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Register a new userTo Block or not to Block: Experiments with Machine Learning for News Comment Moderation
لحظر أو عدم حظره: تجارب مع التعلم الآلي للإعلام التعليق الأخبار
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اليوم، تتضمن المؤسسات الإعلامية الأخبار بانتظام مع القراء من خلال تمكينهم من التعليق على المقالات الإخبارية.هذا يخلق الحاجة إلى التعليق الاعتدال وإزالة التعليقات غير المسموح بها - وهي مهمة تستغرق وقتا طويلا في كثير من الأحيان أداءها المشرفين البشري.في هذه الورقة، نقترب من مشكلة اعتدال تعليق الأخبار التلقائي كتصنيف للتعليقات في الفئات المحظورة وغير المحظورة.نبني مجموعة بيانات جديدة من تعليقات باللغة الإنجليزية المشروح، وتجربة نقل متصل بالتعليق، وتقييم العديد من نماذج التعلم الآلي على مجموعات بيانات الأخبار الكرواتية والإستونية.اسم الفريق: SuperAdmin؛التحدي: اكتشاف التعليقات المحظورة؛أدوات / نماذج: Brrosloen Bert، أرقى بيرت، 24sata تعليق DataSet، Ekspress تعليق DataSet.
Today, news media organizations regularly engage with readers by enabling them to comment on news articles. This creates the need for comment moderation and removal of disallowed comments -- a time-consuming task often performed by human moderators. In this paper we approach the problem of automatic news comment moderation as classification of comments into blocked and not blocked categories. We construct a novel dataset of annotated English comments, experiment with cross-lingual transfer of comment labels and evaluate several machine learning models on datasets of Croatian and Estonian news comments. Team name: SuperAdmin; Challenge: Detection of blocked comments; Tools/models: CroSloEn BERT, FinEst BERT, 24Sata comment dataset, Ekspress comment dataset.
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