Publications

Social media platforms offer avenues for fostering anonymous online connections, discussions on diverse topics likeculture, politics, and community life. However, the proliferation of hate speech poses a pressing challenge forsociety, individuals, policymakers, and researchers alike, both on the continent and globally. Addressing this issuenecessitates comprehensive studies to identify and combat hate speech effectively. This paper conducts a systematicreview of literature in this domain, concentrating on methodologies such as word embedding, machine learning,deep learning, and cutting-edge technologies. Specifically focusing on the past six years of research, this reviewhighlights gaps, challenges, and advancements in hate speech detection techniques. Additionally, it delves intolimitations, algorithmic selection dilemmas, data collection complexities, cleaning challenges, and outlines futureresearch pathways in this critical area.Keywords: Hate Speech Detection, Machine Learning, Social Media Platforms, Text Analysis, AlgorithmSelection.