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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 issues 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 starting point to address their ethical concerns. We aggregated and analyzed the intersectional users' ethical concerns over time and developed a prioritization method to identify critical concerns. To achieve this, we collected posts from over 700 intersectional subreddits discussing software applications, utilized deep learning to identify ethical concerns in these posts, and employed state-of-the-art techniques to analyze their content in relation to time and priority. Our findings revealed that intersectional communities report \textit{critical} complaints related to cyberbullying, inappropriate content, and discrimination, highlighting significant flaws in modern software, particularly for intersectional users. Based on these findings, we discuss how to better address the ethical concerns of intersectional users in software development. |
