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
相关论文
共 50 条
  • [1] Offensive Language Detection from Arabic Texts
    Awajan, Arafat A.
    INTELLIGENT COMPUTING, VOL 3, 2024, 2024, 1018 : 77 - 91
  • [2] Towards Accurate Detection of Offensive Language in Online Communication in Arabic
    Alakrot, Azalden
    Murray, Liam
    Nikolov, Nikola S.
    ARABIC COMPUTATIONAL LINGUISTICS, 2018, 142 : 315 - 320
  • [3] Transfer Learning Across Arabic Dialects for Offensive Language Detection
    Husain, Fatemah
    Uzuner, Ozlem
    2022 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP 2022), 2022, : 196 - 205
  • [4] Arabic Offensive Language Classification on Twitter
    Mubarak, Hamdy
    Darwish, Kareem
    SOCIAL INFORMATICS, SOCINFO 2019, 2019, 11864 : 269 - 276
  • [5] A survey on multi-lingual offensive language detection
    Mnassri, Khouloud
    Farahbakhsh, Reza
    Chalehchaleh, Razieh
    Rajapaksha, Praboda
    Jafari, Amir Reza
    Li, Guanlin
    Crespi, Noel
    PEERJ COMPUTER SCIENCE, 2024, 10
  • [6] Offensive Language Detection of Arabic Tweets Using Deep Learning Algorithm
    AlSukhni, Emad
    AlAzzam, Iyad
    Hanandeh, Sereen
    2024 15TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION SYSTEMS, ICICS 2024, 2024,
  • [8] Comparative performance of ensemble machine learning for Arabic cyberbullying and offensive language detection
    Khairy, Marwa
    Mahmoud, Tarek M. M.
    Omar, Ahmed
    Abd El-Hafeez, Tarek
    LANGUAGE RESOURCES AND EVALUATION, 2024, 58 (02) : 695 - 712
  • [9] Detection of Arabic offensive language in social media using machine learning models
    Mousa, Aya
    Shahin, Ismail
    Nassif, Ali Bou
    Elnagar, Ashraf
    INTELLIGENT SYSTEMS WITH APPLICATIONS, 2024, 22
  • [10] A Multi-Platform Arabic News Comment Dataset for Offensive Language Detection
    Chowdhury, Shammur A.
    Mubarak, Hamdy
    Abdelali, Ahmed
    Jung, Soon-gyo
    Jansen, Bernard J.
    Salminen, Joni
    PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2020), 2020, : 6203 - 6212