Subjectivity Detection

Subjectivity detection aims to automatically identify subjective statements (opinions, beliefs) within text, distinguishing them from objective facts. Current research heavily utilizes transformer-based models like BERT and RoBERTa, often enhanced with hybrid approaches incorporating lexicon-based systems or multi-task learning frameworks to improve accuracy and address challenges like language bias and class imbalance. This field is crucial for applications ranging from combating misinformation and enhancing news credibility to understanding public sentiment in social media and improving the objectivity of information systems.