一句话：通过道德基础理论分析 GitHub issue 讨论，初步发现道德原则与毒性言论存在关联。
开源软件（OSS）项目中的毒性语言会阻碍协作与包容，尤其可能使弱势群体贡献者流失；现有基于机器学习的毒性检测工具虽有效果，但其设计缺乏对 OSS 讨论中毒性本质与触发因素的理解。本文采用道德基础理论（MFT），分析 GitHub issue 线程中的毒性交流，识别文本中表现出的五类道德原则，并探索它们与毒性行为之间的潜在关联。初步结果表明，OSS 交流中的道德原则与毒性评论可能存在联系，且每类道德原则至少与一种毒性类型相关。作者认为，MFT 在毒性检测中的潜力值得进一步研究。
To foster collaboration and inclusivity in Open Source Software (OSS) projects, it is crucial to understand and detect patterns of toxic language that may drive contributors away, especially those from underrepresented communities. Although machine learning-based toxicity detection tools trained on domain-specific data have shown promise, their design lacks an understanding of the unique nature and triggers of toxicity in OSS discussions, highlighting the need for further investigation. In this study, we employ Moral Foundations Theory to examine the relationship between moral principles and toxicity in OSS. Specifically, we analyze toxic communications in GitHub issue threads to identify and understand five types of moral principles exhibited in text, and explore their potential association with toxic behavior. Our preliminary findings suggest a possible link between moral principles and toxic comments in OSS communications, with each moral principle associated with at least one type of toxicity. The potential of MFT in toxicity detection warrants further investigation.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{EhsaniRC23,
title = {Exploring Moral Principles Exhibited in OSS: A Case Study on GitHub Heated Issues},
author = {Ramtin Ehsani and Rezvaneh Rezapour and Preetha Chatterjee},
booktitle = {FSE},
year = {2023},
doi = {10.1145/3611643.3613077}
}