Emotions play a significant role in teamwork and collaborative activities like software development. While researchers have analyzed developer emotions in various software artifacts (e.g., issues, pull requests), few studies have focused on understanding the broad spectrum of emotions expressed in chats. As one of the most widely used means of communication, chats contain valuable information in the form of informal conversations, such as negative perspectives about adopting a tool. In this paper, we present a dataset of developer chat messages manually annotated with a wide range of emotion labels (and sub-labels), and analyze the type of information present in those messages. We also investigate the unique signals of emotions specific to chats and distinguish them from other forms of software communication. Our findings suggest that chats have fewer expressions of Approval and Fear but more expressions of Curiosity compared to GitHub comments. We also notice that Confusion is frequently observed when discussing programming-related information such as unexpected software behavior. Overall, our study highlights the potential of mining emotions in developer chats for supporting software maintenance and evolution tools.

翻译：情感在团队协作及软件开发等合作活动中扮演着重要角色。尽管研究人员已在各类软件制品（如问题报告、拉取请求）中分析了开发者情感，但鲜有研究聚焦于理解聊天中广泛表达的情感谱系。作为最常用的沟通方式之一，聊天以非正式对话形式蕴含宝贵信息，例如对采用某工具的负面看法。本文呈现了一个开发者聊天消息数据集，该数据集经过人工标注，包含丰富的情感标签（及子标签），并分析了这些消息中蕴含的信息类型。我们还探究了聊天中特有的情感信号，并将其与其他软件沟通形式进行区分。研究发现，与GitHub评论相比，聊天中“赞同”与“恐惧”的表达较少，而“好奇”的表达更多。同时我们注意到，在讨论编程相关信息（如意外软件行为）时，“困惑”频繁出现。总体而言，本研究凸显了挖掘开发者聊天情感在支持软件维护与演化工具方面的潜力。