Empathy requires perspective-taking: empathetic responses require a person to reason about what another has experienced and communicate that understanding in language. However, most NLP approaches to empathy do not explicitly model this alignment process. Here, we introduce a new approach to recognizing alignment in empathetic speech, grounded in Appraisal Theory. We introduce a new dataset of over 9.2K span-level annotations of different types of appraisals of a person's experience and over 3K empathetic alignments between a speaker's and observer's speech. Through computational experiments, we show that these appraisals and alignments can be accurately recognized. In experiments in over 9.2M Reddit conversations, we find that appraisals capture meaningful groupings of behavior but that most responses have minimal alignment. However, we find that mental health professionals engage with substantially more empathetic alignment.

翻译：共情需要采取换位思考：共情回应要求个体推理他人经历并利用语言传递这种理解。然而，现有自然语言处理领域的共情研究方法大多未明确建模这一对齐过程。本文提出一种基于评价理论的新方法，用于识别共情话语中的对齐现象。我们构建了一个新数据集，包含超过9200个词级别的经历评价标注，以及3000多个说话者与观察者话语之间的共情对齐标注。通过计算实验，我们证明这些评价与对齐能够被准确识别。在超过920万条Reddit对话实验中，我们发现评价能够有效捕捉行为的有意义分组，但多数回应仅呈现最低程度对齐。值得注意的是，心理健康专业人士展现出显著更高的共情对齐参与度。