This paper addresses the significant issue of offensive language in online communities, detailing its negative effects on both the platforms' reputation and users' mental health. It introduces a novel automatic sentence-level filtering approach that leverages grammatical relationships among words to semantically remove offensive content, offering an efficient alternative to labor-intensive manual filtering. Experiments on a dataset of 11,000 manually filtered YouTube comments demonstrate over 90% agreement with manual methods, proving the practicality and effectiveness of the proposed solution for real-world application.
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Xu, Zhi, and Sencun Zhu. "Filtering offensive language in online communities using grammatical relations." Proceedings of the Seventh Annual Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference. 2010.
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