Cited by 33Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion MiningSpam and Phishing Detection

Building towards Automated Cyberbullying Detection: A Comparative Analysis

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Al-Harigy, Lulwah M., Al-Nuaim, Hana A., Moradpoor, Naghmeh, Tan, Zhiyuan·2022·Computational Intelligence and Neuroscience

Abstract

The increased use of social media among digitally anonymous users, sharing their thoughts and opinions, can facilitate participation and collaboration. However, this anonymity feature which gives users freedom of speech and allows them to conduct activities without being judged by others can also encourage cyberbullying and hate speech. Predators can hide their identity and reach a wide range of audience anytime and anywhere. According to the detrimental effect of cyberbullying, there is a growing need for cyberbullying detection approaches. In this survey paper, a comparative analysis of the automated cyberbullying techniques from different perspectives is discussed including data annotation, data preprocessing, and feature engineering. In addition, the importance of emojis in expressing emotions as well as their influence on sentiment classification and text comprehension leads us to discuss the role of incorporating emojis in the process of cyberbullying detection and their influence on the detection performance. Furthermore, the different domains for using self-supervised learning (SSL) as an annotation technique for cyberbullying detection are explored.

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Authors
Al-Harigy, L. M., Al-Nuaim, H. A., Moradpoor, N., & Tan, Z.
Affiliations
  • King Abdulaziz University (SA)
  • Edinburgh Napier University (GB)
Corresponding author
Al-Harigy, Lulwah M.
Venue
Computational Intelligence and Neuroscience
Publisher
Wiley
Published
2022-06-25
Volume
2022
Pages
1-20
ISSN
  • 1687-5265 (ISSN-L)
  • 1687-5273
OpenAlex
W4283454882
Cited by
32
References
99
Citations by year
2026: 7 · 2025: 15 · 2024: 3 · 2023: 5 · 2022: 2
FWCI
0.44
Type
journal article
Language
en
Open access
Locations
  • Computational Intelligence and Neuroscience (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Edinburgh Napier Research Repository (Edinburgh Napier University) (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Edinburgh Napier Research Repository (Edinburgh Napier University) (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, social media, online anonymity, hate speech, data annotation, data preprocessing, feature engineering, emojis, sentiment classification, self-supervised learning
MeSH terms
Cyberbullying, Humans, Social Media

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