The emergence of online social networks (OSN) platforms removes communication barriers
that are essential to human life, catalyzing social networking growth. However, this …

Information and Communication Technologies fueled social networking and facilitated
communication. However, cyberbullying on the platform had detrimental ramifications. The …

Despite significant advancements in Artificial Intelligence (AI) and Large Language Models
(LLMs), detecting and mitigating bias remains a critical challenge, particularly on social …

This paper applies Natural Language Processing (NLP) methods to analyze the exposure to
trauma experienced by witnesses in international criminal tribunals when testifying in court …

Cyberbullying has emerged as a pervasive issue in the digital age, necessitating advanced
techniques for effective detection and mitigation. This research explores the integration of …

We conduct a comparison of pre-trained encoder-only and decoder-only language models
with and without continued pre-training, to detect online sexism. Our fine-tuning-based …

Automated textual cyberbullying detection is known to be a challenging task. It is sometimes
expected that messages associated with bullying will either be a) abusive, b) targeted at a …

Cyberbullying, characterized by digital abuse such as harassment and doxing, has become
prevalent on social media platforms, mainly targeting despised groups. Victims often endure …

Abstract The integration of Machine Learning (ML) and Artificial Intelligence (AI) algorithms
has radically changed predictive modeling and classification tasks, enhancing a multitude of …

With cyberbullying surging across social media, this study investigates the effectiveness of
four prominent deep learning models–CNN, Bi-LSTM, GRU, and LSTM–in identifying …