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OSS's first extensive investigation of unethical behavior, featuring taxonomy, an ontology-based detection tool (Etor), and an accuracy rate of 74.8%.
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From the viewpoint of stakeholders, this paper offers the first thorough analysis of unethical behavior in open-source software (OSS) initiatives. Our analysis of 316 GitHub problems from 301 repositories reveals 15 different forms of unethical activity, including six situations that haven't been examined before, including self-promotion, soft forking, misinformed licensing alterations, and naming confusion.