Abdulhakeem Ibrahim

Evaluation Artefacts in Deep Hate Speech Detection: A Reproduction Study and a Character-Aware Model Robust to Adversarial Obfuscation

Automated hate speech detection is routinely reported at accuracies above 98%. We show that for two widely cited systems such figures are substantially artefacts of how their evaluation corpora were built, and we propose a model and protocol designed to avoid the same traps. First, we reproduce Ali et al. (2023) and Ki...