A Survey of Offensive Language Detection for the Arabic Language

被引:34
|
作者
Husain, Fatemah [1 ]
Uzuner, Ozlem [2 ]
机构
[1] Kuwait Univ, Sabah AlSalem Univ City Alshadadiya, Coll Life Sci, Informat Sci Dept, POB 5969, Safat 13060, Kuwait
[2] George Mason Univ, 4400 Univ Dr,5359 Nguyen Engn Bldg,MSN 1G8, Fairfax, VA 22030 USA
关键词
Offensive language; literature review; natural language processing; Arabic language; machine learning; deep learning; ONLINE COMMUNICATION;
D O I
10.1145/3421504
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:44
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