  Given the rapid growth of Open-Source Software (OSS) projects, ethical
considerations are becoming more important. Past studies focused on specific
ethical issues (e.g., gender bias and fairness in OSS). There is little to no
study on the different types of unethical behavior in OSS projects. We present
the first study of unethical behavior in OSS projects from the stakeholders'
perspective. Our study of 316 GitHub issues provides a taxonomy of 15 types of
unethical behavior guided by six ethical principles (e.g., autonomy).Examples
of new unethical behavior include soft forking (copying a repository without
forking) and self-promotion (promoting a repository without self-identifying as
contributor to the repository). We also identify 18 types of software artifacts
affected by the unethical behavior. The diverse types of unethical behavior
identified in our study (1) call for attentions of developers and researchers
when making contributions in GitHub, and (2) point to future research on
automated detection of unethical behavior in OSS projects. Based on our study,
we propose Etor, an approach that can automatically detect six types of
unethical behavior by using ontological engineering and Semantic Web Rule
Language (SWRL) rules to model GitHub attributes and software artifacts. Our
evaluation on 195,621 GitHub issues (1,765 GitHub repositories) shows that Etor
can automatically detect 548 unethical behavior with 74.8% average true
positive rate. This shows the feasibility of automated detection of unethical
behavior in OSS projects.
