Hate Speech

Hate speech, encompassing discriminatory and derogatory language targeting individuals or groups, is a significant online problem. Current research focuses on improving automated hate speech detection, employing various deep learning models like BERT, LSTM, and transformer-based architectures, often incorporating multimodal data (text and images) and addressing challenges like implicit hate, code-mixing, and cross-cultural variations. These efforts aim to enhance the accuracy and fairness of hate speech detection systems, ultimately contributing to safer online environments and informing content moderation strategies. The field also explores methods for generating counterspeech and mitigating biases within detection models.