构建角色扮演情感应对语料库，揭示文本中隐含的应对策略。
Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing
- 基于应对理论，将情绪视为应对事件的策略
- 语料中应对策略可被识别但难度高，人与模型均表现不佳
- 为提升模型理解情绪机制提供新方向，适合情感计算研究者
心理研究关注情绪的内在机制，而计算研究常将其简化为标签，导致二者脱节。本文基于应对理论，将情绪视为应对显著情境的策略，推动情绪与行为在语言中的关联研究。为此提出‘应对识别’任务，并通过角色扮演构建首个相关语料库。实验发现，尽管应对策略在文本中存在，但对人类和自动系统而言识别难度均高。该工作为提升模型捕捉情绪深层机制的能力开辟了新路径。
原文摘要 · Abstract (English)
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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