Cited by 58Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion MiningSpam and Phishing Detection

Arabic Cyberbullying Detection: Using Deep Learning

Haidar, Batoul, Chamoun, Maroun, Serhrouchni, Ahmed·2018·2018 7th International Conference on Computer and Communication Engineering (ICCCE)

Abstract

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.

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Crossref · 10.1109/iccce.2018.8539303

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  • One-hot and TF-IDF approaches are utilized in a few studies in cyberbullying identification, but these techniques perform weaker since they tend to be context insensitive.

    “One-hot [74] and TF-IDF approaches are utilized in a few studies in the identification of cyberbullying. However, these techniques perform weaker since they tend to be context insensitive.”

    From A Review on Deep-Learning-Based Cyberbullying Detection (2023) · cites this paper as [74]

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References 28 · Cited by 58

Authors
Haidar, B., Chamoun, M., & Serhrouchni, A.
Affiliations
  • Saint Joseph University (LB)
  • Télécom Paris (FR)
Venue
2018 7th International Conference on Computer and Communication Engineering (ICCCE)
Publisher
IEEE
Published
2018-09
Pages
284-289
OpenAlex
W2900491514
Cited by
58
References
28
Citations by year
2026: 1 · 2025: 4 · 2024: 14 · 2023: 13 · 2022: 9 · 2021: 8 · 2020: 5 · 2019: 4
FWCI
1.73
Type
conference paper
Language
en
Open access
closed
Locations
  • International Conference on Computer and Communication Engineering (publishedVersion)
  • HAL (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
Keywords
cyberbullying detection, Arabic language, deep learning, online abuse

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