Euphemism Detection

Euphemism detection, the computational identification of euphemisms within text, aims to automatically classify words or phrases as euphemistic or literal based on context. Current research heavily utilizes transformer-based models, such as RoBERTa and XLM-RoBERTa, often enhanced with techniques like data augmentation and k-nearest neighbor methods, to achieve high accuracy in this challenging task. This field is significant for advancing natural language processing capabilities and has implications for various applications, including sentiment analysis, hate speech detection, and the understanding of subtle linguistic nuances in communication.