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Register a new userDetecting Community Sensitive Norm Violations in Online Conversations
الكشف عن انتهاكات المعايير الحساسة للمجتمع في المحادثات عبر الإنترنت
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تنشئ المنصات والمجتمعات عبر الإنترنت معاييرها التي تحكم السلوك المقبول داخل المجتمع.ركز جهد كبير في NLP على تحديد السلوكيات غير المقبولة، وفي الآونة الأخيرة، على التنبؤ بها قبل حدوثها.ومع ذلك، ركزت هذه الجهود إلى حد كبير على السمية باعتبارها الشكل الوحيد لانتهاك المعايير المجتمعية.وقد أغفل هذا التركيز على مجموعة أكبر من القواعد التي يفرضها المشرفون.هنا، نقدم مجموعة بيانات جديدة تركز على طيف أكثر اكتمالا من معايير المجتمع وانتهاكاتها في سياقات المجتمع المحلى والعالمي المحلي.نقدم سلسلة من النماذج التي تستخدم هذه البيانات لتطوير اكتشاف انتهاك المعايير والتحسس المجتمعي، مما يدل على أن هذه التغييرات تعطي أداء عال.
Online platforms and communities establish their own norms that govern what behavior is acceptable within the community. Substantial effort in NLP has focused on identifying unacceptable behaviors and, recently, on forecasting them before they occur. However, these efforts have largely focused on toxicity as the sole form of community norm violation. Such focus has overlooked the much larger set of rules that moderators enforce. Here, we introduce a new dataset focusing on a more complete spectrum of community norms and their violations in the local conversational and global community contexts. We introduce a series of models that use this data to develop context- and community-sensitive norm violation detection, showing that these changes give high performance.
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