تقرير
Author Profiling for Hate Speech Detection
| العنوان: | Author Profiling for Hate Speech Detection |
|---|---|
| المؤلفون: | Mishra, Pushkar, Del Tredici, Marco, Yannakoudakis, Helen, Shutova, Ekaterina |
| سنة النشر: | 2019 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | The rapid growth of social media in recent years has fed into some highly undesirable phenomena such as proliferation of abusive and offensive language on the Internet. Previous research suggests that such hateful content tends to come from users who share a set of common stereotypes and form communities around them. The current state-of-the-art approaches to hate speech detection are oblivious to user and community information and rely entirely on textual (i.e., lexical and semantic) cues. In this paper, we propose a novel approach to this problem that incorporates community-based profiling features of Twitter users. Experimenting with a dataset of 16k tweets, we show that our methods significantly outperform the current state of the art in hate speech detection. Further, we conduct a qualitative analysis of model characteristics. We release our code, pre-trained models and all the resources used in the public domain. Comment: Proceedings of the 27th International Conference on Computational Linguistics (COLING) 2018. arXiv admin note: text overlap with arXiv:1809.00378 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1902.06734 |
| رقم الأكسشن: | edsarx.1902.06734 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |