Teng, Teoh Hwai and Varathan, Kasturi Dewi and Crestani, Fabio (2024) A comprehensive review of cyberbullying-related content classification in online social media. Expert Systems with Applications, 244. ISSN 0957-4174, DOI https://doi.org/10.1016/j.eswa.2023.122644.
Full text not available from this repository.Abstract
The emergence of online social networks (OSN) platforms removes communication barriers that are essential to human life, catalyzing social networking growth. However, this emergence has given rise to a negative impact when someone abuses the platform to commit cyberbullying activities. Hence, it is crucial to work on automated cyberbullying-related classification to mitigate the societal phenomena in OSN. The research on the automated classification model for cyberbullying was pioneered over the last decade with growing interest among researchers. It is helpful to track its growth over the decades to elucidate the state-of-arts techniques applied in this field. This paper presents a large amount of literature germane to cyberbullying classification from past to present to provide a comprehensive review. A total of 126 papers were reviewed. This paper emphasizes textbased cyberbullying and multi-modal cyberbullying. The review was presented around the machine learning workflow, encompassing four core sections: dataset analysis, pre-processing analysis, feature analysis, and technique analysis. Based on the critical analysis, limitations are addressed along with the future works that can be conducted to fill the gap in previous research. Furthermore, the review also examined the ethical implications associated with the implementation of these techniques. This review paper is expected to assist readers in fully comprehending the current trend, architecture, and techniques applied to the field.
| Item Type: | Article |
|---|---|
| Funders: | Impact Oriented Research Grant of Univer- sity of Malaya [IIRG001A-19SAH] |
| Uncontrolled Keywords: | Online social network; Machine learning workflow; Cyberbullying; Automated classification; Comprehensive review |
| Subjects: | H Social Sciences > HN Social history and conditions. Social problems. Social reform Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Information System |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 21 Jun 2024 03:35 |
| Last Modified: | 21 Jun 2024 03:35 |
| URI: | http://eprints.um.edu.my/id/eprint/44215 |
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