用于纠纷解决的情绪感知智能体
Emotionally-Aware Agents for Dispute Resolution
AI总结：
本研究聚焦纠纷解决场景，利用大规模买卖纠纷对话语料探究情绪表达对结果的影响，证实大语言模型在情绪强度标注上优于传统方法，为情绪与冲突的相关理论提供支撑，也为研发情绪感知纠纷管理智能体提供了依据。
摘要：
在冲突中，人们借助情绪表达来影响对方的想法、感受与行为。本文探究在纠纷解决场景下，自动文本情绪识别能否为理解这种影响提供洞见。已有研究证实此类方法在谈判中具备应用潜力，但纠纷会引发更强烈的情绪与不同的社会互动过程。我们利用大规模买卖双方纠纷对话语料库，研究情绪表达如何影响主观与客观结果。我们进一步证明，在情绪强度标注任务中，大语言模型的解释力远优于此前的方法，且与人类标注者的决策匹配度更高。研究结果验证了现有关于情绪表达如何作用于冲突升级与化解的理论模型，同时表明基于智能体的系统可通过识别并潜在缓解情绪升级，在纠纷管理中发挥作用。
英文摘要：
In conflict, people use emotional expressions to shape their counterparts' thoughts, feelings, and actions. This paper explores whether automatic text emotion recognition offers insight into this influence in the context of dispute resolution. Prior work has shown the promise of such methods in negotiations; however, disputes evoke stronger emotions and different social processes. We use a large corpus of buyer-seller dispute dialogues to investigate how emotional expressions shape subjective and objective outcomes. We further demonstrate that large-language models yield considerably greater explanatory power than previous methods for emotion intensity annotation and better match the decisions of human annotators. Findings support existing theoretical models for how emotional expressions contribute to conflict escalation and resolution and suggest that agent-based systems could be useful in managing disputes by recognizing and potentially mitigating emotional escalation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
