Cyberbullying detection and machine learning: a systematic literature review
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Linguistics and Language,Language and Linguistics
Link
https://link.springer.com/content/pdf/10.1007/s10462-023-10553-w.pdf
Reference109 articles.
1. Agrawal S, Awekar A (2018) Deep learning for detecting cyberbullying across multiple social media platforms. In European Conference on Information Retrieval (pp. 141–153). Springer, Cham
2. Aizenkot D, Kashy-Rosenbaum G (2018) Cyberbullying in WhatsApp classmates’ groups: evaluation of an intervention program implemented in israeli elementary and middle schools. New Media & Society 20(12):4709–4727
3. Akhter MP, Zheng JB, Naqvi IR, Abdelmajeed M, Sadiq MT (2020) Automatic Detection of Offensive Language for Urdu and Roman Urdu. IEEE Access 8:91213–91226.
4. Aldhyani TH, Al-Adhaileh MH, Alsubari SN (2022) Cyberbullying identification system based deep learning algorithms. Electronics 11(20):3273
5. Al-Garadi MA, Hussain MR, Khan N, Murtaza G, Nweke HF, Ali I, …, Gani A (2019) Predicting cyberbullying on social media in the big data era using machine learning algorithms: review of literature and open challenges. IEEE Access 7:70701–70718
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