Arabic Cyberbullying Detection: Using Deep Learning

被引:0
|
作者
Haidar, Batoul [1 ]
Chamoun, Maroun [1 ]
Serhrouchni, Ahmed [2 ]
机构
[1] Univ St Joseph, Beirut, Lebanon
[2] Telecom ParisTech, Paris, France
关键词
Arabic Language; Cyberbullying Detection; Deep Learning; Natural Language Processing; Neural Networks; NETWORKS;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
As much as internet and smart devices are taking a big role in the lives of children and adolescents, also the threat of Cyberbullying on the lives and wellbeing of those youngsters is rising. The threat of cyberbullying is acknowledged around the world generally and in the Arabic areas specifically. A lot of research is done for finding automated solutions for cyberbullying detection in several languages, but not much has been done for Arabic Language. At the other hand, a lot of interest is invested in Deep Learning techniques, where Deep Learning has been applied in several areas and showed vast success. Thus this paper proposes a solution that employs Deep Learning methods in the process of Arabic Cyberbullying Detection. Specifically a Feed Forward Neural Network is trained on an Arabic Dataset for the purpose of cyberbullying detection.
引用
收藏
页码:284 / 289
页数:6
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