
ID: 283106
2024
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.
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Authors | Enrica Troiano; Sofie Labat; Marco Antonio Stranisci; Viviana Patti; Rossana Damiano; Roman Klinger |
Journal | arXiv |
Year | 2024 |
DOI | DOI not found |
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