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Multilingual cyberbullying detection system: Detecting cyberbullying in Arabic content

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Abstract

In the era of Internet and electronic devices bullying shifted its place from schools and backyards into the cyberspace; it is now known as Cyberbullying. Children of the Arab countries are suffering from cyberbullying same as children worldwide. Thus concerns from cyberbullying are elevating. A lot of research is done for the purpose of handling this situation. The current research is focusing on detection and mitigation of cyberbullying; while previous research dealt with the psychological effects of cyberbullying on the victim and the predator. A lot of research proposed solutions for detecting cyberbullying in English language and a few more languages, but none till now covered cyberbullying in Arabic language. Several techniques contribute in cyberbullying detection, mainly Machine Learning (ML) and Natural Language Processing (NLP). This paper presents a solution for detecting and stopping cyberbullying with focus on content written in Arabic Language. Thus the primary results of the system are displayed and discussed.
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Dates and versions

hal-03295349 , version 1 (21-07-2021)

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Batoul Haidar, Maroun Chamoun, Ahmed Serhrouchni. Multilingual cyberbullying detection system: Detecting cyberbullying in Arabic content. 2017 1st Cyber Security in Networking Conference (CSNet), Oct 2017, Rio de Janeiro, Brazil. pp.1-8, ⟨10.1109/CSNET.2017.8242005⟩. ⟨hal-03295349⟩
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