Cyberbullying in text content detection: an analytical review

Technological advancements have resulted in an exponential increase in the use of online social networks (OSNs) worldwide. While online social networks provide a great communication medium, they also increase the user's exposure to life-threatening situations such as suicide, eating disorder, c...

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Bibliographic Details
Published in:International journal of computers & applications 2023-09, Vol.45 (9), p.579-586
Main Authors: Azumah, Sylvia W., Elsayed, Nelly, ElSayed, Zag, Ozer, Murat
Format: Article
Language:English
Subjects:
Bullying
Cyberbullying
cybercrime
deep learning
Literature reviews
social media
Social networks
text detection
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Summary:Technological advancements have resulted in an exponential increase in the use of online social networks (OSNs) worldwide. While online social networks provide a great communication medium, they also increase the user's exposure to life-threatening situations such as suicide, eating disorder, cybercrime, compulsive behavior, anxiety, and depression. To tackle the issue of cyberbullying, most existing literature focuses on developing approaches to identifying factors and understanding the textual factors associated with cyberbullying. While most of these approaches have brought great success in cyberbullying research, data availability needed to develop model detection remains a challenge in the research space. This paper conducts a comprehensive literature review to provide an understanding of cyberbullying detection.
ISSN:1206-212X
1925-7074
DOI:10.1080/1206212X.2023.2256048