A human-centered systematic literature review of cyberbullying detection algorithms

S Kim, A Razi, G Stringhini, PJ Wisniewski… - Proceedings of the …, 2021 - dl.acm.org
Cyberbullying is a growing problem across social media platforms, inflicting short and long-
lasting effects on victims. To mitigate this problem, research has looked into building …

Informing age-appropriate ai: Examining principles and practices of ai for children

G Wang, J Zhao, M Van Kleek, N Shadbolt - Proceedings of the 2022 …, 2022 - dl.acm.org
AI systems are becoming increasingly pervasive within children's devices, apps, and
services. However, it is not yet well-understood how risks and ethical considerations of AI …

A comparative analysis of machine learning techniques for cyberbullying detection on twitter

A Muneer, SM Fati - Future Internet, 2020 - mdpi.com
The advent of social media, particularly Twitter, raises many issues due to a
misunderstanding regarding the concept of freedom of speech. One of these issues is …

SOLID: A large-scale semi-supervised dataset for offensive language identification

S Rosenthal, P Atanasova, G Karadzhov… - arXiv preprint arXiv …, 2020 - arxiv.org
The widespread use of offensive content in social media has led to an abundance of
research in detecting language such as hate speech, cyberbullying, and cyber-aggression …

When the timeline meets the pipeline: A survey on automated cyberbullying detection

F Elsafoury, S Katsigiannis, Z Pervez, N Ramzan - IEEE access, 2021 - ieeexplore.ieee.org
Web 2.0 helped user-generated platforms to spread widely. Unfortunately, it also allowed for
cyberbullying to spread. Cyberbullying has negative effects that could lead to cases of …

Cyberbullying ends here: Towards robust detection of cyberbullying in social media

M Yao, C Chelmis, DS Zois - The World Wide Web Conference, 2019 - dl.acm.org
The potentially detrimental effects of cyberbullying have led to the development of numerous
automated, data-driven approaches, with emphasis on classification accuracy …

A comprehensive review of cyberbullying-related content classification in online social media

TH Teng, KD Varathan, F Crestani - Expert Systems with Applications, 2024 - Elsevier
The emergence of online social networks (OSN) platforms removes communication barriers
that are essential to human life, catalyzing social networking growth. However, this …

Automatic identification of harmful, aggressive, abusive, and offensive language on the web: A survey of technical biases informed by psychology literature

A Balayn, J Yang, Z Szlavik, A Bozzon - ACM Transactions on Social …, 2021 - dl.acm.org
The automatic detection of conflictual languages (harmful, aggressive, abusive, and
offensive languages) is essential to provide a healthy conversation environment on the Web …

Cyberbullying detection and machine learning: a systematic literature review

V Balakrisnan, M Kaity - Artificial Intelligence Review, 2023 - Springer
The rise in research work focusing on detection of cyberbullying incidents on social media
platforms particularly reflect how dire cyberbullying consequences are, regardless of age …

A study of cyberbullying detection using machine learning techniques

SM Kargutkar, V Chitre - 2020 Fourth International Conference …, 2020 - ieeexplore.ieee.org
Cyberbullying disturbs harassment online, with alarming implications. It exists in different
ways, and is in textual format in most social networks. There is no question that over 1.96 …