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Register a new userA Large-Scale English Multi-Label Twitter Dataset for Cyberbullying and Online Abuse Detection
مجموعة بيانات Twitter متعددة الملصقات على نطاق واسع للكشف عن الإلكترونية وإساءة الاستخدام عبر الإنترنت
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في هذه الورقة، نقدم مجموعة بيانات جديدة تستند إلى Twitter للكشف عن السيبراني وإساءة استخدام عبر الإنترنت.تضم هذه البيانات التي تضم 62،587 تغريدات، تم الحصول على هذه البيانات من تويتر باستخدام شروط استعلام محددة تهدف إلى استرداد تغريدات مع احتمالات عالية من أشكال مختلفة من البلطجة والمحتوى المسيء، بما في ذلك الإهانة والتصيد والبهجة والسخرية والتهديد والإباحية والاستبعاد.لقد قامنا بتجنيد مجموعة من 17 ملقاة لأداء التعليق التوضيحي بحبائهم الجميلة على مجموعة بيانات كل تغريدة موضحة بمثابة ثلاثة محنوح.جميع الحناحيين لدينا هي مستخدمي التعليم العالي والمتكرر في المدرسة الثانوية.اتفاقية المشتركة بين الخصوصية لأن مجموعة البيانات التي تقاسها Krippendorff's ألفا هي 0.67.تم تأكيد التحليلات التي أجريتها في مجموعة بيانات الموضوعات الإلكترونية المشتركة التي أبلغت عن دراسات أخرى وكشفت علاقات مثيرة للاهتمام بين الطبقات.تم استخدام DataSet لتدريب عدد من نماذج التعلم العميقة المستندة إلى المحولات التي تعود إلى نتائج مثيرة للإعجاب.
In this paper, we introduce a new English Twitter-based dataset for cyberbullying detection and online abuse. Comprising 62,587 tweets, this dataset was sourced from Twitter using specific query terms designed to retrieve tweets with high probabilities of various forms of bullying and offensive content, including insult, trolling, profanity, sarcasm, threat, porn and exclusion. We recruited a pool of 17 annotators to perform fine-grained annotation on the dataset with each tweet annotated by three annotators. All our annotators are high school educated and frequent users of social media. Inter-rater agreement for the dataset as measured by Krippendorff's Alpha is 0.67. Analysis performed on the dataset confirmed common cyberbullying themes reported by other studies and revealed interesting relationships between the classes. The dataset was used to train a number of transformer-based deep learning models returning impressive results.
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