自动化终身仇恨言论检测:跨领域适应的当前挑战

Cendra Devayana Putra, Hei-Chia Wang
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引用次数: 0

摘要

仇恨言论是人们在社交网站上发现的一种呈现冒犯性内容的现象。识别和减少不适当的内容对于防止和减少仇恨言论至关重要。本文通过调查几个可信数据库中的27篇相关论文,强调了可能的仇恨言论数据集的多样性,并在四个领域提出了挑战。研究结果指出了未来的系统开发方向,以跟踪各种在线社交平台和领域上的不良内容随时间的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automate Lifelong Hate Speech Detection: Current Challenge In Cross-Domain Adaption
Hate speech is a phenomenon which presents offensive content that people may find on social networking sites. Recognizing and reducing inappropriate content is critical for preventing and reducing hate speech. This article highlights the diversity of possible hate speech datasets and developed challenges in four domains by investigating 27 related papers in several trusted databases. The findings point to future system development directions to trace objectionable content transformations over time on various online social platforms and domains.
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