Demarked: A Strategy for Enhanced Abusive Speech Moderation through Counterspeech, Detoxification, and Message Management
Yimam, Seid Muhie, Dementieva, Daryna, Fischer, Tim, Moskovskiy, Daniil, Rizwan, Naquee, Saha, Punyajoy, Roy, Sarthak, Semmann, Martin, Panchenko, Alexander, Biemann, Chris, Mukherjee, Animesh
–arXiv.org Artificial Intelligence
Despite regulations imposed by nations and social media platforms, such as recent EU regulations targeting digital violence, abusive content persists as a significant challenge. Existing approaches primarily rely on binary solutions, such as outright blocking or banning, yet fail to address the complex nature of abusive speech. In this work, we propose a more comprehensive approach called Demarcation scoring abusive speech based on four aspect -- (i) severity scale; (ii) presence of a target; (iii) context scale; (iv) legal scale -- and suggesting more options of actions like detoxification, counter speech generation, blocking, or, as a final measure, human intervention. Through a thorough analysis of abusive speech regulations across diverse jurisdictions, platforms, and research papers we highlight the gap in preventing measures and advocate for tailored proactive steps to combat its multifaceted manifestations. Our work aims to inform future strategies for effectively addressing abusive speech online.
arXiv.org Artificial Intelligence
Jun-27-2024
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