一句话：提出自动识别并缓解开源开发者文本交流中有毒沟通的博士研究计划，并分析其人口差异与项目影响。
该博士论文计划关注自由/开源软件（FOSS）开发者交流中的有毒与不健康对话。此类沟通可能降低项目专业和谐与生产力，并加剧对新人、女性及边缘群体参与者的不成比例影响，成为多样、公平与包容的障碍。作者拟在软件工程领域构建自动毒性检测器，识别不同人口群体对毒性的理解差异，并分析毒性对开源软件项目结果的影响。摘要未给出已完成的评估结果，而是提出以自动识别与缓解开发者文本交互中的毒性为核心目标的研究路线。
Toxic and unhealthy conversations during the developer’s communication may reduce the professional harmony and productivity of Free and Open Source Software (FOSS) projects. For example, toxic code review comments may raise pushback from an author to complete suggested changes. A toxic communication with another person may hamper future communication and collaboration. Research also suggests that toxicity disproportionately impacts newcomers, women, and other participants from marginalized groups. Therefore, toxicity is a barrier to promote diversity, equity, and inclusion. Since the occurrence of toxic communications is not uncommon among FOSS communities and such communications may have serious repercussions, the primary objective of my proposed dissertation is to automatically identify and mitigate toxicity during developers’ textual interactions. On this goal, I aim to: i) build an automated toxicity detector for Software Engineering (SE) domain, ii) identify the notion of toxicity across demographics, and iii) analyze the impacts of toxicity on the outcomes of Open Source Software (OSS) projects.
DOI 原文 ·
@inproceedings{paperbot7283,
title = {Identification and Mitigation of Toxic Communications Among Open Source Software Developers},
author = {Jaydeb Sarker},
booktitle = {ASE},
year = {2022},
doi = {10.1145/3551349.3559570}
}