一句话：构建并分析人工标注情感标签的 Gitter 开发者聊天数据集，揭示聊天中独特情感信号及其对维护工具的潜力。
本文关注开发者非正式聊天中的情感表达。已有研究多分析 issue、pull request 等软件制品，对聊天中广泛情感 spectrum 的探索较少。作者构建了一个 Gitter 开发者聊天消息数据集，对消息进行人工标注，涵盖多种情感标签与子标签，并分析消息中包含的信息类型。研究还考察聊天特有的情感信号，并与 GitHub 评论等其他软件交流形式对比。结果显示，聊天中 Approval 和 Fear 表达更少，Curiosity 更多；在讨论编程相关信息（如软件意外行为）时，Confusion 经常出现。该研究展示了挖掘开发者聊天情感以支持软件维护与演化工具的潜力。
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.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{abs-2311-04755,
title = {Towards Understanding Emotions in Informal Developer Interactions: A Gitter Chat Study},
author = {Amirali Sajadi and Kostadin Damevski and Preetha Chatterjee},
booktitle = {FSE},
year = {2023},
doi = {10.1145/3611643.3613084}
}