The use of offensive language in user-generated content is a serious problem that needs to be addressed with the latest technology. The field of Natural Language Processing (NLP) can support the automatic detection of offensive language. In this survey, we review previous NLP studies that cover Arabic offensive language detection. This survey investigates the state-of-the-art in offensive language detection for the Arabic language, providing a structured overview of previous approaches, including core techniques, tools, resources, methods, and main features used. This work also discusses the limitations and gaps of the previous studies. Findings from this survey emphasize the importance of investing further effort in detecting Arabic offensive language, including the development of benchmark resources and the invention of novel preprocessing and feature extraction techniques.

中文翻译：

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阿拉伯语攻击性语言检测调查

在用户生成的内容中使用攻击性语言是一个严重的问题，需要使用最新技术来解决。自然语言处理（NLP）领域可以支持攻击性语言的自动检测。在本次调查中，我们回顾了之前涵盖阿拉伯语攻击性语言检测的 NLP 研究。本调查调查了阿拉伯语攻击性语言检测的最新技术，提供了对以前方法的结构化概述，包括核心技术、工具、资源、方法和使用的主要特征。这项工作还讨论了以前研究的局限性和差距。这项调查的结果强调了进一步努力检测阿拉伯语攻击性语言的重要性，