跨越边际：交叉性用户对软件的伦理关切
Crossing Margins: Intersectional Users' Ethical Concerns about Software
AI总结：
本研究针对交叉性用户软件伦理关切研究空白，收集700多个交叉性Subreddits的36777条帖子，利用大语言模型等技术分析交叉性声音，构建反馈驱动框架评估软件对交叉性用户需求的满足度。
摘要：
许多现代软件应用因用户价值观与企业优先级的冲突而产生大量伦理问题。拥有多重边缘身份的交叉性社群受这些伦理问题的影响不成比例，既给软件企业带来法律、财务和声誉后果，也给交叉性用户造成现实伤害。历史上，交叉性社群的声音被系统性边缘化和排斥，无法为软件设计贡献独特视角，从而使与软件相关的伦理问题持续存在。本研究旨在填补交叉性用户软件相关视角研究的空白，为软件从业者提供分析软件伦理话语中交叉性声音的方法。我们从700多个交叉性Subreddits收集了36777条讨论软件应用的帖子，利用大语言模型识别这些帖子中的伦理关切，随后应用带有反事实分析的回归模型，研究交叉性身份维度如何塑造不同软件类型中伦理关切表达的放大或抑制情况，并开展时间序列分析，考察关切表达随时间如何随现实世界事件变化。作为社交媒体领域的案例研究，我们进一步展示如何对已识别的伦理关切进行优先级排序，以突出值得开发者及时关注的问题，并通过调查得出的真实值进行验证。这些分析共同构成了一个新兴的反馈驱动框架的基础，用于评估软件系统是否满足交叉性用户的需求。
英文摘要：
Many modern software applications present numerous ethical concerns due to conflicts between users' values and companies' priorities. Intersectional communities, those with multiple marginalized identities, are disproportionately affected by these ethical issues, leading to legal, financial, and reputational consequences for software companies, as well as real-world harm for intersectional users. Historically, the voices of intersectional communities have been systematically marginalized and excluded from contributing their unique perspectives to software design, perpetuating software-related ethical concerns. This work aims to fill the gap in research on intersectional users' software-related perspectives and provide software practitioners with a methodology for analyzing intersectional voices in software ethics discourse. We collected 36,777 posts from over 700 intersectional subreddits discussing software applications and utilized large language models to identify ethical concerns in these posts. We then applied regression models with counterfactual analysis to examine how intersectional identity dimensions shape the amplification or suppression of ethical concern expression across software genres, and conducted a time-series analysis to examine how concern expression varies over time in relation to real-world events. As a case study in the social media domain, we further demonstrate how identified ethical concerns can be prioritized to surface issues warranting timely developer attention, validated against survey-derived ground truth. Together, these analyses form the basis of a nascent feedback-driven framework for assessing whether software systems are meeting the needs of intersectional users.
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。
